diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index a2f110fd..0206c115 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -49,10 +49,10 @@ jobs:
       - name: run pre-commit
         if: ${{ matrix.python-version == env.LATEST_PY_VERSION }}
         run: |
-          uv run pre-commit run --all-files
+          uv run pre-commit run --all-files --verbose --show-diff-on-failure
 
       - name: Run tests
-        run: uv run pytest
+        run: uv run pytest -n auto
 
   cdk-checks:
     needs: [tests]
diff --git a/.github/workflows/deploy-dev.yml b/.github/workflows/deploy-dev.yml
index a7d88e8e..ae50561e 100644
--- a/.github/workflows/deploy-dev.yml
+++ b/.github/workflows/deploy-dev.yml
@@ -31,6 +31,8 @@ jobs:
       TITILER_MULTIDIM_PYTHONWARNINGS: ignore
       TITILER_MULTIDIM_DEBUG: true
       TITILER_MULTIDIM_READER_ROLE_ARN: ${{ vars.TITILER_MULTIDIM_READER_ROLE_ARN }}
+      TITILER_MULTIDIM_AUTHORIZED_CHUNK_ACCESS: '{"s3://nasa-waterinsight/NLDAS3/forcing/daily/": {"anonymous": true}, "s3://podaac-ops-cumulus-protected/MUR-JPL-L4-GLOB-v4.1/": {"from_env": true}}'
+
 
     steps:
       - name: Determine branch to deploy
diff --git a/.gitignore b/.gitignore
index 7bb7a5dd..25e77dc8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -105,5 +105,6 @@ cdk.out/
 node_modules
 cdk.context.json
 *.nc
+.DS_Store
 
 .test-deploy-env
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 10a63804..9477d10b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -9,13 +9,19 @@ repos:
     hooks:
       - id: ruff
         args: ["--fix"]
+        exclude: ^notebooks/
       - id: ruff-format
+        exclude: ^notebooks/
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v0.991
+    rev: v1.13.0
     hooks:
       - id: mypy
-        language_version: python
+        language_version: python3.12
         exclude: tests/.*
         additional_dependencies:
         - types-attrs
+        - types-redis
+        - types-requests
+        - boto3-stubs
+        - types-aiobotocore
diff --git a/README.md b/README.md
index 72717068..bc2d37c4 100644
--- a/README.md
+++ b/README.md
@@ -14,6 +14,8 @@ Example of application built with `titiler.xarray` [package](https://development
 # It's recommended to install dependencies in a virtual environment
 uv sync --dev
 export TEST_ENVIRONMENT=true  # set this when running locally to mock redis
+#optional: Disable caching
+#export TITILER_MULTIDIM_ENABLE_CACHE=false
 uv run uvicorn titiler.multidim.main:app --reload
 ```
 
@@ -94,3 +96,4 @@ The following steps detail how to to setup and deploy the CDK stack from your lo
 
 In AWS Lambda environment we need to have specific version of botocore, S3FS, FSPEC and other libraries.
 To make sure the application will both work locally and in AWS Lambda environment you can install the dependencies using `python -m pip install -r infrastructure/aws/requirement-lambda.txt`
+
diff --git a/infrastructure/aws/cdk/config.py b/infrastructure/aws/cdk/config.py
index fe5eff0c..a311ab1e 100644
--- a/infrastructure/aws/cdk/config.py
+++ b/infrastructure/aws/cdk/config.py
@@ -96,6 +96,20 @@ class AppSettings(BaseSettings):
         description="Optional root path for all api endpoints",
     )
 
+    # Authorization config for icechunk virtual chunks
+    # This will be passed through to the Lambda as an environment variable
+    authorized_chunk_access: Optional[str] = Field(
+        None,
+        description="JSON string for authorizing virtual chunk access in icechunk datasets",
+    )
+
+    def model_post_init(self, __context):
+        """Add authorized_chunk_access to additional_env if set."""
+        if self.authorized_chunk_access:
+            self.additional_env["TITILER_MULTIDIM_AUTHORIZED_CHUNK_ACCESS"] = (
+                self.authorized_chunk_access
+            )
+
     class Config:
         """model config"""
 
diff --git a/infrastructure/aws/lambda/Dockerfile b/infrastructure/aws/lambda/Dockerfile
index 8edb84ec..faa87fbb 100644
--- a/infrastructure/aws/lambda/Dockerfile
+++ b/infrastructure/aws/lambda/Dockerfile
@@ -15,7 +15,8 @@ EOF
 FROM public.ecr.aws/lambda/python:${PYTHON_VERSION} AS builder
 COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
 
-RUN dnf install -y gcc-c++ && dnf clean all
+# Install system dependencies needed for compilation
+RUN dnf install -y gcc-c++ git && dnf clean all
 
 WORKDIR /build
 
diff --git a/notebooks/compare_xarray_representation.ipynb b/notebooks/compare_xarray_representation.ipynb
new file mode 100644
index 00000000..363a7a3b
--- /dev/null
+++ b/notebooks/compare_xarray_representation.ipynb
@@ -0,0 +1,144 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "67a69623",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/conda/envs/notebook/lib/python3.12/site-packages/numcodecs/zarr3.py:145: UserWarning: Numcodecs codecs are not in the Zarr version 3 specification and may not be supported by other zarr implementations.\n",
+      "  super().__init__(**codec_config)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import icechunk as ic\n",
+    "import xarray as xr\n",
+    "\n",
+    "storage = ic.s3_storage(\n",
+    "    bucket=\"nasa-eodc-public\",\n",
+    "    prefix=\"icechunk/MUR-JPL-L4-GLOB-v4.1-native-v0/\",\n",
+    "    anonymous=True,\n",
+    ")\n",
+    "repo = ic.Repository.open(storage=storage)\n",
+    "session = repo.readonly_session(\"main\")\n",
+    "ds_native = xr.open_zarr(session.store, consolidated=False, zarr_format=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "98b367d6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/conda/envs/notebook/lib/python3.12/site-packages/numcodecs/zarr3.py:145: UserWarning: Numcodecs codecs are not in the Zarr version 3 specification and may not be supported by other zarr implementations.\n",
+      "  super().__init__(**codec_config)\n"
+     ]
+    }
+   ],
+   "source": [
+    "storage = ic.s3_storage(\n",
+    "    bucket=\"nasa-eodc-public\",\n",
+    "    prefix=\"icechunk/MUR-JPL-L4-GLOB-v4.1-virtual-v2-p2\",\n",
+    "    anonymous=True,\n",
+    ")\n",
+    "config = ic.Repository.fetch_config(storage=storage)\n",
+    "vchunk_containers = config.virtual_chunk_containers.keys()\n",
+    "container_credentials = ic.containers_credentials(\n",
+    "    {k: ic.s3_credentials(from_env=True) for k in vchunk_containers}\n",
+    ")\n",
+    "repo = ic.Repository.open(\n",
+    "    storage=storage, authorize_virtual_chunk_access=container_credentials\n",
+    ")\n",
+    "session = repo.readonly_session(\"main\")\n",
+    "ds_virtual = xr.open_zarr(session.store, consolidated=False, zarr_format=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8e192805",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xr.testing.assert_equal(ds_native, ds_virtual.isel(time=[0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08744ab7-a08b-46b5-b773-e8c48454ba92",
+   "metadata": {},
+   "source": [
+    "## They are EXACTLY THE SAME! SO this must be some issue with the time selection?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "21381c94",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fddda7b0dd0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_virtual.isel(time=0, lon=slice(2000, 3000), lat=slice(2000, 3000))[\"analysed_sst\"].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3eccffd6-9996-4cc4-90c1-2f6ed8d0ece6",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/test_native_icechunk.ipynb b/notebooks/test_native_icechunk.ipynb
new file mode 100644
index 00000000..b95dfda8
--- /dev/null
+++ b/notebooks/test_native_icechunk.ipynb
@@ -0,0 +1,1576 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5cef0e5d-e906-4f95-a584-88ace76536f3",
+   "metadata": {},
+   "source": [
+    "Check out the test repo and figure out which time steps have data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "3347e3b1-90a1-4152-9921-f17a88024cee",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/conda/envs/notebook/lib/python3.12/site-packages/numcodecs/zarr3.py:145: UserWarning: Numcodecs codecs are not in the Zarr version 3 specification and may not be supported by other zarr implementations.\n",
+      "  super().__init__(**codec_config)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import icechunk as ic\n",
+    "import xarray as xr\n",
+    "\n",
+    "storage = ic.s3_storage(\n",
+    "    bucket=\"nasa-eodc-public\",\n",
+    "    prefix=\"icechunk/MUR-JPL-L4-GLOB-v4.1-native-v0/\",\n",
+    "    anonymous=True,\n",
+    ")\n",
+    "repo = ic.Repository.open(storage=storage)\n",
+    "session = repo.readonly_session(\"main\")\n",
+    "ds = xr.open_zarr(session.store, consolidated=False, zarr_format=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "67e79824",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 18GB\n",
+       "Dimensions:           (time: 1, lat: 17999, lon: 36000)\n",
+       "Coordinates:\n",
+       "  * lat               (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n",
+       "  * lon               (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time              (time) datetime64[ns] 8B 2024-06-02T09:00:00\n",
+       "Data variables:\n",
+       "    analysed_sst      (time, lat, lon) float64 5GB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "    analysis_error    (time, lat, lon) float64 5GB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "    mask              (time, lat, lon) float32 3GB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "    sea_ice_fraction  (time, lat, lon) float64 5GB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "Attributes: (12/42)\n",
+       "    metadata_link:              http://podaac.jpl.nasa.gov/ws/metadata/datase...\n",
+       "    creator_email:              ghrsst@podaac.jpl.nasa.gov\n",
+       "    acknowledgment:             Please acknowledge the use of these data with...\n",
+       "    easternmost_longitude:      180.0\n",
+       "    geospatial_lat_resolution:  0.009999999776482582\n",
+       "    netcdf_version_id:          4.1\n",
+       "    ...                         ...\n",
+       "    project:                    NASA Making Earth Science Data Records for Us...\n",
+       "    history:                    created at nominal 4-day latency; replaced nr...\n",
+       "    uuid:                       27665bc0-d5fc-11e1-9b23-0800200c9a66\n",
+       "    start_time:                 20240602T090000Z\n",
+       "    publisher_url:              http://www.ghrsst.org\n",
+       "    file_quality_level:         3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-27d65a0a-fa37-420f-a179-77dc7a620f36' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-27d65a0a-fa37-420f-a179-77dc7a620f36' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lat</span>: 17999</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4ba9ef6e-37ec-4ccc-840e-8548e38d1514' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4ba9ef6e-37ec-4ccc-840e-8548e38d1514' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.99 -89.98 ... 89.98 89.99</div><input id='attrs-638292c7-6c90-4af4-b628-e2f0084add38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-638292c7-6c90-4af4-b628-e2f0084add38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df21d4ea-802b-4917-a27a-080942956599' class='xr-var-data-in' type='checkbox'><label for='data-df21d4ea-802b-4917-a27a-080942956599' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.99, -89.98, -89.97, ...,  89.97,  89.98,  89.99],\n",
+       "      shape=(17999,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-6f6dbc00-22bb-4e51-a926-7c008d8399ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f6dbc00-22bb-4e51-a926-7c008d8399ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32aaf5b8-8087-4788-88d6-eae020e4e16b' class='xr-var-data-in' type='checkbox'><label for='data-32aaf5b8-8087-4788-88d6-eae020e4e16b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-179.99, -179.98, -179.97, ...,  179.98,  179.99,  180.  ],\n",
+       "      shape=(36000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-06-02T09:00:00</div><input id='attrs-d84db29d-2fc4-4871-a094-509b09377b3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d84db29d-2fc4-4871-a094-509b09377b3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08244801-10a4-4f94-ac83-29b9d457f6ba' class='xr-var-data-in' type='checkbox'><label for='data-08244801-10a4-4f94-ac83-29b9d457f6ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-06-02T09:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-75fbdc82-f988-4f9c-b6af-22a8275bdcc4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-75fbdc82-f988-4f9c-b6af-22a8275bdcc4' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>analysed_sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-071ed8b6-d18e-429e-aede-5cd841833886' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-071ed8b6-d18e-429e-aede-5cd841833886' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1041a536-e487-41ee-8de0-af73e80aa218' class='xr-var-data-in' type='checkbox'><label for='data-1041a536-e487-41ee-8de0-af73e80aa218' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>-32767</dd><dt><span>standard_name :</span></dt><dd>sea_surface_foundation_temperature</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.83 GiB </td>\n",
+       "                        <td> 15.98 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 324 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>analysis_error</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-09e25a0d-86ef-4ba2-b55a-c207c8a7d84a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09e25a0d-86ef-4ba2-b55a-c207c8a7d84a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42f14ae8-a1b7-4234-b9a3-cae278631b2d' class='xr-var-data-in' type='checkbox'><label for='data-42f14ae8-a1b7-4234-b9a3-cae278631b2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>long_name :</span></dt><dd>estimated error standard deviation of analysed_sst</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.83 GiB </td>\n",
+       "                        <td> 15.98 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 324 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-a03d3c68-9831-449c-a8ac-1c6b776a05a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a03d3c68-9831-449c-a8ac-1c6b776a05a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cae8e61a-2507-4183-a229-ee3a152bd943' class='xr-var-data-in' type='checkbox'><label for='data-cae8e61a-2507-4183-a229-ee3a152bd943' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>flag_masks :</span></dt><dd>[1, 2, 4, 8, 16]</dd><dt><span>valid_max :</span></dt><dd>31</dd><dt><span>flag_meanings :</span></dt><dd>open_sea land open_lake open_sea_with_ice_in_the_grid open_lake_with_ice_in_the_grid</dd><dt><span>long_name :</span></dt><dd>sea/land field composite mask</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.41 GiB </td>\n",
+       "                        <td> 7.99 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 324 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_ice_fraction</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-eb0778d5-1952-47fd-ab69-3c41cf35254e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb0778d5-1952-47fd-ab69-3c41cf35254e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b88b3b7e-561d-48b2-a6c6-b9a2aaa3449e' class='xr-var-data-in' type='checkbox'><label for='data-b88b3b7e-561d-48b2-a6c6-b9a2aaa3449e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>long_name :</span></dt><dd>sea ice area fraction</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.83 GiB </td>\n",
+       "                        <td> 15.98 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 324 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
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+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-197aecf4-9ff7-49a2-ac7a-db5be290b701' class='xr-section-summary-in' type='checkbox'  ><label for='section-197aecf4-9ff7-49a2-ac7a-db5be290b701' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-ed6c8522-51e4-4556-8e7a-6659b4cb0d1c' class='xr-index-data-in' type='checkbox'/><label for='index-ed6c8522-51e4-4556-8e7a-6659b4cb0d1c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.98999786376953,  -89.9800033569336, -89.97000122070312,\n",
+       "       -89.95999908447266, -89.94999694824219, -89.94000244140625,\n",
+       "       -89.93000030517578, -89.91999816894531, -89.91000366210938,\n",
+       "        -89.9000015258789,\n",
+       "       ...\n",
+       "         89.9000015258789,  89.91000366210938,  89.91999816894531,\n",
+       "        89.93000030517578,  89.94000244140625,  89.94999694824219,\n",
+       "        89.95999908447266,  89.97000122070312,   89.9800033569336,\n",
+       "        89.98999786376953],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=17999))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-8fa9a1c3-46a6-47fe-aa8d-57f28ef16686' class='xr-index-data-in' type='checkbox'/><label for='index-8fa9a1c3-46a6-47fe-aa8d-57f28ef16686' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99000549316406, -179.97999572753906, -179.97000122070312,\n",
+       "        -179.9600067138672,  -179.9499969482422, -179.94000244140625,\n",
+       "       -179.92999267578125,  -179.9199981689453, -179.91000366210938,\n",
+       "       -179.89999389648438,\n",
+       "       ...\n",
+       "        179.91000366210938,   179.9199981689453,  179.92999267578125,\n",
+       "        179.94000244140625,   179.9499969482422,   179.9600067138672,\n",
+       "        179.97000122070312,  179.97999572753906,  179.99000549316406,\n",
+       "                     180.0],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-fe399616-cccc-4fe3-8a21-92d9ca677bee' class='xr-index-data-in' type='checkbox'/><label for='index-fe399616-cccc-4fe3-8a21-92d9ca677bee' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-06-02 09:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4e01447d-08c8-49ab-a293-44aba979e621' class='xr-section-summary-in' type='checkbox'  ><label for='section-4e01447d-08c8-49ab-a293-44aba979e621' class='xr-section-summary' >Attributes: <span>(42)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>metadata_link :</span></dt><dd>http://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&amp;shortName=MUR-JPL-L4-GLOB-v04.1</dd><dt><span>creator_email :</span></dt><dd>ghrsst@podaac.jpl.nasa.gov</dd><dt><span>acknowledgment :</span></dt><dd>Please acknowledge the use of these data with the following statement:  These data were provided by JPL under support by NASA MEaSUREs program.</dd><dt><span>easternmost_longitude :</span></dt><dd>180.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>netcdf_version_id :</span></dt><dd>4.1</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees east</dd><dt><span>institution :</span></dt><dd>Jet Propulsion Laboratory</dd><dt><span>publisher_email :</span></dt><dd>ghrsst-po@nceo.ac.uk</dd><dt><span>license :</span></dt><dd>These data are available free of charge under data policy of JPL PO.DAAC.</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Observation Dataset v1.0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>product_version :</span></dt><dd>04.1</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>stop_time :</span></dt><dd>20250928T090000Z</dd><dt><span>gds_version_id :</span></dt><dd>2.0</dd><dt><span>creator_url :</span></dt><dd>http://mur.jpl.nasa.gov</dd><dt><span>id :</span></dt><dd>MUR-JPL-L4-GLOB-v04.1</dd><dt><span>time_coverage_end :</span></dt><dd>20250928T210000Z</dd><dt><span>keywords :</span></dt><dd>Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>spatial_resolution :</span></dt><dd>0.01 degrees</dd><dt><span>creator_name :</span></dt><dd>JPL MUR SST project</dd><dt><span>publisher_name :</span></dt><dd>GHRSST Project Office</dd><dt><span>title :</span></dt><dd>Daily MUR SST, Final product</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees north</dd><dt><span>southernmost_latitude :</span></dt><dd>-90.0</dd><dt><span>naming_authority :</span></dt><dd>org.ghrsst</dd><dt><span>northernmost_latitude :</span></dt><dd>90.0</dd><dt><span>summary :</span></dt><dd>A merged, multi-sensor L4 Foundation SST analysis product from JPL.</dd><dt><span>references :</span></dt><dd>http://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SST</dd><dt><span>westernmost_longitude :</span></dt><dd>-180.0</dd><dt><span>time_coverage_start :</span></dt><dd>20240601T210000Z</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention</dd><dt><span>project :</span></dt><dd>NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Program</dd><dt><span>history :</span></dt><dd>created at nominal 4-day latency; replaced nrt (1-day latency) version.</dd><dt><span>uuid :</span></dt><dd>27665bc0-d5fc-11e1-9b23-0800200c9a66</dd><dt><span>start_time :</span></dt><dd>20240602T090000Z</dd><dt><span>publisher_url :</span></dt><dd>http://www.ghrsst.org</dd><dt><span>file_quality_level :</span></dt><dd>3</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 18GB\n",
+       "Dimensions:           (time: 1, lat: 17999, lon: 36000)\n",
+       "Coordinates:\n",
+       "  * lat               (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n",
+       "  * lon               (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time              (time) datetime64[ns] 8B 2024-06-02T09:00:00\n",
+       "Data variables:\n",
+       "    analysed_sst      (time, lat, lon) float64 5GB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    analysis_error    (time, lat, lon) float64 5GB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    mask              (time, lat, lon) float32 3GB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    sea_ice_fraction  (time, lat, lon) float64 5GB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "Attributes: (12/42)\n",
+       "    metadata_link:              http://podaac.jpl.nasa.gov/ws/metadata/datase...\n",
+       "    creator_email:              ghrsst@podaac.jpl.nasa.gov\n",
+       "    acknowledgment:             Please acknowledge the use of these data with...\n",
+       "    easternmost_longitude:      180.0\n",
+       "    geospatial_lat_resolution:  0.009999999776482582\n",
+       "    netcdf_version_id:          4.1\n",
+       "    ...                         ...\n",
+       "    project:                    NASA Making Earth Science Data Records for Us...\n",
+       "    history:                    created at nominal 4-day latency; replaced nr...\n",
+       "    uuid:                       27665bc0-d5fc-11e1-9b23-0800200c9a66\n",
+       "    start_time:                 20240602T090000Z\n",
+       "    publisher_url:              http://www.ghrsst.org\n",
+       "    file_quality_level:         3"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b87e55cc-7f83-4178-bfc1-9b3d5f21edbe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f1da0067ad0>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds[\"analysed_sst\"].isel(lon=slice(3000, 4000), lat=slice(5000, 6000)).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f90a2e42-4268-4696-b62e-ba0a75add9b5",
+   "metadata": {},
+   "source": [
+    "## Test the tilejson endpoint \n",
+    "\n",
+    "Adopted from https://github.com/developmentseed/titiler-cmr/blob/develop/docs/examples/xarray_backend_example.ipynb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0206c560",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "bf20f0d6-5e7b-498d-90e8-75a712d140d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "\n",
+    "import httpx\n",
+    "import xarray as xr\n",
+    "from folium import Map, TileLayer\n",
+    "\n",
+    "titiler_endpoint = (\n",
+    "    \"https://syonjbeb09.execute-api.us-west-2.amazonaws.com\"  # dev endpoint\n",
+    ")\n",
+    "\n",
+    "\n",
+    "variable = \"analysed_sst\"\n",
+    "datetime_ = ds.time.values[0]\n",
+    "url = \"s3://nasa-eodc-public/icechunk/MUR-JPL-L4-GLOB-v4.1-native-v0/\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4bd4f6a0-98b5-41ed-ae9f-5f22a7b7f5bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'tilejson': '2.2.0', 'version': '1.0.0', 'scheme': 'xyz', 'tiles': ['https://syonjbeb09.execute-api.us-west-2.amazonaws.com/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=s3%3A%2F%2Fnasa-eodc-public%2Ficechunk%2FMUR-JPL-L4-GLOB-v4.1-native-v0%2F&datetime=2024-06-02T09%3A00%3A00.000000000&variable=analysed_sst&rescale=270%2C300&colormap_name=blues_r&sel_method=nearest'], 'minzoom': 0, 'maxzoom': 6, 'bounds': [-179.99500549324037, -89.99499786365084, 180.0050000000763, 89.99499786365084], 'center': [0.00499725341796875, 0.0, 0]}\n"
+     ]
+    }
+   ],
+   "source": [
+    "r = httpx.get(\n",
+    "    f\"{titiler_endpoint}/WebMercatorQuad/tilejson.json\",\n",
+    "    params=(\n",
+    "        (\"url\", url),\n",
+    "        (\"datetime\", datetime_),\n",
+    "        (\"variable\", variable),\n",
+    "        (\"rescale\", \"270,300\"),\n",
+    "        (\"colormap_name\", \"blues_r\"),\n",
+    "        (\"sel_method\", \"nearest\"),\n",
+    "    ),\n",
+    ").json()\n",
+    "\n",
+    "print(r)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4258046a-e39f-481f-8f42-a9583791e08e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
+       "&lt;html&gt;\n",
+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-3.7.1.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap-glyphicons.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
+       "    \n",
+       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_8afc38ad22e689bfa35d53141bb5191d {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
+       "                    left: 0.0%;\n",
+       "                    top: 0.0%;\n",
+       "                }\n",
+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "\n",
+       "            &lt;style&gt;html, body {\n",
+       "                width: 100%;\n",
+       "                height: 100%;\n",
+       "                margin: 0;\n",
+       "                padding: 0;\n",
+       "            }\n",
+       "            &lt;/style&gt;\n",
+       "\n",
+       "            &lt;style&gt;#map {\n",
+       "                position:absolute;\n",
+       "                top:0;\n",
+       "                bottom:0;\n",
+       "                right:0;\n",
+       "                left:0;\n",
+       "                }\n",
+       "            &lt;/style&gt;\n",
+       "\n",
+       "            &lt;script&gt;\n",
+       "                L_NO_TOUCH = false;\n",
+       "                L_DISABLE_3D = false;\n",
+       "            &lt;/script&gt;\n",
+       "\n",
+       "        \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_8afc38ad22e689bfa35d53141bb5191d&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_8afc38ad22e689bfa35d53141bb5191d = L.map(\n",
+       "                &quot;map_8afc38ad22e689bfa35d53141bb5191d&quot;,\n",
+       "                {\n",
+       "                    center: [70.0, -40.0],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    ...{\n",
+       "  &quot;zoom&quot;: 3,\n",
+       "  &quot;zoomControl&quot;: true,\n",
+       "  &quot;preferCanvas&quot;: false,\n",
+       "}\n",
+       "\n",
+       "                }\n",
+       "            );\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_d09362058a19660a9363da225e6f0b1b = L.tileLayer(\n",
+       "                &quot;https://tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
+       "                {\n",
+       "  &quot;minZoom&quot;: 0,\n",
+       "  &quot;maxZoom&quot;: 19,\n",
+       "  &quot;maxNativeZoom&quot;: 19,\n",
+       "  &quot;noWrap&quot;: false,\n",
+       "  &quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;https://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors&quot;,\n",
+       "  &quot;subdomains&quot;: &quot;abc&quot;,\n",
+       "  &quot;detectRetina&quot;: false,\n",
+       "  &quot;tms&quot;: false,\n",
+       "  &quot;opacity&quot;: 1,\n",
+       "}\n",
+       "\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "            tile_layer_d09362058a19660a9363da225e6f0b1b.addTo(map_8afc38ad22e689bfa35d53141bb5191d);\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_8cf67ad73f7135df3a11dfc8fc15778a = L.tileLayer(\n",
+       "                &quot;https://syonjbeb09.execute-api.us-west-2.amazonaws.com/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=s3%3A%2F%2Fnasa-eodc-public%2Ficechunk%2FMUR-JPL-L4-GLOB-v4.1-native-v0%2F\\u0026datetime=2024-06-02T09%3A00%3A00.000000000\\u0026variable=analysed_sst\\u0026rescale=270%2C300\\u0026colormap_name=blues_r\\u0026sel_method=nearest&quot;,\n",
+       "                {\n",
+       "  &quot;minZoom&quot;: 0,\n",
+       "  &quot;maxZoom&quot;: 18,\n",
+       "  &quot;maxNativeZoom&quot;: 18,\n",
+       "  &quot;noWrap&quot;: false,\n",
+       "  &quot;attribution&quot;: &quot;NASA&quot;,\n",
+       "  &quot;subdomains&quot;: &quot;abc&quot;,\n",
+       "  &quot;detectRetina&quot;: false,\n",
+       "  &quot;tms&quot;: false,\n",
+       "  &quot;opacity&quot;: 1,\n",
+       "}\n",
+       "\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "            tile_layer_8cf67ad73f7135df3a11dfc8fc15778a.addTo(map_8afc38ad22e689bfa35d53141bb5191d);\n",
+       "        \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x12684a6f0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "bounds = r[\"bounds\"]\n",
+    "m = Map(location=(70, -40), zoom_start=3)\n",
+    "\n",
+    "TileLayer(\n",
+    "    tiles=r[\"tiles\"][0],\n",
+    "    opacity=1,\n",
+    "    attr=\"NASA\",\n",
+    ").add_to(m)\n",
+    "m"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9097f922-6c31-478b-ad87-e3e899eac8f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "  \"type\": \"FeatureCollection\",\n",
+      "  \"features\": [\n",
+      "    {\n",
+      "      \"type\": \"Feature\",\n",
+      "      \"geometry\": {\n",
+      "        \"type\": \"Polygon\",\n",
+      "        \"coordinates\": [\n",
+      "          [\n",
+      "            [\n",
+      "              -20.79973248834736,\n",
+      "              83.55979308678764\n",
+      "            ],\n",
+      "            [\n",
+      "              -20.79973248834736,\n",
+      "              75.0115425216471\n",
+      "            ],\n",
+      "            [\n",
+      "              14.483337068956956,\n",
+      "              75.0115425216471\n",
+      "            ],\n",
+      "            [\n",
+      "              14.483337068956956,\n",
+      "              83.55979308678764\n",
+      "            ],\n",
+      "            [\n",
+      "              -20.79973248834736,\n",
+      "              83.55979308678764\n",
+      "            ]\n",
+      "          ]\n",
+      "        ]\n",
+      "      },\n",
+      "      \"properties\": {\n",
+      "        \"statistics\": {\n",
+      "          \"2024-06-02T09:00:00.000000000\": {\n",
+      "            \"min\": 271.34999999999997,\n",
+      "            \"max\": 279.005,\n",
+      "            \"mean\": 272.71998336321025,\n",
+      "            \"count\": 2841063.5,\n",
+      "            \"sum\": 774814790.4538239,\n",
+      "            \"std\": 2.1572893578676204,\n",
+      "            \"median\": 271.351,\n",
+      "            \"majority\": 271.34999999999997,\n",
+      "            \"minority\": 279.005,\n",
+      "            \"unique\": 7656.0,\n",
+      "            \"histogram\": [\n",
+      "              [\n",
+      "                1883552,\n",
+      "                103947,\n",
+      "                130543,\n",
+      "                114416,\n",
+      "                100482,\n",
+      "                100568,\n",
+      "                133828,\n",
+      "                126908,\n",
+      "                124721,\n",
+      "                26225\n",
+      "              ],\n",
+      "              [\n",
+      "                271.34999999999997,\n",
+      "                272.1155,\n",
+      "                272.881,\n",
+      "                273.64649999999995,\n",
+      "                274.412,\n",
+      "                275.1775,\n",
+      "                275.943,\n",
+      "                276.70849999999996,\n",
+      "                277.474,\n",
+      "                278.2395,\n",
+      "                279.005\n",
+      "              ]\n",
+      "            ],\n",
+      "            \"valid_percent\": 94.19,\n",
+      "            \"masked_pixels\": 175634.0,\n",
+      "            \"valid_pixels\": 2845190.0,\n",
+      "            \"percentile_2\": 271.34999999999997,\n",
+      "            \"percentile_98\": 278.003\n",
+      "          }\n",
+      "        }\n",
+      "      }\n",
+      "    }\n",
+      "  ]\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "geojson_dict = {\n",
+    "    \"type\": \"FeatureCollection\",\n",
+    "    \"features\": [\n",
+    "        {\n",
+    "            \"type\": \"Feature\",\n",
+    "            \"properties\": {},\n",
+    "            \"geometry\": {\n",
+    "                \"coordinates\": [\n",
+    "                    [\n",
+    "                        [-20.79973248834736, 83.55979308678764],\n",
+    "                        [-20.79973248834736, 75.0115425216471],\n",
+    "                        [14.483337068956956, 75.0115425216471],\n",
+    "                        [14.483337068956956, 83.55979308678764],\n",
+    "                        [-20.79973248834736, 83.55979308678764],\n",
+    "                    ]\n",
+    "                ],\n",
+    "                \"type\": \"Polygon\",\n",
+    "            },\n",
+    "        }\n",
+    "    ],\n",
+    "}\n",
+    "\n",
+    "r = httpx.post(\n",
+    "    f\"{titiler_endpoint}/statistics\",\n",
+    "    params=(\n",
+    "        (\"url\", url),\n",
+    "        (\"datetime\", datetime_),\n",
+    "        (\"variable\", variable),\n",
+    "    ),\n",
+    "    json=geojson_dict,\n",
+    "    timeout=60,\n",
+    ").json()\n",
+    "\n",
+    "print(json.dumps(r, indent=2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "72a847b6-4db4-4a99-b9e2-52d549343a92",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/test_virtual_icechunk.ipynb b/notebooks/test_virtual_icechunk.ipynb
new file mode 100644
index 00000000..1e765687
--- /dev/null
+++ b/notebooks/test_virtual_icechunk.ipynb
@@ -0,0 +1,1663 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5cef0e5d-e906-4f95-a584-88ace76536f3",
+   "metadata": {},
+   "source": [
+    "Check out the test repo and figure out which time steps have data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "3347e3b1-90a1-4152-9921-f17a88024cee",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/conda/envs/notebook/lib/python3.12/site-packages/numcodecs/zarr3.py:145: UserWarning: Numcodecs codecs are not in the Zarr version 3 specification and may not be supported by other zarr implementations.\n",
+      "  super().__init__(**codec_config)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import icechunk as ic\n",
+    "import xarray as xr\n",
+    "\n",
+    "storage = ic.s3_storage(\n",
+    "    bucket=\"nasa-eodc-public\",\n",
+    "    prefix=\"icechunk/MUR-JPL-L4-GLOB-v4.1-virtual-v2-p2\",\n",
+    "    anonymous=True,\n",
+    ")\n",
+    "config = ic.Repository.fetch_config(storage=storage)\n",
+    "vchunk_containers = config.virtual_chunk_containers.keys()\n",
+    "container_credentials = ic.containers_credentials(\n",
+    "    {k: ic.s3_credentials(from_env=True) for k in vchunk_containers}\n",
+    ")\n",
+    "repo = ic.Repository.open(\n",
+    "    storage=storage, authorize_virtual_chunk_access=container_credentials\n",
+    ")\n",
+    "session = repo.readonly_session(\"main\")\n",
+    "ds = xr.open_zarr(session.store, consolidated=False, zarr_format=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "67e79824",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
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+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 9TB\n",
+       "Dimensions:           (time: 497, lat: 17999, lon: 36000)\n",
+       "Coordinates:\n",
+       "  * lat               (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n",
+       "  * lon               (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time              (time) datetime64[ns] 4kB 2024-06-02T09:00:00 ... 2025-...\n",
+       "Data variables:\n",
+       "    analysed_sst      (time, lat, lon) float64 3TB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "    analysis_error    (time, lat, lon) float64 3TB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "    sea_ice_fraction  (time, lat, lon) float64 3TB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "    mask              (time, lat, lon) float32 1TB dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;\n",
+       "Attributes: (12/42)\n",
+       "    metadata_link:              http://podaac.jpl.nasa.gov/ws/metadata/datase...\n",
+       "    creator_email:              ghrsst@podaac.jpl.nasa.gov\n",
+       "    acknowledgment:             Please acknowledge the use of these data with...\n",
+       "    easternmost_longitude:      180.0\n",
+       "    geospatial_lat_resolution:  0.009999999776482582\n",
+       "    netcdf_version_id:          4.1\n",
+       "    ...                         ...\n",
+       "    project:                    NASA Making Earth Science Data Records for Us...\n",
+       "    history:                    created at nominal 4-day latency; replaced nr...\n",
+       "    uuid:                       27665bc0-d5fc-11e1-9b23-0800200c9a66\n",
+       "    start_time:                 20240602T090000Z\n",
+       "    publisher_url:              http://www.ghrsst.org\n",
+       "    file_quality_level:         3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e5f92d75-9aa7-4e66-8764-b959e5a178f2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e5f92d75-9aa7-4e66-8764-b959e5a178f2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 497</li><li><span class='xr-has-index'>lat</span>: 17999</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b62aa813-d58a-42bb-b8ff-81a36280b5d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b62aa813-d58a-42bb-b8ff-81a36280b5d8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.99 -89.98 ... 89.98 89.99</div><input id='attrs-8f50eb9d-7e03-4563-bad9-f2a3c6ab1d02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f50eb9d-7e03-4563-bad9-f2a3c6ab1d02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-508fd74e-7dda-4c6a-b945-d190fbd13bff' class='xr-var-data-in' type='checkbox'><label for='data-508fd74e-7dda-4c6a-b945-d190fbd13bff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.99, -89.98, -89.97, ...,  89.97,  89.98,  89.99],\n",
+       "      shape=(17999,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-ad398398-036f-4a3d-ab15-44890b3e5823' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad398398-036f-4a3d-ab15-44890b3e5823' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbd9ab9d-6c50-49c3-81f5-829032e48841' class='xr-var-data-in' type='checkbox'><label for='data-bbd9ab9d-6c50-49c3-81f5-829032e48841' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-179.99, -179.98, -179.97, ...,  179.98,  179.99,  180.  ],\n",
+       "      shape=(36000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-06-02T09:00:00 ... 2025-10-...</div><input id='attrs-225ce51a-1a54-45bd-aa89-4bd0f5d7babf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-225ce51a-1a54-45bd-aa89-4bd0f5d7babf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cb70718-46a7-49e8-8b9d-7352b7075723' class='xr-var-data-in' type='checkbox'><label for='data-9cb70718-46a7-49e8-8b9d-7352b7075723' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-06-02T09:00:00.000000000&#x27;, &#x27;2024-06-03T09:00:00.000000000&#x27;,\n",
+       "       &#x27;2024-06-04T09:00:00.000000000&#x27;, ..., &#x27;2025-10-09T09:00:00.000000000&#x27;,\n",
+       "       &#x27;2025-10-10T09:00:00.000000000&#x27;, &#x27;2025-10-11T09:00:00.000000000&#x27;],\n",
+       "      shape=(497,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f76e7a88-26a6-4bab-99ec-83bb2f7a97f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f76e7a88-26a6-4bab-99ec-83bb2f7a97f3' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>analysed_sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-a2a1063c-0afc-4b40-a873-5f90d46e5724' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2a1063c-0afc-4b40-a873-5f90d46e5724' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72b50ef4-a968-42b2-86ca-ef8e76bdfefb' class='xr-var-data-in' type='checkbox'><label for='data-72b50ef4-a968-42b2-86ca-ef8e76bdfefb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>-32767</dd><dt><span>standard_name :</span></dt><dd>sea_surface_foundation_temperature</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.34 TiB </td>\n",
+       "                        <td> 15.98 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (497, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 161028 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"195\" height=\"125\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"25\" y2=\"15\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"3\" x2=\"25\" y2=\"19\" />\n",
+       "  <line x1=\"10\" y1=\"6\" x2=\"25\" y2=\"22\" />\n",
+       "  <line x1=\"10\" y1=\"10\" x2=\"25\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"13\" x2=\"25\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"17\" x2=\"25\" y2=\"32\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"25\" y2=\"36\" />\n",
+       "  <line x1=\"10\" y1=\"23\" x2=\"25\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"27\" x2=\"25\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"25\" y2=\"46\" />\n",
+       "  <line x1=\"10\" y1=\"34\" x2=\"25\" y2=\"49\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"25\" y2=\"53\" />\n",
+       "  <line x1=\"10\" y1=\"40\" x2=\"25\" y2=\"56\" />\n",
+       "  <line x1=\"10\" y1=\"44\" x2=\"25\" y2=\"60\" />\n",
+       "  <line x1=\"10\" y1=\"47\" x2=\"25\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"51\" x2=\"25\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"54\" x2=\"25\" y2=\"70\" />\n",
+       "  <line x1=\"10\" y1=\"57\" x2=\"25\" y2=\"73\" />\n",
+       "  <line x1=\"10\" y1=\"59\" x2=\"25\" y2=\"75\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>analysis_error</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-a382266f-9e2b-40c0-ab70-4d256c2aa35e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a382266f-9e2b-40c0-ab70-4d256c2aa35e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5df20a3b-591f-42ce-90fb-8c61cfc3a023' class='xr-var-data-in' type='checkbox'><label for='data-5df20a3b-591f-42ce-90fb-8c61cfc3a023' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>long_name :</span></dt><dd>estimated error standard deviation of analysed_sst</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.34 TiB </td>\n",
+       "                        <td> 15.98 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (497, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 161028 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_ice_fraction</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-86fa4f7b-faf1-4368-a76f-c410351241bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86fa4f7b-faf1-4368-a76f-c410351241bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45eea9a7-9f11-4a1e-8bb0-53c3fb64c01a' class='xr-var-data-in' type='checkbox'><label for='data-45eea9a7-9f11-4a1e-8bb0-53c3fb64c01a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>long_name :</span></dt><dd>sea ice area fraction</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.34 TiB </td>\n",
+       "                        <td> 15.98 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (497, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 161028 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1023, 2047), meta=np.ndarray&gt;</div><input id='attrs-80eb084d-412f-4c55-a919-e3a7057dbc07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80eb084d-412f-4c55-a919-e3a7057dbc07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-875b2603-7bfe-4c67-a570-96990fd0268d' class='xr-var-data-in' type='checkbox'><label for='data-875b2603-7bfe-4c67-a570-96990fd0268d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>flag_masks :</span></dt><dd>[1, 2, 4, 8, 16]</dd><dt><span>valid_max :</span></dt><dd>31</dd><dt><span>flag_meanings :</span></dt><dd>open_sea land open_lake open_sea_with_ice_in_the_grid open_lake_with_ice_in_the_grid</dd><dt><span>long_name :</span></dt><dd>sea/land field composite mask</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.17 TiB </td>\n",
+       "                        <td> 7.99 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (497, 17999, 36000) </td>\n",
+       "                        <td> (1, 1023, 2047) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 161028 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4149877f-0078-430b-95ec-d69a855bd2c4' class='xr-section-summary-in' type='checkbox'  ><label for='section-4149877f-0078-430b-95ec-d69a855bd2c4' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1c112557-8fd5-49b9-bfdd-676f00bab641' class='xr-index-data-in' type='checkbox'/><label for='index-1c112557-8fd5-49b9-bfdd-676f00bab641' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.98999786376953,  -89.9800033569336, -89.97000122070312,\n",
+       "       -89.95999908447266, -89.94999694824219, -89.94000244140625,\n",
+       "       -89.93000030517578, -89.91999816894531, -89.91000366210938,\n",
+       "        -89.9000015258789,\n",
+       "       ...\n",
+       "         89.9000015258789,  89.91000366210938,  89.91999816894531,\n",
+       "        89.93000030517578,  89.94000244140625,  89.94999694824219,\n",
+       "        89.95999908447266,  89.97000122070312,   89.9800033569336,\n",
+       "        89.98999786376953],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=17999))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-eb244381-638e-4c88-9a74-047ee1351115' class='xr-index-data-in' type='checkbox'/><label for='index-eb244381-638e-4c88-9a74-047ee1351115' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99000549316406, -179.97999572753906, -179.97000122070312,\n",
+       "        -179.9600067138672,  -179.9499969482422, -179.94000244140625,\n",
+       "       -179.92999267578125,  -179.9199981689453, -179.91000366210938,\n",
+       "       -179.89999389648438,\n",
+       "       ...\n",
+       "        179.91000366210938,   179.9199981689453,  179.92999267578125,\n",
+       "        179.94000244140625,   179.9499969482422,   179.9600067138672,\n",
+       "        179.97000122070312,  179.97999572753906,  179.99000549316406,\n",
+       "                     180.0],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f9dec35f-499a-441f-992c-86d99aeed25f' class='xr-index-data-in' type='checkbox'/><label for='index-f9dec35f-499a-441f-992c-86d99aeed25f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-06-02 09:00:00&#x27;, &#x27;2024-06-03 09:00:00&#x27;,\n",
+       "               &#x27;2024-06-04 09:00:00&#x27;, &#x27;2024-06-05 09:00:00&#x27;,\n",
+       "               &#x27;2024-06-06 09:00:00&#x27;, &#x27;2024-06-07 09:00:00&#x27;,\n",
+       "               &#x27;2024-06-08 09:00:00&#x27;, &#x27;2024-06-09 09:00:00&#x27;,\n",
+       "               &#x27;2024-06-10 09:00:00&#x27;, &#x27;2024-06-11 09:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2025-10-02 09:00:00&#x27;, &#x27;2025-10-03 09:00:00&#x27;,\n",
+       "               &#x27;2025-10-04 09:00:00&#x27;, &#x27;2025-10-05 09:00:00&#x27;,\n",
+       "               &#x27;2025-10-06 09:00:00&#x27;, &#x27;2025-10-07 09:00:00&#x27;,\n",
+       "               &#x27;2025-10-08 09:00:00&#x27;, &#x27;2025-10-09 09:00:00&#x27;,\n",
+       "               &#x27;2025-10-10 09:00:00&#x27;, &#x27;2025-10-11 09:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=497, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-45a1d8bf-28b8-4ea3-8a7e-8c7ca0a96a53' class='xr-section-summary-in' type='checkbox'  ><label for='section-45a1d8bf-28b8-4ea3-8a7e-8c7ca0a96a53' class='xr-section-summary' >Attributes: <span>(42)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>metadata_link :</span></dt><dd>http://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&amp;shortName=MUR-JPL-L4-GLOB-v04.1</dd><dt><span>creator_email :</span></dt><dd>ghrsst@podaac.jpl.nasa.gov</dd><dt><span>acknowledgment :</span></dt><dd>Please acknowledge the use of these data with the following statement:  These data were provided by JPL under support by NASA MEaSUREs program.</dd><dt><span>easternmost_longitude :</span></dt><dd>180.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>netcdf_version_id :</span></dt><dd>4.1</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees east</dd><dt><span>institution :</span></dt><dd>Jet Propulsion Laboratory</dd><dt><span>publisher_email :</span></dt><dd>ghrsst-po@nceo.ac.uk</dd><dt><span>license :</span></dt><dd>These data are available free of charge under data policy of JPL PO.DAAC.</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Observation Dataset v1.0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>product_version :</span></dt><dd>04.1</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>stop_time :</span></dt><dd>20251011T090000Z</dd><dt><span>gds_version_id :</span></dt><dd>2.0</dd><dt><span>creator_url :</span></dt><dd>http://mur.jpl.nasa.gov</dd><dt><span>id :</span></dt><dd>MUR-JPL-L4-GLOB-v04.1</dd><dt><span>time_coverage_end :</span></dt><dd>20251011T210000Z</dd><dt><span>keywords :</span></dt><dd>Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>spatial_resolution :</span></dt><dd>0.01 degrees</dd><dt><span>creator_name :</span></dt><dd>JPL MUR SST project</dd><dt><span>publisher_name :</span></dt><dd>GHRSST Project Office</dd><dt><span>title :</span></dt><dd>Daily MUR SST, Final product</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees north</dd><dt><span>southernmost_latitude :</span></dt><dd>-90.0</dd><dt><span>naming_authority :</span></dt><dd>org.ghrsst</dd><dt><span>northernmost_latitude :</span></dt><dd>90.0</dd><dt><span>summary :</span></dt><dd>A merged, multi-sensor L4 Foundation SST analysis product from JPL.</dd><dt><span>references :</span></dt><dd>http://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SST</dd><dt><span>westernmost_longitude :</span></dt><dd>-180.0</dd><dt><span>time_coverage_start :</span></dt><dd>20240601T210000Z</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention</dd><dt><span>project :</span></dt><dd>NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Program</dd><dt><span>history :</span></dt><dd>created at nominal 4-day latency; replaced nrt (1-day latency) version.</dd><dt><span>uuid :</span></dt><dd>27665bc0-d5fc-11e1-9b23-0800200c9a66</dd><dt><span>start_time :</span></dt><dd>20240602T090000Z</dd><dt><span>publisher_url :</span></dt><dd>http://www.ghrsst.org</dd><dt><span>file_quality_level :</span></dt><dd>3</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 9TB\n",
+       "Dimensions:           (time: 497, lat: 17999, lon: 36000)\n",
+       "Coordinates:\n",
+       "  * lat               (lat) float32 72kB -89.99 -89.98 -89.97 ... 89.98 89.99\n",
+       "  * lon               (lon) float32 144kB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time              (time) datetime64[ns] 4kB 2024-06-02T09:00:00 ... 2025-...\n",
+       "Data variables:\n",
+       "    analysed_sst      (time, lat, lon) float64 3TB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    analysis_error    (time, lat, lon) float64 3TB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    sea_ice_fraction  (time, lat, lon) float64 3TB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "    mask              (time, lat, lon) float32 1TB dask.array<chunksize=(1, 1023, 2047), meta=np.ndarray>\n",
+       "Attributes: (12/42)\n",
+       "    metadata_link:              http://podaac.jpl.nasa.gov/ws/metadata/datase...\n",
+       "    creator_email:              ghrsst@podaac.jpl.nasa.gov\n",
+       "    acknowledgment:             Please acknowledge the use of these data with...\n",
+       "    easternmost_longitude:      180.0\n",
+       "    geospatial_lat_resolution:  0.009999999776482582\n",
+       "    netcdf_version_id:          4.1\n",
+       "    ...                         ...\n",
+       "    project:                    NASA Making Earth Science Data Records for Us...\n",
+       "    history:                    created at nominal 4-day latency; replaced nr...\n",
+       "    uuid:                       27665bc0-d5fc-11e1-9b23-0800200c9a66\n",
+       "    start_time:                 20240602T090000Z\n",
+       "    publisher_url:              http://www.ghrsst.org\n",
+       "    file_quality_level:         3"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b87e55cc-7f83-4178-bfc1-9b3d5f21edbe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f55dd05b1d0>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds[\"analysed_sst\"].isel(lon=slice(3000, 4000), lat=slice(5000, 6000), time=0).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f90a2e42-4268-4696-b62e-ba0a75add9b5",
+   "metadata": {},
+   "source": [
+    "## Test the tilejson endpoint \n",
+    "\n",
+    "Adopted from https://github.com/developmentseed/titiler-cmr/blob/develop/docs/examples/xarray_backend_example.ipynb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "bf20f0d6-5e7b-498d-90e8-75a712d140d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "\n",
+    "import httpx\n",
+    "import xarray as xr\n",
+    "from folium import Map, TileLayer\n",
+    "\n",
+    "titiler_endpoint = (\n",
+    "    \"https://syonjbeb09.execute-api.us-west-2.amazonaws.com\"  # dev endpoint\n",
+    ")\n",
+    "\n",
+    "\n",
+    "variable = \"analysed_sst\"\n",
+    "datetime_ = ds.time.values[0]\n",
+    "url = \"s3://nasa-eodc-public/icechunk/MUR-JPL-L4-GLOB-v4.1-virtual-v2-p2\"\n",
+    "# url = \"s3://nasa-eodc-public/icechunk/MUR-JPL-L4-GLOB-v4.1-native-v0/\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4bd4f6a0-98b5-41ed-ae9f-5f22a7b7f5bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'tilejson': '2.2.0', 'version': '1.0.0', 'scheme': 'xyz', 'tiles': ['https://syonjbeb09.execute-api.us-west-2.amazonaws.com/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=s3%3A%2F%2Fnasa-eodc-public%2Ficechunk%2FMUR-JPL-L4-GLOB-v4.1-virtual-v2-p2&decode_times=false&datetime=2024-06-02T09%3A00%3A00.000000000&variable=analysed_sst&rescale=270%2C300&colormap_name=blues_r&sel_method=nearest'], 'minzoom': 0, 'maxzoom': 6, 'bounds': [-179.99500549324037, -89.99499786365084, 180.0050000000763, 89.99499786365084], 'center': [0.00499725341796875, 0.0, 0]}\n"
+     ]
+    }
+   ],
+   "source": [
+    "r = httpx.get(\n",
+    "    f\"{titiler_endpoint}/WebMercatorQuad/tilejson.json\",\n",
+    "    params=(\n",
+    "        (\"url\", url),\n",
+    "        (\"decode_times\", False),\n",
+    "        (\"datetime\", datetime_),\n",
+    "        (\"variable\", variable),\n",
+    "        (\"rescale\", \"270,300\"),\n",
+    "        (\"colormap_name\", \"blues_r\"),\n",
+    "        (\"sel_method\", \"nearest\"),\n",
+    "    ),\n",
+    ").json()\n",
+    "\n",
+    "print(r)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "08af389d-9076-4748-a0e8-2859d7867465",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4258046a-e39f-481f-8f42-a9583791e08e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
+       "&lt;html&gt;\n",
+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-3.7.1.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap-glyphicons.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
+       "    \n",
+       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_8c73653ec88fa87fc9d259b157f6969b {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
+       "                    left: 0.0%;\n",
+       "                    top: 0.0%;\n",
+       "                }\n",
+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "\n",
+       "            &lt;style&gt;html, body {\n",
+       "                width: 100%;\n",
+       "                height: 100%;\n",
+       "                margin: 0;\n",
+       "                padding: 0;\n",
+       "            }\n",
+       "            &lt;/style&gt;\n",
+       "\n",
+       "            &lt;style&gt;#map {\n",
+       "                position:absolute;\n",
+       "                top:0;\n",
+       "                bottom:0;\n",
+       "                right:0;\n",
+       "                left:0;\n",
+       "                }\n",
+       "            &lt;/style&gt;\n",
+       "\n",
+       "            &lt;script&gt;\n",
+       "                L_NO_TOUCH = false;\n",
+       "                L_DISABLE_3D = false;\n",
+       "            &lt;/script&gt;\n",
+       "\n",
+       "        \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_8c73653ec88fa87fc9d259b157f6969b&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_8c73653ec88fa87fc9d259b157f6969b = L.map(\n",
+       "                &quot;map_8c73653ec88fa87fc9d259b157f6969b&quot;,\n",
+       "                {\n",
+       "                    center: [70.0, -40.0],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    ...{\n",
+       "  &quot;zoom&quot;: 3,\n",
+       "  &quot;zoomControl&quot;: true,\n",
+       "  &quot;preferCanvas&quot;: false,\n",
+       "}\n",
+       "\n",
+       "                }\n",
+       "            );\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_a8a6232be0201b62a6296a4bacea0ffd = L.tileLayer(\n",
+       "                &quot;https://tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
+       "                {\n",
+       "  &quot;minZoom&quot;: 0,\n",
+       "  &quot;maxZoom&quot;: 19,\n",
+       "  &quot;maxNativeZoom&quot;: 19,\n",
+       "  &quot;noWrap&quot;: false,\n",
+       "  &quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;https://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors&quot;,\n",
+       "  &quot;subdomains&quot;: &quot;abc&quot;,\n",
+       "  &quot;detectRetina&quot;: false,\n",
+       "  &quot;tms&quot;: false,\n",
+       "  &quot;opacity&quot;: 1,\n",
+       "}\n",
+       "\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "            tile_layer_a8a6232be0201b62a6296a4bacea0ffd.addTo(map_8c73653ec88fa87fc9d259b157f6969b);\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_a1f9a4eac3ad7a4434ba03ac4caf540d = L.tileLayer(\n",
+       "                &quot;https://syonjbeb09.execute-api.us-west-2.amazonaws.com/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=s3%3A%2F%2Fnasa-eodc-public%2Ficechunk%2FMUR-JPL-L4-GLOB-v4.1-virtual-v2-p2\\u0026decode_times=false\\u0026datetime=2024-06-02T09%3A00%3A00.000000000\\u0026variable=analysed_sst\\u0026rescale=270%2C300\\u0026colormap_name=blues_r\\u0026sel_method=nearest&quot;,\n",
+       "                {\n",
+       "  &quot;minZoom&quot;: 0,\n",
+       "  &quot;maxZoom&quot;: 18,\n",
+       "  &quot;maxNativeZoom&quot;: 18,\n",
+       "  &quot;noWrap&quot;: false,\n",
+       "  &quot;attribution&quot;: &quot;NASA&quot;,\n",
+       "  &quot;subdomains&quot;: &quot;abc&quot;,\n",
+       "  &quot;detectRetina&quot;: false,\n",
+       "  &quot;tms&quot;: false,\n",
+       "  &quot;opacity&quot;: 1,\n",
+       "}\n",
+       "\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "            tile_layer_a1f9a4eac3ad7a4434ba03ac4caf540d.addTo(map_8c73653ec88fa87fc9d259b157f6969b);\n",
+       "        \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x7f3d18156630>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "bounds = r[\"bounds\"]\n",
+    "m = Map(location=(70, -40), zoom_start=3)\n",
+    "\n",
+    "TileLayer(\n",
+    "    tiles=r[\"tiles\"][0],\n",
+    "    opacity=1,\n",
+    "    attr=\"NASA\",\n",
+    ").add_to(m)\n",
+    "m"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "9097f922-6c31-478b-ad87-e3e899eac8f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "  \"detail\": \"Unable to allocate 11.2 GiB for an array with shape (497, 855, 3528) and data type float64\"\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "geojson_dict = {\n",
+    "    \"type\": \"FeatureCollection\",\n",
+    "    \"features\": [\n",
+    "        {\n",
+    "            \"type\": \"Feature\",\n",
+    "            \"properties\": {},\n",
+    "            \"geometry\": {\n",
+    "                \"coordinates\": [\n",
+    "                    [\n",
+    "                        [-20.79973248834736, 83.55979308678764],\n",
+    "                        [-20.79973248834736, 75.0115425216471],\n",
+    "                        [14.483337068956956, 75.0115425216471],\n",
+    "                        [14.483337068956956, 83.55979308678764],\n",
+    "                        [-20.79973248834736, 83.55979308678764],\n",
+    "                    ]\n",
+    "                ],\n",
+    "                \"type\": \"Polygon\",\n",
+    "            },\n",
+    "        }\n",
+    "    ],\n",
+    "}\n",
+    "\n",
+    "r = httpx.post(\n",
+    "    f\"{titiler_endpoint}/statistics\",\n",
+    "    params=(\n",
+    "        (\"url\", url),\n",
+    "        (\"datetime\", datetime_),\n",
+    "        (\"variable\", variable),\n",
+    "    ),\n",
+    "    json=geojson_dict,\n",
+    "    timeout=60,\n",
+    ").json()\n",
+    "\n",
+    "print(json.dumps(r, indent=2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "72a847b6-4db4-4a99-b9e2-52d549343a92",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/pyproject.toml b/pyproject.toml
index cc0ab158..7991e6e7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,8 +25,8 @@ classifiers = [
 ]
 dynamic = ["version"]
 dependencies = [
-    "titiler.core>=0.23.0,<0.24",
-    "titiler.xarray>=0.23.0,<0.24",
+    "titiler-core>=0.25.0,<0.26",
+    "titiler-xarray>=0.25.0,<0.26",
     "aiohttp",
     "aiobotocore>=2.24.0",
     "boto3>=1.39.0",
@@ -41,8 +41,9 @@ dependencies = [
     "requests",
     "rioxarray",
     "s3fs",
-    "xarray",
-    "zarr>=2,<3",
+    "xarray>=2025.10.1",
+    "zarr>3.1.0",
+    "icechunk>=1.1.9",
 ]
 
 [project.optional-dependencies]
@@ -56,6 +57,7 @@ lambda = [
 
 [dependency-groups]
 dev = [
+    "dask>=2025.9.1",
     "fakeredis>=2.23.5",
     "httpx",
     "ipykernel>=6.30.1",
@@ -65,8 +67,13 @@ dev = [
     "pytest-asyncio>=0.24.0",
     "pytest-cov>=5.0.0",
     "pytest>=8.3.2",
+    "pytest-xdist",
     "uvicorn>=0.34.0",
     "yappi>=1.6.0",
+    "virtualizarr",
+    "obstore",
+    "minio",
+    "docker",
 ]
 deployment = [
     "aws-cdk-lib~=2.177.0",
@@ -74,6 +81,11 @@ deployment = [
     "pydantic-settings~=2.0",
     "python-dotenv>=1.0.1",
 ]
+notebooks = [
+    "folium",
+    "httpx",
+    "matplotlib",
+]
 
 [project.urls]
 Homepage = "https://github.com/developmentseed/titiler-multidim"
@@ -97,6 +109,8 @@ known_first_party = ["titiler"]
 default_section = "THIRDPARTY"
 
 [tool.ruff]
+
+[tool.ruff.lint]
 select = [
     "D1",  # pydocstyle errors
     "E",  # pycodestyle errors
@@ -111,8 +125,9 @@ ignore = [
     "B905",  # ignore zip() without an explicit strict= parameter, only support with python >3.10
 ]
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 "tests/test_app.py" = ["D1"]
+"tests/test_reader.py" = ["D1"]
 "tests/fixtures/generate_test_zarr.py" = ["D1"]
 "tests/fixtures/generate_test_reference.py" = ["D1"]
 
@@ -126,8 +141,6 @@ explicit_package_bases = true
 requires = ["pdm-backend"]
 build-backend = "pdm.backend"
 
-
-
 [tool.pdm.version]
 source = "file"
 path = "src/titiler/multidim/__init__.py"
@@ -142,3 +155,4 @@ excludes = ["tests/", "**/.mypy_cache", "**/.DS_Store"]
 
 [tool.pytest.ini_options]
 addopts = "--cov=titiler.multidim --cov-report term-missing -s -vv"
+pythonpath = ["src", "tests"]
diff --git a/src/titiler/multidim/main.py b/src/titiler/multidim/main.py
index ce6509b1..99db5a10 100644
--- a/src/titiler/multidim/main.py
+++ b/src/titiler/multidim/main.py
@@ -90,7 +90,7 @@
     app.add_middleware(
         ServerTimingMiddleware,
         calls_to_track={
-            "1-xarray-open_dataset": (reader.xarray_open_dataset,),
+            "1-xarray-open_dataset": (reader.guess_opener,),
             "2-rioxarray-reproject": (rioxarray.raster_array.RasterArray.reproject,),
         },
     )
diff --git a/src/titiler/multidim/reader.py b/src/titiler/multidim/reader.py
index 73477235..1165f21d 100644
--- a/src/titiler/multidim/reader.py
+++ b/src/titiler/multidim/reader.py
@@ -1,24 +1,242 @@
 """XarrayReader"""
 
 import pickle
-from typing import Any, List, Optional
+import os
+from typing import Any, List, Optional, Dict
+from urllib.parse import urlparse
+
 
 import attr
+import xarray as xr
 
 from titiler.multidim.redis_pool import get_redis
 from titiler.multidim.settings import ApiSettings
 from titiler.xarray.io import Reader, get_variable, xarray_open_dataset
 
+try:
+    import icechunk
+except ImportError:  # pragma: nocover
+    icechunk = None  # type: ignore
+
+try:
+    import fsspec
+except ImportError:  # pragma: nocover
+    fsspec = None  # type: ignore
+
+try:
+    import obstore
+except ImportError:  # pragma: nocover
+    obstore = None  # type: ignore
+
+try:
+    import h5netcdf
+except ImportError:  # pragma: nocover
+    h5netcdf = None  # type: ignore
+
+try:
+    import zarr
+except ImportError:  # pragma: nocover
+    zarr = None  # type: ignore
+
 api_settings = ApiSettings()
 cache_client = get_redis()
 
 
+def opener_icechunk(
+    src_path: str,
+    group: Optional[Any] = None,
+    decode_times: bool = True,
+    authorize_virtual_chunk_access: Optional[Dict[str, Dict[str, Any]]] = None,
+) -> xr.Dataset:
+    """Open an IceChunk dataset using xarray."""
+    assert icechunk is not None, "'icechunk' must be installed to read icechunk dataset"
+
+    # TODO: This will likely be repeated across openers. Can we somehow handle this in the Reader Class?
+    parsed = urlparse(src_path)
+    protocol = parsed.scheme or "file"
+
+    authorize_virtual_chunk_access = authorize_virtual_chunk_access or {}
+
+    print(f"DEBUG: authorize_virtual_chunk_access = {authorize_virtual_chunk_access}")
+    if protocol == "file":
+        storage = icechunk.local_filesystem_storage(src_path)
+    elif protocol == "s3":
+        storage = icechunk.s3_storage(
+            bucket=parsed.netloc,
+            prefix=parsed.path.lstrip(
+                "/"
+            ),  # remove leading slash, this is an annoying mismatch between icechunk and urlparse
+            from_env=True,  # we always assume that we can get credentials from env vars or IAM role for the store itself?
+        )
+    else:
+        raise NotImplementedError(
+            f"icechunk storage for protocol {protocol} is not implemented"
+        )
+    # # I think it would be more elegant to get the virtual chunk containers and compare against authorized
+    # # containers from settings but that might be slow?
+    # config = icechunk.Repository.fetch_config(storage=storage)
+    # vchunk_containers = config.virtual_chunk_containers.keys()
+    # container_credentials = icechunk.containers_credentials(
+    #     {k: icechunk.s3_credentials(from_env=True) for k in vchunk_containers}
+    # )
+    # Only create credentials object if there are credentials to authorize
+    # Empty credentials dict causes PyString conversion errors in icechunk
+    vchunk_creds = (
+        icechunk.containers_credentials(
+            {
+                prefix: icechunk.s3_credentials(**auth_kwargs)
+                for prefix, auth_kwargs in authorize_virtual_chunk_access.items()
+            }
+        )
+        if authorize_virtual_chunk_access
+        else None
+    )
+
+    repo = icechunk.Repository.open(
+        storage=storage, authorize_virtual_chunk_access=vchunk_creds
+    )
+    print("DEBUG: opened icechunk repo")
+    session = repo.readonly_session("main")
+    store = session.store
+    return xr.open_dataset(
+        store,
+        group=group,
+        decode_times=decode_times,
+        engine="zarr",
+        consolidated=False,
+        zarr_format=3,
+    )
+
+
+# this is my hacky way of using obstore here, might want to check if there is a better way.
+def _is_dir(store, path: str = "") -> bool:  # TODO: type this properly.
+    """Return True if path is a prefix containing any objects (directory-like)."""
+    # sanitize path and slashes
+    path = path.rstrip("/") + "/"
+    stream = store.list(prefix=path, chunk_size=1)
+    try:
+        batch = next(stream)
+        return len(batch) > 0
+    except StopIteration:
+        return False
+
+
+def identify_storage_backend(src_path: str) -> str:
+    """Identify the storage backend for a given path."""
+    parsed = urlparse(src_path)
+    protocol = parsed.scheme or "file"
+
+    if protocol == "file":
+        store = obstore.store.LocalStore(src_path)
+    elif protocol == "s3":
+        store = obstore.store.S3Store(
+            bucket=parsed.netloc,
+            prefix=parsed.path.lstrip("/"),
+        )
+    else:
+        raise NotImplementedError(
+            f"Storage backend identification for protocol {protocol} is not implemented"
+        )
+
+    is_dir = _is_dir(store)
+    if not is_dir:
+        # assume this is a file, and detect the format based on the file extension
+        _, ext = os.path.splitext(parsed.path)
+        if ext in [".nc", ".nc4"]:
+            format = "h5netcdf"
+        else:
+            raise NotImplementedError(
+                f"File format identification for extension {ext} is not implemented"
+            )
+    else:
+        has_manifests = _is_dir(store, "manifests")
+        if has_manifests:
+            format = "icechunk"
+        else:
+            format = "zarr"
+    return format
+
+
+def guess_opener(
+    src_path: str,
+    group: Optional[Any] = None,
+    decode_times: bool = True,
+    authorize_virtual_chunk_access: Optional[Dict[str, Dict[str, Any]]] = None,
+    **kwargs: Any,
+) -> xr.Dataset:
+    """Guess the storage backend and return an xarray Dataset.
+
+    Args:
+        src_path: Path to the dataset
+        group: Optional group/subgroup to open
+        decode_times: Whether to decode time coordinates
+        authorize_virtual_chunk_access: Authorization config for icechunk virtual chunks
+        **kwargs: Additional arguments to pass to the opener
+
+    Returns:
+        xarray.Dataset
+    """
+
+    # Identify the storage backend
+    storage_format = identify_storage_backend(src_path)
+
+    if storage_format == "icechunk":
+        return opener_icechunk(
+            src_path,
+            group=group,
+            decode_times=decode_times,
+            authorize_virtual_chunk_access=authorize_virtual_chunk_access,
+        )
+    else:
+        # For zarr, h5netcdf, or other formats, use the standard xarray opener
+        return xarray_open_dataset(
+            src_path, group=group, decode_times=decode_times, **kwargs
+        )
+
+
+#     """Guess the appropriate opener based on the file extension."""
+#     # for now simply try the icechunk opener and if it fails, fall back to xarray open_dataset.
+#     # In the future we may want to be more specific about which opener to use either based on a config or some other heuristic
+
+#             s3_endpoint_url = os.environ.get("AWS_ENDPOINT_URL")
+#             if s3_endpoint_url:
+#                 # Check if the endpoint URL starts with 'http://' to determine if SSL should be disabled.
+#                 # This is necessary for local S3-compatible services like Minio that might not use HTTPS.
+#                 disable_ssl = s3_endpoint_url.startswith("http://")
+#                 store = obstore.Store.from_url(src_path, endpoint_url=s3_endpoint_url, disable_ssl=disable_ssl)
+#             else:
+#                 store = obstore.Store.from_url(src_path)        is_dir = store.is_dir("")
+#         manifests_exist = store.is_dir("manifests")
+#         print(f"obstore: is_dir={is_dir}, manifests_exist={manifests_exist}")
+#     except (ImportError, Exception) as e:
+#         print(f"obstore check failed: {e}")
+#         is_dir = os.path.isdir(src_path)
+#         manifests_exist = os.path.exists(os.path.join(src_path, "manifests"))
+#         print(f"os.path: is_dir={is_dir}, manifests_exist={manifests_exist}")
+
+
+#     if is_dir and manifests_exist:
+#         return opener_icechunk(
+#             src_path,
+#             group=group,
+#             decode_times=decode_times,
+#             authorize_virtual_chunk_access=settings[
+#                 "authorized_chunk_access"
+#             ],  # TODO this needs to be moved further up the stack so it can be passed in from the API call or some other config. For now we hardcode it here for testing purposes.
+#         )
+#     else:
+#         return xarray_open_dataset(
+#             src_path, group=group, decode_times=decode_times, **kwargs
+#         )
+
+
 @attr.s
 class XarrayReader(Reader):
     """Custom XarrayReader with redis cache"""
 
     def __attrs_post_init__(self):
         """Set bounds and CRS."""
+        self.opener = guess_opener
         ds = None
         # Generate cache key and attempt to fetch the dataset from cache
         cache_key = f"{self.src_path}_group:{self.group}_time:{self.decode_times}"
@@ -29,10 +247,17 @@ def __attrs_post_init__(self):
                 print(f"Found dataset in Cache {cache_key}")
                 ds = pickle.loads(data_bytes)
 
+        # If opener_options doesn't have authorize_virtual_chunk_access, use settings
+        if "authorize_virtual_chunk_access" not in self.opener_options:
+            self.opener_options["authorize_virtual_chunk_access"] = (
+                api_settings.authorized_chunk_access
+            )
+
         self.ds = ds or self.opener(
             self.src_path,
             group=self.group,
             decode_times=self.decode_times,
+            **self.opener_options,
         )
 
         if not ds and api_settings.enable_cache:
@@ -55,11 +280,21 @@ def list_variables(
         src_path: str,
         group: Optional[Any] = None,
         decode_times: bool = True,
+        opener_options: Optional[Dict[str, Any]] = None,
     ) -> List[str]:
         """List available variable in a dataset."""
-        with xarray_open_dataset(
+        # todo: why is this not a method of the reader class? Seems like a smell that I have to define the opener here again....
+        opener_options = opener_options or {}
+        # If opener_options doesn't have authorize_virtual_chunk_access, use settings
+        if "authorize_virtual_chunk_access" not in opener_options:
+            opener_options["authorize_virtual_chunk_access"] = (
+                api_settings.authorized_chunk_access
+            )
+
+        with guess_opener(
             src_path,
             group=group,
             decode_times=decode_times,
+            **opener_options,
         ) as ds:
             return list(ds.data_vars)  # type: ignore
diff --git a/src/titiler/multidim/settings.py b/src/titiler/multidim/settings.py
index 57ca2683..cf03b9d7 100644
--- a/src/titiler/multidim/settings.py
+++ b/src/titiler/multidim/settings.py
@@ -1,5 +1,8 @@
 """Titiler-xarray API settings."""
 
+import json
+from typing import Any, Dict
+
 from pydantic import field_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
@@ -18,6 +21,10 @@ class ApiSettings(BaseSettings):
     cache_host: str = "127.0.0.1"
     enable_cache: bool = True
 
+    # Configuration for authorizing virtual chunk access in icechunk datasets
+    # Format: {"s3://bucket/prefix/": {"anonymous": true}, "s3://other/": {"from_env": true}}
+    authorized_chunk_access: Dict[str, Dict[str, Any]] = {}
+
     @field_validator("cors_origins")
     def parse_cors_origin(cls, v):
         """Parse CORS origins."""
@@ -27,3 +34,13 @@ def parse_cors_origin(cls, v):
     def parse_cors_allow_methods(cls, v):
         """Parse CORS allowed methods."""
         return [method.strip().upper() for method in v.split(",")]
+
+    @field_validator("authorized_chunk_access", mode="before")
+    def parse_authorized_chunk_access(cls, v):
+        """Parse authorized_chunk_access from JSON string or dict."""
+        if isinstance(v, str):
+            try:
+                return json.loads(v)
+            except json.JSONDecodeError as e:
+                raise ValueError(f"Invalid JSON in authorized_chunk_access: {e}") from e
+        return v or {}
diff --git a/tests/conftest.py b/tests/conftest.py
index 09a793f2..9e6b73a8 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,15 +1,45 @@
-"""titiler.multidim tests configuration."""
+"""Auto-parametrized fixture that runs both cache configurations."""
 
+import json
+import sys
 import pytest
 from fastapi.testclient import TestClient
 
 
-@pytest.fixture
-def app(monkeypatch):
-    """App fixture."""
+# This fixture will automatically parametrize ALL tests that use it
+@pytest.fixture(
+    params=[
+        pytest.param({"cache": True}, id="with_cache"),
+        pytest.param({"cache": False}, id="without_cache"),
+    ]
+)
+def app(request, monkeypatch):
+    """Auto-parametrized app fixture that runs tests with both cache configurations."""
+    config = request.param
+    enable_cache = config.get("cache", False)
+
+    # Set environment variables using monkeypatch (auto-cleanup)
     monkeypatch.setenv("TITILER_MULTIDIM_DEBUG", "TRUE")
     monkeypatch.setenv("TEST_ENVIRONMENT", "1")
+    monkeypatch.setenv(
+        "TITILER_MULTIDIM_ENABLE_CACHE", "TRUE" if enable_cache else "FALSE"
+    )
+    # virtual container auth for icechunk tests
+    monkeypatch.setenv(
+        "TITILER_MULTIDIM_AUTHORIZED_CHUNK_ACCESS",
+        json.dumps(
+            {"s3://nasa-waterinsight/NLDAS3/forcing/daily/": {"anonymous": True}}
+        ),
+    )
+
+    # Clear module cache to ensure fresh import
+    modules_to_clear = [
+        key for key in sys.modules.keys() if key.startswith("titiler.multidim")
+    ]
+    for module in modules_to_clear:
+        del sys.modules[module]
 
+    # Import and return the app
     from titiler.multidim.main import app
 
     with TestClient(app) as client:
diff --git a/tests/fixtures/generate_test_icechunk.py b/tests/fixtures/generate_test_icechunk.py
new file mode 100644
index 00000000..9b09d873
--- /dev/null
+++ b/tests/fixtures/generate_test_icechunk.py
@@ -0,0 +1,60 @@
+"""Create icechunk fixtures (native and later virtual)."""
+# TODO: these files could also be generated together with the zarr files using the same data
+
+import numpy as np
+import xarray as xr
+import icechunk as ic
+
+# Define dimensions and chunk sizes
+res = 5
+time_dim = 10
+lat_dim = 36
+lon_dim = 72
+chunk_size = {"time": 10, "lat": 10, "lon": 10}
+
+# Create coordinates
+time = np.arange(time_dim)
+lat = np.linspace(-90.0 + res / 2, 90.0 - res / 2, lat_dim)
+lon = np.linspace(-180.0 + res / 2, 180.0 - res / 2, lon_dim)
+
+dtype = np.float64
+# Initialize variables with random data
+CDD0 = xr.DataArray(
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
+    dims=("time", "lat", "lon"),
+    name="CDD0",
+)
+DISPH = xr.DataArray(
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
+    dims=("time", "lat", "lon"),
+    name="DISPH",
+)
+FROST_DAYS = xr.DataArray(
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
+    dims=("time", "lat", "lon"),
+    name="FROST_DAYS",
+)
+GWETPROF = xr.DataArray(
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
+    dims=("time", "lat", "lon"),
+    name="GWETPROF",
+)
+
+# Create dataset
+ds = xr.Dataset(
+    {
+        "CDD0": CDD0.chunk(chunk_size),
+        "DISPH": DISPH.chunk(chunk_size),
+        "FROST_DAYS": FROST_DAYS.chunk(chunk_size),
+        "GWETPROF": GWETPROF.chunk(chunk_size),
+    },
+    coords={"time": time, "lat": lat, "lon": lon},
+)
+storage = ic.local_filesystem_storage("tests/fixtures/icechunk_native")
+config = ic.RepositoryConfig.default()
+repo = ic.Repository.create(storage=storage, config=config)
+session = repo.writable_session("main")
+store = session.store
+
+ds.to_zarr(store, consolidated=False)
+session.commit("Add initial data")
diff --git a/tests/fixtures/generate_test_icechunk_virtual.py b/tests/fixtures/generate_test_icechunk_virtual.py
new file mode 100644
index 00000000..8ac91192
--- /dev/null
+++ b/tests/fixtures/generate_test_icechunk_virtual.py
@@ -0,0 +1,61 @@
+"""Here we test generating icechunk virtual files"""
+
+from virtualizarr import open_virtual_mfdataset
+from virtualizarr.parsers import HDFParser
+from virtualizarr.registry import ObjectStoreRegistry
+
+import obstore
+import icechunk
+
+# NOTE: For now Ill build stores that are stored locally, but point to data on s3.
+# Eventually this should probably be built out with a bunch of different options? Not sure if local storage referencing local files would make sense?
+
+# Store that we cannot access from the tests (to ensure proper error handling) - MUR would fit the bill
+
+# Store that points to a public s3 bucket (Using NLDAS as examples - see https://github.com/virtual-zarr/nldas-icechunk/tree/master for details)
+
+urls = [
+    "s3://nasa-waterinsight/NLDAS3/forcing/daily/200101/NLDAS_FOR0010_D.A20010101.030.beta.nc",
+    "s3://nasa-waterinsight/NLDAS3/forcing/daily/200101/NLDAS_FOR0010_D.A20010102.030.beta.nc",
+    "s3://nasa-waterinsight/NLDAS3/forcing/daily/200101/NLDAS_FOR0010_D.A20010103.030.beta.nc",
+]
+
+bucket = "s3://nasa-waterinsight"
+store = obstore.store.from_url(bucket, region="us-west-2", skip_signature=True)
+registry = ObjectStoreRegistry({bucket: store})
+parser = HDFParser()
+
+vds = open_virtual_mfdataset(
+    urls,
+    parser=parser,
+    registry=registry,
+)
+
+storage = icechunk.local_filesystem_storage(
+    "tests/fixtures/icechunk_virtual_accessible"
+)
+
+config = icechunk.RepositoryConfig.default()
+config.set_virtual_chunk_container(
+    icechunk.VirtualChunkContainer(
+        "s3://nasa-waterinsight/NLDAS3/forcing/daily/",
+        icechunk.s3_store(region="us-west-2"),
+    )
+)
+
+virtual_credentials = icechunk.containers_credentials(
+    {
+        "s3://nasa-waterinsight/NLDAS3/forcing/daily/": icechunk.s3_anonymous_credentials()
+    }
+)
+
+repo = icechunk.Repository.open_or_create(
+    storage=storage,
+    config=config,
+    authorize_virtual_chunk_access=virtual_credentials,
+)
+
+session = repo.writable_session("main")
+vds.vz.to_icechunk(session.store)
+session.commit("Committed test dataset with virtual chunks")
+print("Done committing virtual dataset with publicly accessible chunk to icechunk repo")
diff --git a/tests/fixtures/generate_test_zarr.py b/tests/fixtures/generate_test_zarr.py
index 78900bee..66448207 100644
--- a/tests/fixtures/generate_test_zarr.py
+++ b/tests/fixtures/generate_test_zarr.py
@@ -1,4 +1,4 @@
-"""Create zarr fixture."""
+"""Create zarr fixtures for v2 and v3."""
 
 import numpy as np
 import xarray as xr
@@ -8,31 +8,32 @@
 time_dim = 10
 lat_dim = 36
 lon_dim = 72
-chunk_size = (10, 10, 10)
+chunk_size = {"time": 10, "lat": 10, "lon": 10}
 
 # Create coordinates
 time = np.arange(time_dim)
-lat = np.linspace(-90 + res / 2, 90 - res / 2, lat_dim)
-lon = np.linspace(-180 + res / 2, 180 - res / 2, lon_dim)
+lat = np.linspace(-90.0 + res / 2, 90.0 - res / 2, lat_dim)
+lon = np.linspace(-180.0 + res / 2, 180.0 - res / 2, lon_dim)
 
+dtype = np.float64
 # Initialize variables with random data
 CDD0 = xr.DataArray(
-    np.random.rand(time_dim, lat_dim, lon_dim).astype(np.uint8),
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
     dims=("time", "lat", "lon"),
     name="CDD0",
 )
 DISPH = xr.DataArray(
-    np.random.rand(time_dim, lat_dim, lon_dim).astype(np.uint8),
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
     dims=("time", "lat", "lon"),
     name="DISPH",
 )
 FROST_DAYS = xr.DataArray(
-    np.random.rand(time_dim, lat_dim, lon_dim).astype(np.uint8),
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
     dims=("time", "lat", "lon"),
     name="FROST_DAYS",
 )
 GWETPROF = xr.DataArray(
-    np.random.rand(time_dim, lat_dim, lon_dim).astype(np.uint8),
+    np.random.rand(time_dim, lat_dim, lon_dim).astype(dtype),
     dims=("time", "lat", "lon"),
     name="GWETPROF",
 )
@@ -49,4 +50,17 @@
 )
 
 # Save dataset to a local Zarr store
-ds.to_zarr("tests/fixtures/test_zarr_store.zarr", mode="w")
+ds.to_zarr(
+    "tests/fixtures/zarr_store_v3.zarr",
+    mode="w",
+    zarr_format=3,
+    consolidated=False,
+)
+
+# Save dataset to a local Zarr store
+ds.to_zarr(
+    "tests/fixtures/zarr_store_v2.zarr",
+    mode="w",
+    zarr_format=2,
+    consolidated=True,
+)
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diff --git a/tests/fixtures/icechunk_native/manifests/DA2BK1KS5MEN611YTKB0 b/tests/fixtures/icechunk_native/manifests/DA2BK1KS5MEN611YTKB0
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diff --git a/tests/fixtures/icechunk_native/manifests/V0HR8DHPN303QME8G6QG b/tests/fixtures/icechunk_native/manifests/V0HR8DHPN303QME8G6QG
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diff --git a/tests/fixtures/icechunk_native/refs/branch.main/ref.json b/tests/fixtures/icechunk_native/refs/branch.main/ref.json
new file mode 100644
index 00000000..b9854de2
--- /dev/null
+++ b/tests/fixtures/icechunk_native/refs/branch.main/ref.json
@@ -0,0 +1 @@
+{"snapshot":"X7NF54E8W362EQT4PJDG"}
\ No newline at end of file
diff --git a/tests/fixtures/icechunk_native/snapshots/1CECHNKREP0F1RSTCMT0 b/tests/fixtures/icechunk_native/snapshots/1CECHNKREP0F1RSTCMT0
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diff --git a/tests/fixtures/icechunk_virtual_accessible/chunks/3VM83JZ6YXVENDK42MJ0 b/tests/fixtures/icechunk_virtual_accessible/chunks/3VM83JZ6YXVENDK42MJ0
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diff --git a/tests/fixtures/icechunk_virtual_accessible/chunks/NMGAQQ6SKTEA9C0TK5G0 b/tests/fixtures/icechunk_virtual_accessible/chunks/NMGAQQ6SKTEA9C0TK5G0
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diff --git a/tests/fixtures/icechunk_virtual_accessible/config.yaml b/tests/fixtures/icechunk_virtual_accessible/config.yaml
new file mode 100644
index 00000000..d50d7300
--- /dev/null
+++ b/tests/fixtures/icechunk_virtual_accessible/config.yaml
@@ -0,0 +1,18 @@
+inline_chunk_threshold_bytes: null
+get_partial_values_concurrency: null
+compression: null
+max_concurrent_requests: null
+caching: null
+storage: null
+virtual_chunk_containers:
+  s3://nasa-waterinsight/NLDAS3/forcing/daily/:
+    name: null
+    url_prefix: s3://nasa-waterinsight/NLDAS3/forcing/daily/
+    store: !s3
+      region: us-west-2
+      endpoint_url: null
+      anonymous: false
+      allow_http: false
+      force_path_style: false
+      network_stream_timeout_seconds: 60
+manifest: null
diff --git a/tests/fixtures/icechunk_virtual_accessible/manifests/3DSZ7KZ1H0BEVXWDG8VG b/tests/fixtures/icechunk_virtual_accessible/manifests/3DSZ7KZ1H0BEVXWDG8VG
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diff --git a/tests/fixtures/icechunk_virtual_accessible/manifests/M3FEWMD68JVFZ83VVN4G b/tests/fixtures/icechunk_virtual_accessible/manifests/M3FEWMD68JVFZ83VVN4G
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diff --git a/tests/fixtures/icechunk_virtual_accessible/manifests/N8YD2MV2C4AY75KRX0C0 b/tests/fixtures/icechunk_virtual_accessible/manifests/N8YD2MV2C4AY75KRX0C0
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diff --git a/tests/fixtures/icechunk_virtual_accessible/manifests/RPNYSDFXG5C8HK9XX200 b/tests/fixtures/icechunk_virtual_accessible/manifests/RPNYSDFXG5C8HK9XX200
new file mode 100644
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diff --git a/tests/fixtures/icechunk_virtual_accessible/manifests/XBJ9KNQ117HM4X75EG6G b/tests/fixtures/icechunk_virtual_accessible/manifests/XBJ9KNQ117HM4X75EG6G
new file mode 100644
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diff --git a/tests/fixtures/icechunk_virtual_accessible/refs/branch.main/ref.json b/tests/fixtures/icechunk_virtual_accessible/refs/branch.main/ref.json
new file mode 100644
index 00000000..6265d207
--- /dev/null
+++ b/tests/fixtures/icechunk_virtual_accessible/refs/branch.main/ref.json
@@ -0,0 +1 @@
+{"snapshot":"80FX0M404MCT0R3665E0"}
\ No newline at end of file
diff --git a/tests/fixtures/icechunk_virtual_accessible/snapshots/1CECHNKREP0F1RSTCMT0 b/tests/fixtures/icechunk_virtual_accessible/snapshots/1CECHNKREP0F1RSTCMT0
new file mode 100644
index 00000000..321a7bd2
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diff --git a/tests/fixtures/icechunk_virtual_accessible/snapshots/80FX0M404MCT0R3665E0 b/tests/fixtures/icechunk_virtual_accessible/snapshots/80FX0M404MCT0R3665E0
new file mode 100644
index 00000000..18481174
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diff --git a/tests/fixtures/icechunk_virtual_accessible/transactions/80FX0M404MCT0R3665E0 b/tests/fixtures/icechunk_virtual_accessible/transactions/80FX0M404MCT0R3665E0
new file mode 100644
index 00000000..82b00475
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diff --git a/tests/fixtures/responses/icechunk_native_histogram.json b/tests/fixtures/responses/icechunk_native_histogram.json
new file mode 100644
index 00000000..520bb04b
--- /dev/null
+++ b/tests/fixtures/responses/icechunk_native_histogram.json
@@ -0,0 +1,42 @@
+[
+{
+  "bucket": [0.0007906359070823932, 0.10060333282002616],
+  "value": 278
+},
+{
+  "bucket": [0.10060333282002616, 0.20041602973296993],
+  "value": 229
+},
+{
+  "bucket": [0.20041602973296993, 0.3002287266459137],
+  "value": 265
+},
+{
+  "bucket": [0.3002287266459137, 0.40004142355885747],
+  "value": 298
+},
+{
+  "bucket": [0.40004142355885747, 0.4998541204718012],
+  "value": 257
+},
+{
+  "bucket": [0.4998541204718012, 0.599666817384745],
+  "value": 245
+},
+{
+  "bucket": [0.599666817384745, 0.6994795142976887],
+  "value": 252
+},
+{
+  "bucket": [0.6994795142976887, 0.7992922112106325],
+  "value": 244
+},
+{
+  "bucket": [0.7992922112106325, 0.8991049081235764],
+  "value": 242
+},
+{
+  "bucket": [0.8991049081235764, 0.99891760503652],
+  "value": 282
+}
+]
diff --git a/tests/fixtures/responses/icechunk_native_info.json b/tests/fixtures/responses/icechunk_native_info.json
new file mode 100644
index 00000000..f2a45e59
--- /dev/null
+++ b/tests/fixtures/responses/icechunk_native_info.json
@@ -0,0 +1,14 @@
+{
+    "bounds": [-180.0, -90.0, 180.0, 90.0],
+    "band_metadata": [["b1", {}]],
+    "band_descriptions": [["b1", "0"]],
+    "dtype": "float64",
+    "nodata_type": "Nodata",
+    "height": 36,
+    "count": 1,
+    "width": 72,
+    "attrs": {},
+    "crs": "http://www.opengis.net/def/crs/EPSG/0/4326",
+    "dimensions": ["y", "x"],
+    "name": "CDD0"
+}
diff --git a/tests/fixtures/responses/test_zarr_store_zarr_tilejson.json b/tests/fixtures/responses/icechunk_native_tilejson.json
similarity index 67%
rename from tests/fixtures/responses/test_zarr_store_zarr_tilejson.json
rename to tests/fixtures/responses/icechunk_native_tilejson.json
index 497b8ff6..41927a87 100644
--- a/tests/fixtures/responses/test_zarr_store_zarr_tilejson.json
+++ b/tests/fixtures/responses/icechunk_native_tilejson.json
@@ -1,9 +1,9 @@
 {
-  "tilejson": "2.2.0",
+  "tilejson": "3.0.0",
   "version": "1.0.0",
   "scheme": "xyz",
   "tiles": [
-    "http://testserver/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=tests%2Ffixtures%2Ftest_zarr_store.zarr&variable=CDD0&decode_times=false&sel=time%3D0"
+    "http://testserver/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=tests%2Ffixtures%2Ficechunk_native&variable=CDD0&decode_times=false&sel=time%3D0"
   ],
   "minzoom": 0,
   "maxzoom": 0,
diff --git a/tests/fixtures/responses/icechunk_virtual_accessible_histogram.json b/tests/fixtures/responses/icechunk_virtual_accessible_histogram.json
new file mode 100644
index 00000000..e7c33b48
--- /dev/null
+++ b/tests/fixtures/responses/icechunk_virtual_accessible_histogram.json
@@ -0,0 +1,42 @@
+[
+  {
+    "bucket": [126.3478012084961, 158.7461265563965],
+    "value": 610382
+  },
+  {
+    "bucket": [158.7461265563965, 191.1444519042969],
+    "value": 4513028
+  },
+  {
+    "bucket": [191.1444519042969, 223.54277725219725],
+    "value": 7084716
+  },
+  {
+    "bucket": [223.54277725219725, 255.94110260009765],
+    "value": 7813948
+  },
+  {
+    "bucket": [255.94110260009765, 288.33942794799805],
+    "value": 3784551
+  },
+  {
+    "bucket": [288.33942794799805, 320.7377532958984],
+    "value": 1173699
+  },
+  {
+    "bucket": [320.7377532958984, 353.1360786437988],
+    "value": 587492
+  },
+  {
+    "bucket": [353.1360786437988, 385.5344039916992],
+    "value": 548761
+  },
+  {
+    "bucket": [385.5344039916992, 417.9327293395996],
+    "value": 1071600
+  },
+  {
+    "bucket": [417.9327293395996, 450.3310546875],
+    "value": 57403
+  }
+]
\ No newline at end of file
diff --git a/tests/fixtures/responses/icechunk_virtual_accessible_info.json b/tests/fixtures/responses/icechunk_virtual_accessible_info.json
new file mode 100644
index 00000000..fb18f025
--- /dev/null
+++ b/tests/fixtures/responses/icechunk_virtual_accessible_info.json
@@ -0,0 +1,39 @@
+{
+    "bounds": [
+        -168.9999951170962,
+        7.000000114825381,
+        -51.99999725350927,
+        71.99999511680303
+    ],
+    "crs": "http://www.opengis.net/def/crs/EPSG/0/4326",
+    "band_metadata": [
+        [
+            "b1",
+            {}
+        ]
+    ],
+    "band_descriptions": [
+        [
+            "b1",
+            "1.0"
+        ]
+    ],
+    "dtype": "float64",
+    "nodata_type": "Nodata",
+    "name": "LWdown",
+    "count": 1,
+    "width": 11700,
+    "height": 6500,
+    "dimensions": [
+        "y",
+        "x"
+    ],
+    "attrs": {
+        "units": "W m-2",
+        "standard_name": "Surface incident longwave radiation",
+        "long_name": "Longwave radiation flux downwards (surface)",
+        "cell_methods": "time: mean",
+        "vmin": 126.3478012084961,
+        "vmax": 450.3310546875
+    }
+}
\ No newline at end of file
diff --git a/tests/fixtures/responses/icechunk_virtual_accessible_tilejson.json b/tests/fixtures/responses/icechunk_virtual_accessible_tilejson.json
new file mode 100644
index 00000000..297b1005
--- /dev/null
+++ b/tests/fixtures/responses/icechunk_virtual_accessible_tilejson.json
@@ -0,0 +1,21 @@
+{
+  "tilejson": "3.0.0",
+  "version": "1.0.0",
+  "scheme": "xyz",
+  "tiles": [
+    "http://testserver/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=tests%2Ffixtures%2Ficechunk_virtual_accessible&variable=LWdown&decode_times=false&sel=time%3D1.0"
+  ],
+  "minzoom": 1,
+  "maxzoom": 7,
+  "bounds": [
+    -168.9999951170962,
+    7.000000114825381,
+    -51.99999725350927,
+    71.99999511680303
+  ],
+  "center": [
+    -110.49999618530273,
+    39.49999761581421,
+    1
+  ]
+}
\ No newline at end of file
diff --git a/tests/fixtures/responses/pyramid_zarr_tilejson.json b/tests/fixtures/responses/pyramid_zarr_tilejson.json
index 0b0ac3e2..955219bc 100644
--- a/tests/fixtures/responses/pyramid_zarr_tilejson.json
+++ b/tests/fixtures/responses/pyramid_zarr_tilejson.json
@@ -1,5 +1,5 @@
 {
-  "tilejson": "2.2.0",
+  "tilejson": "3.0.0",
   "version": "1.0.0",
   "scheme": "xyz",
   "tiles": [
diff --git a/tests/fixtures/responses/reference_json_tilejson.json b/tests/fixtures/responses/reference_json_tilejson.json
index d10ea414..27b6af9c 100644
--- a/tests/fixtures/responses/reference_json_tilejson.json
+++ b/tests/fixtures/responses/reference_json_tilejson.json
@@ -1,5 +1,5 @@
 {
-  "tilejson": "2.2.0",
+  "tilejson": "3.0.0",
   "version": "1.0.0",
   "scheme": "xyz",
   "tiles": [
diff --git a/tests/fixtures/responses/reference_tilejson.json b/tests/fixtures/responses/reference_tilejson.json
index cf7099b1..707a2a38 100644
--- a/tests/fixtures/responses/reference_tilejson.json
+++ b/tests/fixtures/responses/reference_tilejson.json
@@ -1,5 +1,5 @@
 {
-    "tilejson": "2.2.0",
+    "tilejson": "3.0.0",
     "version": "1.0.0",
     "scheme": "xyz",
     "tiles": [
diff --git a/tests/fixtures/responses/refernce_tilejson.json b/tests/fixtures/responses/refernce_tilejson.json
index 976a619b..26962a10 100644
--- a/tests/fixtures/responses/refernce_tilejson.json
+++ b/tests/fixtures/responses/refernce_tilejson.json
@@ -1,5 +1,5 @@
 {
-    "tilejson": "2.2.0",
+    "tilejson": "3.0.0",
     "version": "1.0.0",
     "scheme": "xyz",
     "tiles": [
diff --git a/tests/fixtures/responses/test_CDD0_tilejson.json b/tests/fixtures/responses/test_CDD0_tilejson.json
index 242819b9..cf8b0ae8 100644
--- a/tests/fixtures/responses/test_CDD0_tilejson.json
+++ b/tests/fixtures/responses/test_CDD0_tilejson.json
@@ -1,5 +1,5 @@
 {
-    "tilejson": "2.2.0",
+    "tilejson": "3.0.0",
     "version": "1.0.0",
     "scheme": "xyz",
     "tiles": [
diff --git a/tests/fixtures/responses/test_zarr_store_info.json b/tests/fixtures/responses/test_zarr_store_info.json
deleted file mode 100644
index b8e44170..00000000
--- a/tests/fixtures/responses/test_zarr_store_info.json
+++ /dev/null
@@ -1,12 +0,0 @@
-{
-    "bounds": [-180, -90.0, 180.0, 90.0],
-    "band_metadata": [],
-    "band_descriptions": [],
-    "dtype": "float64",
-    "nodata_type": "None",
-    "height": 36,
-    "count": 1,
-    "width": 72,
-    "attrs": {},
-    "name": "CDD0"
-}
diff --git a/tests/fixtures/responses/test_zarr_store_zarr_histogram.json b/tests/fixtures/responses/test_zarr_store_zarr_histogram.json
deleted file mode 100644
index 384908e6..00000000
--- a/tests/fixtures/responses/test_zarr_store_zarr_histogram.json
+++ /dev/null
@@ -1,72 +0,0 @@
-[
-  {
-    "bucket": [
-      -0.5,
-      -0.4
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      -0.4,
-      -0.3
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      -0.3,
-      -0.19999999999999996
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      -0.19999999999999996,
-      -0.09999999999999998
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      -0.09999999999999998,
-      0.0
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      0.0,
-      0.10000000000000009
-    ],
-    "value": 2592
-  },
-  {
-    "bucket": [
-      0.10000000000000009,
-      0.20000000000000007
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      0.20000000000000007,
-      0.30000000000000004
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      0.30000000000000004,
-      0.4
-    ],
-    "value": 0
-  },
-  {
-    "bucket": [
-      0.4,
-      0.5
-    ],
-    "value": 0
-  }
-]
\ No newline at end of file
diff --git a/tests/fixtures/responses/test_zarr_store_zarr_info.json b/tests/fixtures/responses/test_zarr_store_zarr_info.json
deleted file mode 100644
index b8be05e7..00000000
--- a/tests/fixtures/responses/test_zarr_store_zarr_info.json
+++ /dev/null
@@ -1,14 +0,0 @@
-{
-  "bounds": [-180.0, -90.0, 180.0, 90.0],
-  "crs": "http://www.opengis.net/def/crs/EPSG/0/4326",
-  "band_metadata": [["b1", {}]],
-  "band_descriptions": [["b1", "0"]],
-  "dtype": "uint8",
-  "nodata_type": "None",
-  "name": "CDD0",
-  "count": 1,
-  "width": 72,
-  "height": 36,
-  "attrs": {},
-  "dimensions": ["y", "x"]
-}
diff --git a/tests/fixtures/responses/testfile_nc_tilejson.json b/tests/fixtures/responses/testfile_nc_tilejson.json
index 7d0d96e9..4af10fd4 100644
--- a/tests/fixtures/responses/testfile_nc_tilejson.json
+++ b/tests/fixtures/responses/testfile_nc_tilejson.json
@@ -1,5 +1,5 @@
 {
-  "tilejson": "2.2.0",
+  "tilejson": "3.0.0",
   "version": "1.0.0",
   "scheme": "xyz",
   "tiles": [
diff --git a/tests/fixtures/responses/unconsolidated_zarr_tilejson.json b/tests/fixtures/responses/unconsolidated_zarr_tilejson.json
index a496e83d..b41cbb13 100644
--- a/tests/fixtures/responses/unconsolidated_zarr_tilejson.json
+++ b/tests/fixtures/responses/unconsolidated_zarr_tilejson.json
@@ -1,5 +1,5 @@
 {
-  "tilejson": "2.2.0",
+  "tilejson": "3.0.0",
   "version": "1.0.0",
   "scheme": "xyz",
   "tiles": [
diff --git a/tests/fixtures/responses/zarr_store_v2_zarr_histogram.json b/tests/fixtures/responses/zarr_store_v2_zarr_histogram.json
new file mode 100644
index 00000000..6d805b3e
--- /dev/null
+++ b/tests/fixtures/responses/zarr_store_v2_zarr_histogram.json
@@ -0,0 +1,42 @@
+[
+  {
+    "bucket": [0.0005931922785458177, 0.10051167807017113],
+    "value": 215
+  },
+  {
+    "bucket": [0.10051167807017113, 0.20043016386179643],
+    "value": 263
+  },
+  {
+    "bucket": [0.20043016386179643, 0.30034864965342173],
+    "value": 260
+  },
+  {
+    "bucket": [0.30034864965342173, 0.40026713544504705],
+    "value": 277
+  },
+  {
+    "bucket": [0.40026713544504705, 0.5001856212366724],
+    "value": 251
+  },
+  {
+    "bucket": [0.5001856212366724, 0.6001041070282976],
+    "value": 265
+  },
+  {
+    "bucket": [0.6001041070282976, 0.700022592819923],
+    "value": 272
+  },
+  {
+    "bucket": [0.700022592819923, 0.7999410786115483],
+    "value": 279
+  },
+  {
+    "bucket": [0.7999410786115483, 0.8998595644031736],
+    "value": 269
+  },
+  {
+    "bucket": [0.8998595644031736, 0.9997780501947989],
+    "value": 241
+  }
+]
diff --git a/tests/fixtures/responses/zarr_store_v2_zarr_info.json b/tests/fixtures/responses/zarr_store_v2_zarr_info.json
new file mode 100644
index 00000000..b5014904
--- /dev/null
+++ b/tests/fixtures/responses/zarr_store_v2_zarr_info.json
@@ -0,0 +1,15 @@
+{
+    "bounds": [-180.0, -90.0, 180.0, 90.0],
+    "band_metadata": [["b1", {}]],
+    "band_descriptions": [["b1", "0"]],
+    "dtype": "float64",
+    "nodata_type": "Nodata",
+    "height": 36,
+    "count": 1,
+    "width": 72,
+    "attrs": {},
+    "crs": "http://www.opengis.net/def/crs/EPSG/0/4326",
+    "dimensions": ["y", "x"],
+    "name": "CDD0"
+}
+
diff --git a/tests/fixtures/responses/zarr_store_v2_zarr_tilejson.json b/tests/fixtures/responses/zarr_store_v2_zarr_tilejson.json
new file mode 100644
index 00000000..fe84aac5
--- /dev/null
+++ b/tests/fixtures/responses/zarr_store_v2_zarr_tilejson.json
@@ -0,0 +1,12 @@
+{
+  "tilejson": "3.0.0",
+  "version": "1.0.0",
+  "scheme": "xyz",
+  "tiles": [
+    "http://testserver/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=tests%2Ffixtures%2Fzarr_store_v2.zarr&variable=CDD0&decode_times=false&sel=time%3D0"
+  ],
+  "minzoom": 0,
+  "maxzoom": 0,
+  "bounds": [-180.0, -90.0, 180.0, 90.0],
+  "center": [0.0, 0.0, 0]
+}
diff --git a/tests/fixtures/responses/zarr_store_v3_zarr_histogram.json b/tests/fixtures/responses/zarr_store_v3_zarr_histogram.json
new file mode 100644
index 00000000..6d805b3e
--- /dev/null
+++ b/tests/fixtures/responses/zarr_store_v3_zarr_histogram.json
@@ -0,0 +1,42 @@
+[
+  {
+    "bucket": [0.0005931922785458177, 0.10051167807017113],
+    "value": 215
+  },
+  {
+    "bucket": [0.10051167807017113, 0.20043016386179643],
+    "value": 263
+  },
+  {
+    "bucket": [0.20043016386179643, 0.30034864965342173],
+    "value": 260
+  },
+  {
+    "bucket": [0.30034864965342173, 0.40026713544504705],
+    "value": 277
+  },
+  {
+    "bucket": [0.40026713544504705, 0.5001856212366724],
+    "value": 251
+  },
+  {
+    "bucket": [0.5001856212366724, 0.6001041070282976],
+    "value": 265
+  },
+  {
+    "bucket": [0.6001041070282976, 0.700022592819923],
+    "value": 272
+  },
+  {
+    "bucket": [0.700022592819923, 0.7999410786115483],
+    "value": 279
+  },
+  {
+    "bucket": [0.7999410786115483, 0.8998595644031736],
+    "value": 269
+  },
+  {
+    "bucket": [0.8998595644031736, 0.9997780501947989],
+    "value": 241
+  }
+]
diff --git a/tests/fixtures/responses/zarr_store_v3_zarr_info.json b/tests/fixtures/responses/zarr_store_v3_zarr_info.json
new file mode 100644
index 00000000..f2a45e59
--- /dev/null
+++ b/tests/fixtures/responses/zarr_store_v3_zarr_info.json
@@ -0,0 +1,14 @@
+{
+    "bounds": [-180.0, -90.0, 180.0, 90.0],
+    "band_metadata": [["b1", {}]],
+    "band_descriptions": [["b1", "0"]],
+    "dtype": "float64",
+    "nodata_type": "Nodata",
+    "height": 36,
+    "count": 1,
+    "width": 72,
+    "attrs": {},
+    "crs": "http://www.opengis.net/def/crs/EPSG/0/4326",
+    "dimensions": ["y", "x"],
+    "name": "CDD0"
+}
diff --git a/tests/fixtures/responses/zarr_store_v3_zarr_tilejson.json b/tests/fixtures/responses/zarr_store_v3_zarr_tilejson.json
new file mode 100644
index 00000000..9642ed5d
--- /dev/null
+++ b/tests/fixtures/responses/zarr_store_v3_zarr_tilejson.json
@@ -0,0 +1,12 @@
+{
+  "tilejson": "3.0.0",
+  "version": "1.0.0",
+  "scheme": "xyz",
+  "tiles": [
+    "http://testserver/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=tests%2Ffixtures%2Fzarr_store_v3.zarr&variable=CDD0&decode_times=false&sel=time%3D0"
+  ],
+  "minzoom": 0,
+  "maxzoom": 0,
+  "bounds": [-180.0, -90.0, 180.0, 90.0],
+  "center": [0.0, 0.0, 0]
+}
diff --git a/tests/fixtures/test_zarr_store.zarr/.zgroup b/tests/fixtures/test_zarr_store.zarr/.zgroup
deleted file mode 100644
index 3b7daf22..00000000
--- a/tests/fixtures/test_zarr_store.zarr/.zgroup
+++ /dev/null
@@ -1,3 +0,0 @@
-{
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/.zmetadata b/tests/fixtures/test_zarr_store.zarr/.zmetadata
deleted file mode 100644
index 5e3a9d2c..00000000
--- a/tests/fixtures/test_zarr_store.zarr/.zmetadata
+++ /dev/null
@@ -1,208 +0,0 @@
-{
-    "metadata": {
-        ".zattrs": {},
-        ".zgroup": {
-            "zarr_format": 2
-        },
-        "CDD0/.zarray": {
-            "chunks": [
-                10,
-                10,
-                10
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "|u1",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                10,
-                36,
-                72
-            ],
-            "zarr_format": 2
-        },
-        "CDD0/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "time",
-                "lat",
-                "lon"
-            ]
-        },
-        "DISPH/.zarray": {
-            "chunks": [
-                10,
-                10,
-                10
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "|u1",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                10,
-                36,
-                72
-            ],
-            "zarr_format": 2
-        },
-        "DISPH/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "time",
-                "lat",
-                "lon"
-            ]
-        },
-        "FROST_DAYS/.zarray": {
-            "chunks": [
-                10,
-                10,
-                10
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "|u1",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                10,
-                36,
-                72
-            ],
-            "zarr_format": 2
-        },
-        "FROST_DAYS/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "time",
-                "lat",
-                "lon"
-            ]
-        },
-        "GWETPROF/.zarray": {
-            "chunks": [
-                10,
-                10,
-                10
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "|u1",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                10,
-                36,
-                72
-            ],
-            "zarr_format": 2
-        },
-        "GWETPROF/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "time",
-                "lat",
-                "lon"
-            ]
-        },
-        "lat/.zarray": {
-            "chunks": [
-                36
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "<f8",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                36
-            ],
-            "zarr_format": 2
-        },
-        "lat/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "lat"
-            ]
-        },
-        "lon/.zarray": {
-            "chunks": [
-                72
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "<f8",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                72
-            ],
-            "zarr_format": 2
-        },
-        "lon/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "lon"
-            ]
-        },
-        "time/.zarray": {
-            "chunks": [
-                10
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "lz4",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dtype": "<i8",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                10
-            ],
-            "zarr_format": 2
-        },
-        "time/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "time"
-            ]
-        }
-    },
-    "zarr_consolidated_format": 1
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/CDD0/.zarray b/tests/fixtures/test_zarr_store.zarr/CDD0/.zarray
deleted file mode 100644
index 1785efbc..00000000
--- a/tests/fixtures/test_zarr_store.zarr/CDD0/.zarray
+++ /dev/null
@@ -1,24 +0,0 @@
-{
-    "chunks": [
-        10,
-        10,
-        10
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "|u1",
-    "fill_value": null,
-    "filters": null,
-    "order": "C",
-    "shape": [
-        10,
-        36,
-        72
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/CDD0/.zattrs b/tests/fixtures/test_zarr_store.zarr/CDD0/.zattrs
deleted file mode 100644
index 76231419..00000000
--- a/tests/fixtures/test_zarr_store.zarr/CDD0/.zattrs
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "time",
-        "lat",
-        "lon"
-    ]
-}
\ No newline at end of file
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diff --git a/tests/fixtures/test_zarr_store.zarr/DISPH/.zarray b/tests/fixtures/test_zarr_store.zarr/DISPH/.zarray
deleted file mode 100644
index 1785efbc..00000000
--- a/tests/fixtures/test_zarr_store.zarr/DISPH/.zarray
+++ /dev/null
@@ -1,24 +0,0 @@
-{
-    "chunks": [
-        10,
-        10,
-        10
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "|u1",
-    "fill_value": null,
-    "filters": null,
-    "order": "C",
-    "shape": [
-        10,
-        36,
-        72
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/DISPH/.zattrs b/tests/fixtures/test_zarr_store.zarr/DISPH/.zattrs
deleted file mode 100644
index 76231419..00000000
--- a/tests/fixtures/test_zarr_store.zarr/DISPH/.zattrs
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "time",
-        "lat",
-        "lon"
-    ]
-}
\ No newline at end of file
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diff --git a/tests/fixtures/test_zarr_store.zarr/FROST_DAYS/.zarray b/tests/fixtures/test_zarr_store.zarr/FROST_DAYS/.zarray
deleted file mode 100644
index 1785efbc..00000000
--- a/tests/fixtures/test_zarr_store.zarr/FROST_DAYS/.zarray
+++ /dev/null
@@ -1,24 +0,0 @@
-{
-    "chunks": [
-        10,
-        10,
-        10
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "|u1",
-    "fill_value": null,
-    "filters": null,
-    "order": "C",
-    "shape": [
-        10,
-        36,
-        72
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/FROST_DAYS/.zattrs b/tests/fixtures/test_zarr_store.zarr/FROST_DAYS/.zattrs
deleted file mode 100644
index 76231419..00000000
--- a/tests/fixtures/test_zarr_store.zarr/FROST_DAYS/.zattrs
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "time",
-        "lat",
-        "lon"
-    ]
-}
\ No newline at end of file
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--- a/tests/fixtures/test_zarr_store.zarr/GWETPROF/.zarray
+++ /dev/null
@@ -1,24 +0,0 @@
-{
-    "chunks": [
-        10,
-        10,
-        10
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "|u1",
-    "fill_value": null,
-    "filters": null,
-    "order": "C",
-    "shape": [
-        10,
-        36,
-        72
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/GWETPROF/.zattrs b/tests/fixtures/test_zarr_store.zarr/GWETPROF/.zattrs
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+++ /dev/null
@@ -1,7 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "time",
-        "lat",
-        "lon"
-    ]
-}
\ No newline at end of file
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diff --git a/tests/fixtures/test_zarr_store.zarr/lat/.zarray b/tests/fixtures/test_zarr_store.zarr/lat/.zarray
deleted file mode 100644
index 4502ec9c..00000000
--- a/tests/fixtures/test_zarr_store.zarr/lat/.zarray
+++ /dev/null
@@ -1,20 +0,0 @@
-{
-    "chunks": [
-        36
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "<f8",
-    "fill_value": "NaN",
-    "filters": null,
-    "order": "C",
-    "shape": [
-        36
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/lat/.zattrs b/tests/fixtures/test_zarr_store.zarr/lat/.zattrs
deleted file mode 100644
index cd3ac946..00000000
--- a/tests/fixtures/test_zarr_store.zarr/lat/.zattrs
+++ /dev/null
@@ -1,5 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "lat"
-    ]
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/lon/.zarray b/tests/fixtures/test_zarr_store.zarr/lon/.zarray
deleted file mode 100644
index dfc59d6c..00000000
--- a/tests/fixtures/test_zarr_store.zarr/lon/.zarray
+++ /dev/null
@@ -1,20 +0,0 @@
-{
-    "chunks": [
-        72
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "<f8",
-    "fill_value": "NaN",
-    "filters": null,
-    "order": "C",
-    "shape": [
-        72
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/lon/.zattrs b/tests/fixtures/test_zarr_store.zarr/lon/.zattrs
deleted file mode 100644
index 6e3c5fe8..00000000
--- a/tests/fixtures/test_zarr_store.zarr/lon/.zattrs
+++ /dev/null
@@ -1,5 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "lon"
-    ]
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/time/.zarray b/tests/fixtures/test_zarr_store.zarr/time/.zarray
deleted file mode 100644
index f24b0552..00000000
--- a/tests/fixtures/test_zarr_store.zarr/time/.zarray
+++ /dev/null
@@ -1,20 +0,0 @@
-{
-    "chunks": [
-        10
-    ],
-    "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "lz4",
-        "id": "blosc",
-        "shuffle": 1
-    },
-    "dtype": "<i8",
-    "fill_value": null,
-    "filters": null,
-    "order": "C",
-    "shape": [
-        10
-    ],
-    "zarr_format": 2
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/time/.zattrs b/tests/fixtures/test_zarr_store.zarr/time/.zattrs
deleted file mode 100644
index 5a25782b..00000000
--- a/tests/fixtures/test_zarr_store.zarr/time/.zattrs
+++ /dev/null
@@ -1,5 +0,0 @@
-{
-    "_ARRAY_DIMENSIONS": [
-        "time"
-    ]
-}
\ No newline at end of file
diff --git a/tests/fixtures/test_zarr_store.zarr/.zattrs b/tests/fixtures/zarr_store_v2.zarr/.zattrs
similarity index 100%
rename from tests/fixtures/test_zarr_store.zarr/.zattrs
rename to tests/fixtures/zarr_store_v2.zarr/.zattrs
diff --git a/tests/fixtures/zarr_store_v2.zarr/.zgroup b/tests/fixtures/zarr_store_v2.zarr/.zgroup
new file mode 100644
index 00000000..cab13da6
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/.zgroup
@@ -0,0 +1,3 @@
+{
+  "zarr_format": 2
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v2.zarr/.zmetadata b/tests/fixtures/zarr_store_v2.zarr/.zmetadata
new file mode 100644
index 00000000..c421c778
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/.zmetadata
@@ -0,0 +1 @@
+{"metadata": {".zgroup": {"zarr_format": 2}, ".zattrs": {}, "CDD0/.zattrs": {"_ARRAY_DIMENSIONS": ["time", "lat", "lon"]}, "CDD0/.zarray": {"shape": [10, 36, 72], "chunks": [10, 10, 10], "dtype": "<f8", "fill_value": "NaN", "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}, "DISPH/.zattrs": {"_ARRAY_DIMENSIONS": ["time", "lat", "lon"]}, "DISPH/.zarray": {"shape": [10, 36, 72], "chunks": [10, 10, 10], "dtype": "<f8", "fill_value": "NaN", "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}, "FROST_DAYS/.zattrs": {"_ARRAY_DIMENSIONS": ["time", "lat", "lon"]}, "FROST_DAYS/.zarray": {"shape": [10, 36, 72], "chunks": [10, 10, 10], "dtype": "<f8", "fill_value": "NaN", "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}, "GWETPROF/.zattrs": {"_ARRAY_DIMENSIONS": ["time", "lat", "lon"]}, "GWETPROF/.zarray": {"shape": [10, 36, 72], "chunks": [10, 10, 10], "dtype": "<f8", "fill_value": "NaN", "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}, "lat/.zattrs": {"_ARRAY_DIMENSIONS": ["lat"]}, "lat/.zarray": {"shape": [36], "chunks": [36], "dtype": "<f8", "fill_value": "NaN", "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}, "lon/.zattrs": {"_ARRAY_DIMENSIONS": ["lon"]}, "lon/.zarray": {"shape": [72], "chunks": [72], "dtype": "<f8", "fill_value": "NaN", "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}, "time/.zattrs": {"_ARRAY_DIMENSIONS": ["time"]}, "time/.zarray": {"shape": [10], "chunks": [10], "dtype": "<i8", "fill_value": null, "order": "C", "filters": null, "dimension_separator": ".", "compressor": {"id": "blosc", "cname": "lz4", "clevel": 5, "shuffle": 1, "blocksize": 0}, "zarr_format": 2}}, "zarr_consolidated_format": 1}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v2.zarr/CDD0/.zarray b/tests/fixtures/zarr_store_v2.zarr/CDD0/.zarray
new file mode 100644
index 00000000..b4b61048
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/CDD0/.zarray
@@ -0,0 +1,25 @@
+{
+  "shape": [
+    10,
+    36,
+    72
+  ],
+  "chunks": [
+    10,
+    10,
+    10
+  ],
+  "dtype": "<f8",
+  "fill_value": "NaN",
+  "order": "C",
+  "filters": null,
+  "dimension_separator": ".",
+  "compressor": {
+    "id": "blosc",
+    "cname": "lz4",
+    "clevel": 5,
+    "shuffle": 1,
+    "blocksize": 0
+  },
+  "zarr_format": 2
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v2.zarr/CDD0/.zattrs b/tests/fixtures/zarr_store_v2.zarr/CDD0/.zattrs
new file mode 100644
index 00000000..05bb7217
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/CDD0/.zattrs
@@ -0,0 +1,7 @@
+{
+  "_ARRAY_DIMENSIONS": [
+    "time",
+    "lat",
+    "lon"
+  ]
+}
\ No newline at end of file
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diff --git a/tests/fixtures/zarr_store_v2.zarr/DISPH/.zarray b/tests/fixtures/zarr_store_v2.zarr/DISPH/.zarray
new file mode 100644
index 00000000..b4b61048
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/DISPH/.zarray
@@ -0,0 +1,25 @@
+{
+  "shape": [
+    10,
+    36,
+    72
+  ],
+  "chunks": [
+    10,
+    10,
+    10
+  ],
+  "dtype": "<f8",
+  "fill_value": "NaN",
+  "order": "C",
+  "filters": null,
+  "dimension_separator": ".",
+  "compressor": {
+    "id": "blosc",
+    "cname": "lz4",
+    "clevel": 5,
+    "shuffle": 1,
+    "blocksize": 0
+  },
+  "zarr_format": 2
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v2.zarr/DISPH/.zattrs b/tests/fixtures/zarr_store_v2.zarr/DISPH/.zattrs
new file mode 100644
index 00000000..05bb7217
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/DISPH/.zattrs
@@ -0,0 +1,7 @@
+{
+  "_ARRAY_DIMENSIONS": [
+    "time",
+    "lat",
+    "lon"
+  ]
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v2.zarr/DISPH/0.0.0 b/tests/fixtures/zarr_store_v2.zarr/DISPH/0.0.0
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index 00000000..b4b61048
--- /dev/null
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index 00000000..05bb7217
--- /dev/null
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index 00000000..b4b61048
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/GWETPROF/.zarray
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new file mode 100644
index 00000000..05bb7217
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/GWETPROF/.zattrs
@@ -0,0 +1,7 @@
+{
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+}
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new file mode 100644
index 00000000..075be27a
--- /dev/null
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+  "chunks": [
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+  "dtype": "<f8",
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+  "order": "C",
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new file mode 100644
index 00000000..b61fcccb
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/lat/.zattrs
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similarity index 100%
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new file mode 100644
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--- /dev/null
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+  "chunks": [
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+  "dtype": "<f8",
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--- /dev/null
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similarity index 100%
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index 00000000..a5c6d0c0
--- /dev/null
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+  "chunks": [
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+  "dtype": "<i8",
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+  "order": "C",
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+  "zarr_format": 2
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index 00000000..0713e5ba
--- /dev/null
+++ b/tests/fixtures/zarr_store_v2.zarr/time/.zattrs
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+{
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+    "time"
+  ]
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rename to tests/fixtures/zarr_store_v2.zarr/time/0
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--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/CDD0/zarr.json
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+{
+  "shape": [
+    10,
+    36,
+    72
+  ],
+  "data_type": "float64",
+  "chunk_grid": {
+    "name": "regular",
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+      "chunk_shape": [
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+        10,
+        10
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {
+    "_FillValue": "AAAAAAAA+H8="
+  },
+  "dimension_names": [
+    "time",
+    "lat",
+    "lon"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
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new file mode 100644
index 00000000..a61ec317
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/DISPH/zarr.json
@@ -0,0 +1,51 @@
+{
+  "shape": [
+    10,
+    36,
+    72
+  ],
+  "data_type": "float64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        10,
+        10,
+        10
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {
+    "_FillValue": "AAAAAAAA+H8="
+  },
+  "dimension_names": [
+    "time",
+    "lat",
+    "lon"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
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diff --git a/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/1 b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/1
new file mode 100644
index 00000000..a9edcc78
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diff --git a/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/2 b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/2
new file mode 100644
index 00000000..0eab499f
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diff --git a/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/3 b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/3
new file mode 100644
index 00000000..7f52dce6
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index 00000000..46fae31c
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new file mode 100644
index 00000000..ae4bf98a
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diff --git a/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/6 b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/6
new file mode 100644
index 00000000..e8eab0b0
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diff --git a/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/7 b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/c/0/3/7
new file mode 100644
index 00000000..3c25aed6
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diff --git a/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/zarr.json b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/zarr.json
new file mode 100644
index 00000000..a61ec317
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/FROST_DAYS/zarr.json
@@ -0,0 +1,51 @@
+{
+  "shape": [
+    10,
+    36,
+    72
+  ],
+  "data_type": "float64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        10,
+        10,
+        10
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {
+    "_FillValue": "AAAAAAAA+H8="
+  },
+  "dimension_names": [
+    "time",
+    "lat",
+    "lon"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/0/0 b/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/0/0
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index 00000000..afab1145
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index 00000000..aed20924
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index 00000000..87559736
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new file mode 100644
index 00000000..6d741610
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diff --git a/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/3/6 b/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/3/6
new file mode 100644
index 00000000..e45d5877
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diff --git a/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/3/7 b/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/3/7
new file mode 100644
index 00000000..92b514da
Binary files /dev/null and b/tests/fixtures/zarr_store_v3.zarr/GWETPROF/c/0/3/7 differ
diff --git a/tests/fixtures/zarr_store_v3.zarr/GWETPROF/zarr.json b/tests/fixtures/zarr_store_v3.zarr/GWETPROF/zarr.json
new file mode 100644
index 00000000..a61ec317
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/GWETPROF/zarr.json
@@ -0,0 +1,51 @@
+{
+  "shape": [
+    10,
+    36,
+    72
+  ],
+  "data_type": "float64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        10,
+        10,
+        10
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {
+    "_FillValue": "AAAAAAAA+H8="
+  },
+  "dimension_names": [
+    "time",
+    "lat",
+    "lon"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v3.zarr/lat/c/0 b/tests/fixtures/zarr_store_v3.zarr/lat/c/0
new file mode 100644
index 00000000..b562295d
Binary files /dev/null and b/tests/fixtures/zarr_store_v3.zarr/lat/c/0 differ
diff --git a/tests/fixtures/zarr_store_v3.zarr/lat/zarr.json b/tests/fixtures/zarr_store_v3.zarr/lat/zarr.json
new file mode 100644
index 00000000..05816a2b
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/lat/zarr.json
@@ -0,0 +1,45 @@
+{
+  "shape": [
+    36
+  ],
+  "data_type": "float64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        36
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {
+    "_FillValue": "AAAAAAAA+H8="
+  },
+  "dimension_names": [
+    "lat"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v3.zarr/lon/c/0 b/tests/fixtures/zarr_store_v3.zarr/lon/c/0
new file mode 100644
index 00000000..48a5653c
Binary files /dev/null and b/tests/fixtures/zarr_store_v3.zarr/lon/c/0 differ
diff --git a/tests/fixtures/zarr_store_v3.zarr/lon/zarr.json b/tests/fixtures/zarr_store_v3.zarr/lon/zarr.json
new file mode 100644
index 00000000..5f318d69
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/lon/zarr.json
@@ -0,0 +1,45 @@
+{
+  "shape": [
+    72
+  ],
+  "data_type": "float64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        72
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {
+    "_FillValue": "AAAAAAAA+H8="
+  },
+  "dimension_names": [
+    "lon"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v3.zarr/time/c/0 b/tests/fixtures/zarr_store_v3.zarr/time/c/0
new file mode 100644
index 00000000..0c32aa6b
Binary files /dev/null and b/tests/fixtures/zarr_store_v3.zarr/time/c/0 differ
diff --git a/tests/fixtures/zarr_store_v3.zarr/time/zarr.json b/tests/fixtures/zarr_store_v3.zarr/time/zarr.json
new file mode 100644
index 00000000..f37873d8
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/time/zarr.json
@@ -0,0 +1,43 @@
+{
+  "shape": [
+    10
+  ],
+  "data_type": "int64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        10
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {},
+  "dimension_names": [
+    "time"
+  ],
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
\ No newline at end of file
diff --git a/tests/fixtures/zarr_store_v3.zarr/zarr.json b/tests/fixtures/zarr_store_v3.zarr/zarr.json
new file mode 100644
index 00000000..ce5438a4
--- /dev/null
+++ b/tests/fixtures/zarr_store_v3.zarr/zarr.json
@@ -0,0 +1,6 @@
+{
+  "attributes": {},
+  "zarr_format": 3,
+  "consolidated_metadata": null,
+  "node_type": "group"
+}
\ No newline at end of file
diff --git a/tests/test_app.py b/tests/test_app.py
index 49fbf48f..d00ffbe7 100644
--- a/tests/test_app.py
+++ b/tests/test_app.py
@@ -4,17 +4,41 @@
 
 from helpers import find_string_in_stream
 
+
 DATA_DIR = "tests/fixtures"
-test_zarr_store = os.path.join(DATA_DIR, "test_zarr_store.zarr")
+test_zarr_store_v2 = os.path.join(DATA_DIR, "zarr_store_v2.zarr")
+test_zarr_store_v3 = os.path.join(DATA_DIR, "zarr_store_v3.zarr")
 test_netcdf_store = os.path.join(DATA_DIR, "testfile.nc")
 test_unconsolidated_store = os.path.join(DATA_DIR, "unconsolidated.zarr")
 test_pyramid_store = os.path.join(DATA_DIR, "pyramid.zarr")
+test_icechunk_native = os.path.join(DATA_DIR, "icechunk_native")
+test_icechunk_virtual_accessible = os.path.join(DATA_DIR, "icechunk_virtual_accessible")
 
 store_params = {}
 
-store_params["zarr_store"] = {
+store_params["zarr_store_v2"] = {
+    "params": {
+        "url": test_zarr_store_v2,
+        "variable": "CDD0",
+        "decode_times": False,
+        "sel": "time=0",
+    },
+    "variables": ["CDD0", "DISPH", "FROST_DAYS", "GWETPROF"],
+}
+
+store_params["zarr_store_v3"] = {
+    "params": {
+        "url": test_zarr_store_v3,
+        "variable": "CDD0",
+        "decode_times": False,
+        "sel": "time=0",
+    },
+    "variables": ["CDD0", "DISPH", "FROST_DAYS", "GWETPROF"],
+}
+
+store_params["icechunk_native"] = {
     "params": {
-        "url": test_zarr_store,
+        "url": test_icechunk_native,
         "variable": "CDD0",
         "decode_times": False,
         "sel": "time=0",
@@ -22,6 +46,27 @@
     "variables": ["CDD0", "DISPH", "FROST_DAYS", "GWETPROF"],
 }
 
+store_params["icechunk_virtual_accessible"] = {
+    "params": {
+        "url": test_icechunk_virtual_accessible,
+        "variable": "LWdown",
+        "decode_times": False,
+        "sel": "time=1.0",
+    },
+    "variables": [
+        "LWdown",
+        "Wind_N",
+        "Tair",
+        "Rainf",
+        "Wind_E",
+        "Qair",
+        "Tair_max",
+        "Tair_min",
+        "SWdown",
+        "PSurf",
+    ],
+}
+
 store_params["netcdf_store"] = {
     "params": {
         "url": test_netcdf_store,
@@ -54,8 +99,10 @@
 
 def get_variables_test(app, ds_params):
     response = app.get("/variables", params=ds_params["params"])
+    print(response)
     assert response.status_code == 200
-    assert response.json() == ds_params["variables"]
+    # TODO: Do we care about the order?
+    assert set(response.json()) == set(ds_params["variables"])
     assert response.headers["server-timing"]
     timings = response.headers["server-timing"].split(",")
     assert len(timings) == 2
@@ -149,10 +196,13 @@ def test_histogram(store_params, app):
     return histogram_test(app, store_params)
 
 
-def test_histogram_error(app):
+# TODO: Maybe this is overkill to parametrize?
+@pytest.mark.parametrize("store_params", store_params.values(), ids=store_params.keys())
+def test_histogram_error(store_params, app):
+    store_path = store_params["params"]["url"]
     response = app.get(
         "/histogram",
-        params={"url": test_zarr_store},
+        params={"url": store_path},
     )
     assert response.status_code == 422
     assert response.json() == {
@@ -174,9 +224,12 @@ def test_map_without_params(app):
     assert find_string_in_stream(response, "Step 1: Enter the URL of your Zarr store")
 
 
-def test_map_with_params(app):
+@pytest.mark.parametrize("store_params", store_params.values(), ids=store_params.keys())
+def test_map_with_params(store_params, app):
+    store_path = store_params["params"]["url"]
+    variable = store_params["variables"][0]
     response = app.get(
-        "/WebMercatorQuad/map", params={"url": test_zarr_store, "variable": "CDD0"}
+        "/WebMercatorQuad/map", params={"url": store_path, "variable": variable}
     )
     assert response.status_code == 200
     assert response.headers["Content-Type"] == "text/html; charset=utf-8"
diff --git a/uv.lock b/uv.lock
index 79e5b3d8..255ef910 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2,8 +2,8 @@ version = 1
 revision = 2
 requires-python = ">=3.12"
 resolution-markers = [
-    "python_full_version >= '3.13'",
-    "python_full_version < '3.13'",
+    "python_full_version >= '3.14'",
+    "python_full_version < '3.14'",
 ]
 
 [[package]]
@@ -35,16 +35,16 @@ wheels = [
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.4"
+version = "2.6.1"
 source = { registry = "https://pypi.org/simple" }
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.11.11"
+version = "3.13.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -55,38 +55,76 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
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+    { name = "icechunk" },
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@@ -1886,18 +3037,29 @@ deployment = [
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@@ -1909,6 +3071,7 @@ requires-dist = [
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