Index: ../trunk-jpl/src/m/classes/stochasticforcing.py
===================================================================
--- ../trunk-jpl/src/m/classes/stochasticforcing.py	(revision 26673)
+++ ../trunk-jpl/src/m/classes/stochasticforcing.py	(revision 26674)
@@ -134,7 +134,7 @@
                     dimensions[ind] = md.frontalforcings.num_basins
 
             # Scaling covariance matrix (scale column-by-column and row-by-row)
-            scaledfields = ['DefaultCalving', 'SMBautoregression'] # list of fields that need scaling * 1/yts
+            scaledfields = ['DefaultCalving','FloatingMeltRate','SMBautoregression'] # list of fields that need scaling * 1/yts
             tempcovariance = np.copy(self.covariance)
             for i in range(num_fields):
                 if self.fields[i] in scaledfields:
Index: ../trunk-jpl/test/NightlyRun/test543.py
===================================================================
--- ../trunk-jpl/test/NightlyRun/test543.py	(revision 26673)
+++ ../trunk-jpl/test/NightlyRun/test543.py	(revision 26674)
@@ -75,8 +75,8 @@
 
 #Hard-coding covariance matrix because python is complaining
 covglob = np.array([[1e-4,0.,0.,0.,0.,0.],[0.,1e-4,0.,0.,0.,0.],[0.,0.,1e-2,0.,0.,0.],[0.,0.,0.,1e-1,0.,0.],[0.,0.,0.,0.,0.05,0.],[0.,0.,0.,0.,0.,0.05]])
-testchol = np.linalg.cholesky(covglob)
-print(testchol)
+#testchol = np.linalg.cholesky(covglob)
+#print(testchol)
 
 # Stochastic forcing
 md.stochasticforcing.isstochasticforcing = 1