Changes between Initial Version and Version 1 of PDAF_diag_diffstats

Timestamp:

Mar 27, 2026, 6:30:09 PM (4 days ago)

Author:

lnerger

Comment:

--

PDAF_diag_diffstats

@@ +1 @@
+= PDAF_diag_diffstats = 
+
+This page documents the routine `PDAF_diag_diffstats` of PDAF, which was introduced with PDAF V3.1.
+
+The routine is provided two vector of the same length and returns a vector with 6 statistics comparing the two vectors. The statistics can, for example, be used to plot a Taylor diagram.
+
+The routine can be called in the pre/poststep routine of PDAF both before and after the analysis step to compute the ensemble statistics. 
+
+The interface is: 
+{{{
+  SUBROUTINE PDAF_diag_diffstats(dim_p, vec1, vec2, stats, verbose)
+
+    INTEGER, INTENT(in) :: dim_p     !< Size of vector
+    REAL, INTENT(inout) :: vec1(:)   !< Vector 1
+    REAL, INTENT(inout) :: vec2(:)   !< Vector 2
+    REAL, INTENT(inout) :: stats(6)  !< Vector holding statistics
+          ! Included statistics are:
+          !  (1,:) correlations between vec1 and vec2 (corr)
+          !  (2,:) centered RMS difference between vec1 and vec2 (cRMSD)
+          !  (3,:) mean bias (vec1-vec2)
+          !  (4,:) mean absolute difference between vec1 and vec2 (MAD)
+          !  (5,:) standard deviation of vec1 (STDDEV(vec1))
+          !  (6,:) standard deviation of vec2 (STDDEV(vec2))
+    INTEGER, INTENT(in) :: verbose   !< Verbosity flag
+}}}
+
+
+For verbose>0 a list of statistics is printed for each observation type in the form
+{{{
+PDAF   corr      cRMSD       bias         MAD      STDDEV(1)   STDDEV(2)
+PDAF   0.611   7.084E-01   4.376E-02   5.774E-01   8.787E-01   7.179E-01
+}}}
+
+**Note:**
+ * The statistics are computed for the global domain. Thus, with parallelization the values in `stats(6)` will be identical for all processes.
+ * The routine performs MPI operations to obtain the global result. These operations are performed within the communicator `COMM_filter`, i.e. within the communicator computing the analysis step.
+ * To compare the assimilated observations with the ensemble mean, one can use the PDAF-OMI routine [wiki:PDAFomi_diag_diffstats].