Update nasa_power VARIABLE_MAP with additional parameters

docs/sphinx/source/whatsnew/v0.15.2.rst

@@ -28,6 +28,10 @@ Enhancements
 * Added mapping of the parameter ``"albedo"`` in
   :py:func:`~pvlib.iotools.get_nasa_power` when ``map_variables=True``
   (:pull:`2753`)
+* Add the following parameters to :py:func:`~pvlib.iotools.get_nasa_power`
+  when ``map_variables=True``: ``temp_dew``, ``precipitable_water``,
+  ``relative_humidity``, ``ghi_extra``, ``dhi_clear``, and ``longwave_down``
+  (:pull:`2762`)
 
 
 Documentation
@@ -62,3 +66,4 @@ Contributors
 * Cliff Hansen (:ghuser:`cwhanse`)
 * Arthur Onno (:ghuser:`ArthurOnnoTerabase`)
 * Adam R. Jensen (:ghuser:`AdamRJensen`)
+* Karl Hill (:ghuser:`karlhillx`)

pvlib/iotools/nasa_power.py

@@ -14,11 +14,19 @@
     'ALLSKY_SFC_SW_DWN': 'ghi',
     'ALLSKY_SFC_SW_DIFF': 'dhi',
     'ALLSKY_SFC_SW_DNI': 'dni',
+    'ALLSKY_SRF_ALB': 'albedo',
+    'ALLSKY_SFC_LW_DWN': 'longwave_down',
+    'CLRSKY_SFC_SW_DIFF': 'dhi_clear',
+    'CLRSKY_SFC_SW_DNI': 'dni_clear',
     'CLRSKY_SFC_SW_DWN': 'ghi_clear',
+    'PS': 'pressure',
+    'RH2M': 'relative_humidity',
     'T2M': 'temp_air',
+    'T2MDEW': 'temp_dew',
+    'TQV': 'precipitable_water',
+    'TOA_SW_DWN': 'ghi_extra',
     'WS2M': 'wind_speed_2m',
     'WS10M': 'wind_speed',
-    'ALLSKY_SRF_ALB': 'albedo',
 }
 
 
@@ -82,6 +90,12 @@ def get_nasa_power(latitude, longitude, start, end,
     requests.HTTPError
         Raises an error when an incorrect request is made.
 
+    Notes
+    -----
+    When ``map_variables=True`` the following unit conversions are applied:
+    pressure is converted from kPa to Pa, and precipitable water
+    is converted from kg/m² (mm) to cm.
+
     Returns
     -------
     data : pd.DataFrame
@@ -150,5 +164,11 @@ def get_nasa_power(latitude, longitude, start, end,
     # Rename according to pvlib convention
     if map_variables:
         df = df.rename(columns=VARIABLE_MAP)
+        # PS is returned in kPa; convert to Pa for pvlib compatibility.
+        if 'pressure' in df.columns:
+            df['pressure'] = df['pressure'] * 1000
+        # TQV is returned in kg/m^2 (=mm); convert to cm for compatibility
+        if 'precipitable_water' in df.columns:
+            df['precipitable_water'] = df['precipitable_water'] / 10
 
     return df, meta

tests/iotools/test_nasa_power.py

@@ -98,3 +98,110 @@ def test_get_nasa_power_duplicate_parameter_name(data_index):
                                      start=data_index[0],
                                      end=data_index[-1],
                                      parameters=2*['ALLSKY_SFC_SW_DWN'])
+
+
+@pytest.mark.remote_data
+@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
+def test_get_nasa_power_all_variable_map_parameters_valid():
+    """
+    Every NASA POWER parameter name in VARIABLE_MAP must be accepted by the
+    live API. A typo or stale name (e.g. CLRSKY_DIFF vs CLRSKY_SFC_SW_DIFF)
+    causes the API to return an HTTPError, which would fail this test.
+
+    NASA POWER allows max 15 parameters per request; VARIABLE_MAP is split
+    into two batches to stay within that limit.
+    """
+    from pvlib.iotools.nasa_power import VARIABLE_MAP
+    nasa_params = list(VARIABLE_MAP.keys())
+    # Split into two batches; API limit is 15.
+    half = (len(nasa_params) + 1) // 2
+    batch1 = nasa_params[:half]
+    batch2 = nasa_params[half:]
+
+    for batch in [batch1, batch2]:
+        data, meta = pvlib.iotools.get_nasa_power(
+            latitude=44.76,
+            longitude=7.64,
+            start='2025-02-02',
+            end='2025-02-02',
+            parameters=batch,
+            map_variables=False,
+        )
+        missing = set(batch) - set(data.columns)
+        assert not missing, f"NASA POWER did not return: {sorted(missing)}"
+
+
+@pytest.mark.remote_data
+@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
+def test_get_nasa_power_all_variable_map_renamed():
+    """
+    With map_variables=True every NASA name must be renamed to its pvlib
+    equivalent. Catches duplicate-target collisions (e.g. two entries both
+    mapping to 'temp_dew', which silently drops a column under pandas rename).
+    """
+    from pvlib.iotools.nasa_power import VARIABLE_MAP
+    nasa_params = list(VARIABLE_MAP.keys())
+    pvlib_names = set(VARIABLE_MAP.values())
+
+    data, _ = pvlib.iotools.get_nasa_power(
+        latitude=44.76,
+        longitude=7.64,
+        start='2025-02-02',
+        end='2025-02-02',
+        parameters=nasa_params,
+        map_variables=True,
+    )
+
+    missing = pvlib_names - set(data.columns)
+    assert not missing, (
+        f"map_variables=True dropped pvlib columns: {sorted(missing)}. "
+        "Likely cause: duplicate target names in VARIABLE_MAP."
+    )
+
+
+@pytest.mark.remote_data
+@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
+def test_get_nasa_power_pressure_unit_conversion():
+    """
+    NASA POWER returns PS in kPa; pvlib convention is Pa.
+    Sea-level surface pressure should be ~101 kPa = ~101325 Pa, not ~101.
+    """
+    data, _ = pvlib.iotools.get_nasa_power(
+        latitude=0.0,  # sea-level equatorial point
+        longitude=-30.0,
+        start='2025-02-02',
+        end='2025-02-02',
+        parameters=['PS'],
+        map_variables=True,
+    )
+    mean_pressure = data['pressure'].mean()
+    # Anywhere on earth, surface pressure in Pa is between ~50k and ~110k.
+    # If the conversion is missing, value will be ~100 (kPa) and fail this.
+    assert 50_000 < mean_pressure < 110_000, (
+        f"PS not converted from kPa to Pa. Got mean={mean_pressure}"
+    )
+
+
+@pytest.mark.remote_data
+@pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY)
+def test_get_nasa_power_precipitable_water_unit_conversion():
+    """
+    NASA POWER returns TQV in kg/m^2 (= mm of water column);
+    pvlib convention is cm. Typical atmospheric column is 1-5 cm,
+    never above ~7 cm. If the /10 conversion is missing, values will
+    be 10-50 and fail this bound.
+    """
+    data, _ = pvlib.iotools.get_nasa_power(
+        latitude=0.0,  # tropics: high water vapor, worst case for bounds
+        longitude=-60.0,
+        start='2025-02-02',
+        end='2025-02-02',
+        parameters=['TQV'],
+        map_variables=True,
+    )
+    mean_pw = data['precipitable_water'].mean()
+    # pvlib precipitable_water is in cm. Tropical column is <~7 cm.
+    # Missing /10 conversion would give 10-70 (kg/m^2 = mm).
+    assert 0 < mean_pw < 10, (
+        f"TQV not converted from kg/m^2 to cm. Got mean={mean_pw}"
+    )