Add NASA POWER to iotools

docs/sphinx/source/reference/iotools.rst

@@ -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
 *****
 

docs/sphinx/source/whatsnew/v0.13.1.rst

@@ -19,7 +19,8 @@ Bug fixes
 
 Enhancements
 ~~~~~~~~~~~~
-
+* Added function :py:func:`~pvlib.iotools.get_nasa_power` to retrieve data from NASA POWER.
+  (:pull:`2500`)
 
 Documentation
 ~~~~~~~~~~~~~
@@ -45,3 +46,5 @@ Maintenance
 Contributors
 ~~~~~~~~~~~~
 * Elijah Passmore (:ghuser:`eljpsm`)
+* Ioannis Sifnaios (:ghuser:`IoannisSifnaios`)
+

pvlib/iotools/__init__.py

@@ -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

pvlib/iotools/nasa_power.py

@@ -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', url=URL,
+                   elevation=None, wind_height=None, wind_surface=None,
+                   map_variables=True):
+    """
+    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

tests/iotools/test_nasa_power.py

@@ -0,0 +1,92 @@
+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)
+
+
+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)
+
+
+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
+
+
+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'])
+
+
+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'])