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794cc5d
Create nasa_power.py
IoannisSifnaios Jul 15, 2025
ff8d010
Updated API
IoannisSifnaios Jul 15, 2025
9a99395
Update __init__.py
IoannisSifnaios Jul 15, 2025
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fixed minor typos
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update metadata
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Add tests
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fix lint
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2nd try
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update whatsnew
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suggestions from code review vol.2
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Merge branch 'main' into add_nasa_power
IoannisSifnaios Jul 30, 2025
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11 changes: 11 additions & 0 deletions docs/sphinx/source/reference/iotools.rst
Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,17 @@ clear-sky irradiance globally.
iotools.parse_cams


NASA POWER
**********

Satellite-derived irradiance and weather data with global coverage.

.. autosummary::
:toctree: generated/

iotools.get_nasa_power


NSRDB
*****

Expand Down
6 changes: 4 additions & 2 deletions docs/sphinx/source/whatsnew/v0.13.1.rst
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,8 @@ Bug fixes

Enhancements
~~~~~~~~~~~~

* Add :py:func:`pvlib.iotools.get_nasa_power` to retrieve data from NASA POWER free API.
(:pull:`2500`)

Documentation
~~~~~~~~~~~~~
Expand Down Expand Up @@ -47,5 +48,6 @@ Maintenance
Contributors
~~~~~~~~~~~~
* Elijah Passmore (:ghuser:`eljpsm`)
* Ioannis Sifnaios (:ghuser:`IoannisSifnaios`)
* Rajiv Daxini (:ghuser:`RDaxini`)
* Omar Bahamida (:ghuser:`OmarBahamida`)
* Omar Bahamida (:ghuser:`OmarBahamida`)
1 change: 1 addition & 0 deletions pvlib/iotools/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -39,3 +39,4 @@
from pvlib.iotools.solcast import get_solcast_historic # noqa: F401
from pvlib.iotools.solcast import get_solcast_tmy # noqa: F401
from pvlib.iotools.solargis import get_solargis # noqa: F401
from pvlib.iotools.nasa_power import get_nasa_power # noqa: F401
153 changes: 153 additions & 0 deletions pvlib/iotools/nasa_power.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,153 @@
"""Functions for reading and retrieving data from NASA POWER."""

import pandas as pd
import requests
import numpy as np

URL = 'https://power.larc.nasa.gov/api/temporal/hourly/point'

DEFAULT_PARAMETERS = [
'dni', 'dhi', 'ghi', 'temp_air', 'wind_speed'
]

VARIABLE_MAP = {
'ALLSKY_SFC_SW_DWN': 'ghi',
'ALLSKY_SFC_SW_DIFF': 'dhi',
'ALLSKY_SFC_SW_DNI': 'dni',
'CLRSKY_SFC_SW_DWN': 'ghi_clear',
'T2M': 'temp_air',
'WS2M': 'wind_speed_2m',
'WS10M': 'wind_speed',
}


def get_nasa_power(latitude, longitude, start, end,
parameters=DEFAULT_PARAMETERS, *, community='re',
elevation=None, wind_height=None, wind_surface=None,
map_variables=True, url=URL):
"""
Retrieve irradiance and weather data from NASA POWER.

A general description of NASA POWER is given in [1]_ and the API is
described in [2]_. A detailed list of the available parameters can be
found in [3]_.

Parameters
----------
latitude: float
In decimal degrees, north is positive (ISO 19115).
longitude: float
In decimal degrees, east is positive (ISO 19115).
start: datetime like
First timestamp of the requested period.
end: datetime like
Last timestamp of the requested period.
parameters: str, list
List of parameters. The default parameters are mentioned below; for the
full list see [3]_. Note that the pvlib naming conventions can also be
used.

* Global Horizontal Irradiance (GHI) [Wm⁻²]
* Diffuse Horizontal Irradiance (DHI) [Wm⁻²]
* Direct Normal Irradiance (DNI) [Wm⁻²]
* Air temperature at 2 m [C]
* Wind speed at 10 m [m/s]

community: str, default 're'
Can be one of the following depending on which parameters are of
interest. Note that in many cases this choice
might affect the units of the parameter.

* ``'re'``: renewable energy
* ``'sb'``: sustainable buildings
* ``'ag'``: agroclimatology

elevation: float, optional
The custom site elevation in meters to produce the corrected
atmospheric pressure adjusted for elevation.
wind_height: float, optional
The custom wind height in meters to produce the wind speed adjusted
for height. Has to be between 10 and 300 m; see [4]_.
wind_surface: str, optional
The definable surface type to adjust the wind speed. For a list of the
surface types see [4]_. If you provide a wind surface alias please
include a site elevation with the request.
map_variables: bool, default True
When true, renames columns of the Dataframe to pvlib variable names
where applicable. See variable :const:`VARIABLE_MAP`.

Raises
------
requests.HTTPError
Raises an error when an incorrect request is made.

Returns
-------
data : pd.DataFrame
Time series data. The index corresponds to the start (left) of the
interval.
meta : dict
Metadata.

References
----------
.. [1] `NASA Prediction Of Worldwide Energy Resources (POWER)
<https://power.larc.nasa.gov/>`_
.. [2] `NASA POWER API
<https://power.larc.nasa.gov/api/pages/>`_
.. [3] `NASA POWER API parameters
<https://power.larc.nasa.gov/parameters/>`_
.. [4] `NASA POWER corrected wind speed parameters
<https://power.larc.nasa.gov/docs/methodology/meteorology/wind/>`_
"""
start = pd.Timestamp(start)
end = pd.Timestamp(end)

# allow the use of pvlib parameter names
parameter_dict = {v: k for k, v in VARIABLE_MAP.items()}
parameters = [parameter_dict.get(p, p) for p in parameters]

params = {
'latitude': latitude,
'longitude': longitude,
'start': start.strftime('%Y%m%d'),
'end': end.strftime('%Y%m%d'),
'community': community,
'parameters': ','.join(parameters), # make parameters in a string
'format': 'json',
'user': None,
'header': True,
'time-standard': 'utc',
'site-elevation': elevation,
'wind-elevation': wind_height,
'wind-surface': wind_surface,
}

response = requests.get(url, params=params)
if not response.ok:
# response.raise_for_status() does not give a useful error message
raise requests.HTTPError(response.json())

# Parse the data to dataframe
data = response.json()
hourly_data = data['properties']['parameter']
df = pd.DataFrame(hourly_data)
df.index = pd.to_datetime(df.index, format='%Y%m%d%H').tz_localize('UTC')

# Create metadata dictionary
meta = data['header']
meta['times'] = data['times']
meta['parameters'] = data['parameters']

meta['longitude'] = data['geometry']['coordinates'][0]
meta['latitude'] = data['geometry']['coordinates'][1]
meta['altitude'] = data['geometry']['coordinates'][2]

# Replace NaN values
df = df.replace(meta['fill_value'], np.nan)

# Rename according to pvlib convention
if map_variables:
df = df.rename(columns=VARIABLE_MAP)

return df, meta
100 changes: 100 additions & 0 deletions tests/iotools/test_nasa_power.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,100 @@
import pandas as pd
import pytest
import pvlib
from requests.exceptions import HTTPError
from tests.conftest import RERUNS, RERUNS_DELAY


@pytest.fixture
def data_index():
index = pd.date_range(start='2025-02-02 00:00+00:00',
end='2025-02-02 23:00+00:00', freq='1h')
return index


@pytest.fixture
def ghi_series(data_index):
ghi = [
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.25, 184.2, 281.55, 368.3, 406.48,
386.45, 316.05, 210.1, 109.05, 12.9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
]
return pd.Series(data=ghi, index=data_index, name='ghi')


@pytest.mark.remote_data
@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
def test_get_nasa_power(data_index, ghi_series):
data, meta = pvlib.iotools.get_nasa_power(latitude=44.76,
longitude=7.64,
start=data_index[0],
end=data_index[-1],
parameters=['ALLSKY_SFC_SW_DWN'],
map_variables=False)
# Check that metadata is correct
assert meta['latitude'] == 44.76
assert meta['longitude'] == 7.64
assert meta['altitude'] == 705.88
assert meta['start'] == '20250202'
assert meta['end'] == '20250202'
assert meta['time_standard'] == 'UTC'
assert meta['title'] == 'NASA/POWER Source Native Resolution Hourly Data'
# Assert that the index is parsed correctly
pd.testing.assert_index_equal(data.index, data_index)
# Test one column
pd.testing.assert_series_equal(data['ALLSKY_SFC_SW_DWN'], ghi_series,
check_freq=False, check_names=False)


@pytest.mark.remote_data
@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
def test_get_nasa_power_pvlib_params_naming(data_index, ghi_series):
data, meta = pvlib.iotools.get_nasa_power(latitude=44.76,
longitude=7.64,
start=data_index[0],
end=data_index[-1],
parameters=['ghi'])
# Assert that the index is parsed correctly
pd.testing.assert_index_equal(data.index, data_index)
# Test one column
pd.testing.assert_series_equal(data['ghi'], ghi_series,
check_freq=False)


@pytest.mark.remote_data
@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
def test_get_nasa_power_map_variables(data_index):
# Check that variables are mapped by default to pvlib names
data, meta = pvlib.iotools.get_nasa_power(latitude=44.76,
longitude=7.64,
start=data_index[0],
end=data_index[-1])
mapped_column_names = ['ghi', 'dni', 'dhi', 'temp_air', 'wind_speed']
for c in mapped_column_names:
assert c in data.columns
assert meta['latitude'] == 44.76
assert meta['longitude'] == 7.64
assert meta['altitude'] == 705.88


@pytest.mark.remote_data
@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
def test_get_nasa_power_wrong_parameter_name(data_index):
# Test if HTTPError is raised if a wrong parameter name is asked
with pytest.raises(HTTPError, match=r"ALLSKY_SFC_SW_DLN"):
pvlib.iotools.get_nasa_power(latitude=44.76,
longitude=7.64,
start=data_index[0],
end=data_index[-1],
parameters=['ALLSKY_SFC_SW_DLN'])


@pytest.mark.remote_data
@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
def test_get_nasa_power_duplicate_parameter_name(data_index):
# Test if HTTPError is raised if a duplicate parameter is asked
with pytest.raises(HTTPError, match=r"ALLSKY_SFC_SW_DWN"):
pvlib.iotools.get_nasa_power(latitude=44.76,
longitude=7.64,
start=data_index[0],
end=data_index[-1],
parameters=2*['ALLSKY_SFC_SW_DWN'])
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