diff --git a/MARBL_tools/netcdf_comparison.py b/MARBL_tools/netcdf_comparison.py
index 087d6bf8..b6331a45 100755
--- a/MARBL_tools/netcdf_comparison.py
+++ b/MARBL_tools/netcdf_comparison.py
@@ -206,8 +206,8 @@ def _variable_check_loose(ds_base, ds_new, rtol, atol, thres):
         conversion_factor = _get_conversion_factor(ds_base, ds_new, var)
 
         # (1) Are NaNs in the same place?
-        mask = ~np.isnan(ds_base[var].data)
-        if np.any(mask ^ ~np.isnan(ds_new[var].data)):
+        mask = np.isfinite(ds_base[var].data)
+        if np.any(mask ^ np.isfinite(ds_new[var].data)):
             error_checking['messages'].append('NaNs are not in same place')
 
         # (2) compare everywhere that baseline is 0
@@ -237,8 +237,13 @@ def _variable_check_loose(ds_base, ds_new, rtol, atol, thres):
         new_data = np.where(np.abs(ds_base[var].data[mask]) > thres,
                             conversion_factor*ds_new[var].data[mask],
                             0)
+        # denominator for relative error is column max value
+        # note the assumption that column is first dimension
+        col_max = np.nanmax(np.abs(ds_base[var].data), axis=tuple(np.arange(1,len(ds_base[var].data.shape))))
+        rel_denom = (np.ones(ds_base[var].data.transpose().shape)*col_max).transpose()
+        rel_denom = rel_denom[mask]
         rel_err = np.where(base_data != 0, np.abs(new_data - base_data), 0) / \
-                  np.where(base_data != 0, np.abs(base_data), 1)
+                  np.where(rel_denom != 0, rel_denom, 1)
         if np.any(rel_err > rtol):
             if rtol == 0:
                 abs_err = np.abs(new_data - base_data)