playing the the scaling of gridded covariances to match old CT better

da/ctgridded/statevector.py

@@ -80,7 +80,7 @@ class CtGriddedStateVector(StateVector):
                 cov         = cov_ocn
             else: 
                 cov         = f.GetVariable('covariance')
-                cov_sf      = 0.5/np.sqrt(cov.diagonal().sum())  # this scaling factor makes the total variance close to the value of a single ecoregion
+                cov_sf      = 0.75/np.sqrt(cov.diagonal().sum())  # this scaling factor makes the total variance close to the value of a single ecoregion
                 cov         = cov*cov_sf
 
             dummy   = f.close()