trim rcp config files

Former-commit-id: e69d210f94418ee57ebb179b11a65027e861e54d

models/examples/gfdl_cm3/config/rcp26data.json.REMOVED.git-id

@@ -1 +1 @@
-4fd2e696fabaf5864effaa61d3507a2d56b223f6
+50eb36defaf25fb4f786de99370de8f77c8ad5ff

models/examples/gfdl_cm3/config/rcp85data.json.REMOVED.git-id

@@ -1 +1 @@
-61cfb7f0563cecc897da3c7c187142935f49c75f
+00885c964cf72522c637b95ccadc99b8b2760e39

models/examples/gfdl_cm3/src/climate_model.py

@@ -20,14 +20,14 @@ def temp_inc(init_data, year):
             # convert to format that plays nice with mongodb; only get U.S squares
             single_year_US[i] = {}
         for j in json1_data[i]:
-            mean_glob_temps.append(json1_data[i][j][year][2])
+            mean_glob_temps.append(json1_data[i][j][year][0])
 
             # contiguous United States boundaries
             if 49 >= float(i) >= 23 and -68 >= float(j) >= -128:
                 single_year_US[i][j] = (
-                    json1_data[i][j][year][0],
+                    json1_data[i][j][year][0] - 273.15,
                     json1_data[i][j][year][1],
-                    json1_data[i][j][year][2] - 273.15,
+                    json1_data[i][j][year][2],
                 )
 
     # apply weights to get global average temperature
@@ -48,11 +48,11 @@ def temp_inc(init_data, year):
             # precipitation (mm)
             translated_pr[
                 f"lat_{int(lat*100)}_lon_{int(lon*100)}"
-            ] = lon_values[0]
+            ] = lon_values[1]
             # evaporation (mm)
             translated_ev[
                 f"lat_{int(lat*100)}_lon_{int(lon*100)}"
-            ] = lon_values[1]
+            ] = lon_values[2]
 
     return (
         temperature,