snapshot...

modules/amv/intercompare.py

@@ -1042,6 +1042,7 @@ def best_fit(amv_spd, amv_dir, amv_prs, amv_lat, amv_lon, fcst_spd, fcst_dir, fc
 
 
 def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcst_dir, fcst_alt,
+                      fcst_uwind=None, fcst_vwind=None,
                       alt_top=25000.0, alt_bot=0.0, bf_half_width=500.0, constraint_half_width=400.0):
     verbose = False
     fcst_num_levels = fcst_spd.shape[0]
@@ -1064,16 +1065,19 @@ def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcs
             print('AMV location lat,lon,alt ({0},{1},{2}) failed to find fcst alt around AMV'.format(amv_lat,amv_lon,amv_alt))
         return bf_tup
 
-    # Diagnostic field: Find the model minimum speed and maximum speed within PressDiff of the AMV.
-    if verbose:
-        sat_wind_min_spd = min(fcst_spd[kk])
-        sat_wind_max_spd = max(fcst_spd[kk])
-
     # Compute U anv V for both AMVs and forecast
     amv_uwind = -amv_spd * np.sin((np.pi/180.0)*amv_dir)
     amv_vwind = -amv_spd * np.cos((np.pi/180.0)*amv_dir)
+    if fcst_uwind is None:
         fcst_uwind = -fcst_spd * np.sin((np.pi/180.0)*fcst_dir)
         fcst_vwind = -fcst_spd * np.cos((np.pi/180.0)*fcst_dir)
+    else:
+        fcst_spd = np.sqrt(fcst_uwind**2 + fcst_vwind**2)
+
+    # Diagnostic field: Find the model minimum speed and maximum speed within PressDiff of the AMV.
+    if verbose:
+        sat_wind_min_spd = min(fcst_spd[kk])
+        sat_wind_max_spd = max(fcst_spd[kk])
 
     # Calculate the vector difference between the AMV and model background at all levels.
     vec_diff = np.sqrt((amv_uwind - fcst_uwind) ** 2 + (amv_vwind - fcst_vwind) ** 2)