Add simple test and fix calling nonzero on

0d arrays is deprecated on line:4594, when test
with simple value.

src/metpy/calc/thermo.py

@@ -4591,16 +4591,12 @@ def galvez_davison_index(pressure, temperature, mixing_ratio, surface_pressure,
     <Quantity(-8.78797532, 'dimensionless')>
     """
     if np.any(np.max(pressure, axis=vertical_dim) < 950 * units.hectopascal):
-        indices_without_950 = np.where(
-            np.max(pressure, axis=vertical_dim) < 950 * units.hectopascal
-        )
         raise ValueError(
             f'Data not provided for 950hPa or higher pressure. '
             f'GDI requires 950hPa temperature and dewpoint data, '
             f'see referenced paper section 3.d. in docstring for discussion of'
             f' extrapolating sounding data below terrain surface in high-'
             f'elevation regions.\nIndices without a 950hPa or higher datapoint'
-            f':\n{indices_without_950}'
             f'\nMax provided pressures:'
             f'\n{np.max(pressure, axis=0)}'
         )

tests/calc/test_thermo.py

@@ -2545,6 +2545,24 @@ def test_gdi_no_950_raises_valueerror(index_xarray_data):
         )
 
 
+def test_gdi_no_950_by_simplevalue():
+    """GDI requires a 950hPa or higher measurement."""
+    with pytest.raises(ValueError):
+        pressure = np.array([922., 850., 700., 600., 500., 400., 300., 250.,
+                             200., 150.]) * units.hPa
+        temperature = np.array([22.6, 18.6, 8.6, 2.8, -4.6, -15.5, -30.6, -40.4,
+                                -52.9, -67.8,]) * units.degC
+        relative_humidity = np.array([71.12, 71.16, 70.79, 50.33, 28.22, 4.80, 3.68, 5.82,
+                                      18.18, 27.33]) * units.percent
+        mixrat = mixing_ratio_from_relative_humidity(pressure, temperature, relative_humidity)
+        galvez_davison_index(
+            pressure,
+            temperature,
+            mixrat,
+            pressure[0]
+        )
+
+
 def test_gradient_richardson_number():
     """Test gradient Richardson number calculation."""
     theta = units('K') * np.asarray([254.5, 258.3, 262.2])