Update nasa_power VARIABLE_MAP with additional parameters (#2762)

* Update nasa_power VARIABLE_MAP with additional parameters

- Added: ALLSKY_SFC_LW_DWN, ALLSKY_TOA_SW_DWN, CLRSKY_DIFF, PS,
  T2MDEW, T2MWET, RH2M, SRF_ALB, TQV
- Fix PS unit conversion: kPa to Pa for pvlib.atmosphere compatibility
- Fix parameter names: CLRSKY_DIFF -> CLRSKY_SFC_SW_DIFF,
  ALLSKY_TOA_SW_DWN -> TOA_SW_DWN, SRF_ALB -> ALLSKY_SRF_ALB
- Drop T2MWET (duplicate target name breaks pandas rename)
- Add TQV unit conversion: kg/m^2 to cm
- Add regression tests for all VARIABLE_MAP params and unit conversions

* Fix flake8 E501/E702 in test file

* Address review comments: move unit conversion note to Notes section, simplify inline comments

- Move unit conversion documentation from map_variables param description
  to a dedicated Notes section in the docstring
- Simplify pressure conversion comment (remove specific function list)
- Simplify TQV conversion comment (remove specific function reference)

* Add dni_clear to variable map

* Update notes section

* Fix linter

* Split test_get_nasa_power_all_variable_map_parameters_valid into two batches

VARIABLE_MAP now has 16 entries, exceeding NASA POWER's 15-parameter-per-request
limit. Split the test into two batches of 8 instead of asserting the limit.

* Add whatsnew entry for nasa_power VARIABLE_MAP additions (PR #2762)

* Address review: simplify whatsnew entry, add self to Contributors (PR #2762)

* Apply suggestion from @echedey-ls

Co-authored-by: Echedey Luis <80125792+echedey-ls@users.noreply.github.com>

* Apply suggestion from @AdamRJensen - combine whatsnew entries

---------

Co-authored-by: Adam R. Jensen <39184289+AdamRJensen@users.noreply.github.com>
Co-authored-by: Echedey Luis <80125792+echedey-ls@users.noreply.github.com>

Author: 3 people

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

@@ -40,13 +40,11 @@ Bug fixes
 
 Enhancements
 ~~~~~~~~~~~~
-* Add the ``front_side_fraction`` parameter to
-  :py:func:`pvlib.snow.loss_townsend` to support Townsend snow-loss
-  workflows for bifacial systems. (:issue:`2755`, :pull:`2756`)
-  
-* 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``, ``longwave_down``,
+  and ``albedo``.
+  (:issue:`2731`, :pull:`2753`, :pull:`2762`)
 
 
 Documentation
@@ -83,4 +81,5 @@ Contributors
 * :ghuser:`shethkajal7`
 * Arthur Onno (:ghuser:`ArthurOnnoTerabase`)
 * Adam R. Jensen (:ghuser:`AdamRJensen`)
+* Karl Hill (:ghuser:`karlhillx`)
 * Rajiv Daxini (:ghuser:`RDaxini`)

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}"
+    )