[Dart-dev] DART/branches Revision: 12240

[dart at ucar.edu]

nancy at ucar.edu
2017-12-22 14:08:19 -0700 (Fri, 22 Dec 2017)
250
fix the tests that try to print out in english words
what combination of inflation options were selected.

am expecting no change in the numerical results.

also updated a few comments to be more correct,
and lined a few things up.  merry xmas tim.




Modified: DART/branches/enhanced_inflation/assimilation_code/modules/assimilation/adaptive_inflate_mod.f90
===================================================================
--- DART/branches/enhanced_inflation/assimilation_code/modules/assimilation/adaptive_inflate_mod.f90	2017-12-22 19:27:54 UTC (rev 12239)
+++ DART/branches/enhanced_inflation/assimilation_code/modules/assimilation/adaptive_inflate_mod.f90	2017-12-22 21:08:19 UTC (rev 12240)
@@ -571,8 +571,8 @@
 end subroutine update_inflation
 
 !------------------------------------------------------------------
-!> Uses one of 3 algorithms in references on DART web site to update the distribution of inflation.
-!> Anderson 2007, Anderson 2009, or Gharamti 2017
+!> Uses one of 2 algorithms in references on DART web site to update the 
+!> distribution of inflation:  Anderson 2007, 2009 or Gharamti 2017
 
 subroutine bayes_cov_inflate(ens_size, inf_type, x_p, sigma_p_2, y_o, sigma_o_2, lambda_mean, lambda_sd, &
    gamma_corr, sd_lower_bound_in, sd_max_change_in, new_cov_inflate, new_cov_inflate_sd)
@@ -589,7 +589,7 @@
 real(r8) :: b, c, d, Q, R, disc, alpha, beta, cube_root_alpha, cube_root_beta, x
 real(r8) :: rrr, cube_root_rrr, angle, mx(3), sep(3), mlambda(3)
 
-! If gamma is 0, nothing happens
+! If gamma is 0, nothing changes
 if(gamma_corr <= 0.0_r8) then
    new_cov_inflate    = lambda_mean
    new_cov_inflate_sd = lambda_sd
@@ -693,7 +693,7 @@
       endif
    
       ! Can now compute the standard deviation consistent with this as
-         ! sigma = sqrt(-x^2 / (2 ln(r))  where r is ratio and x is lambda_sd (distance from mean)
+      !    sigma = sqrt(-x^2 / (2 ln(r))  where r is ratio and x is lambda_sd (distance from mean)
       new_cov_inflate_sd = sqrt( -1.0_r8 * lambda_sd_2 / (2.0_r8 * log(ratio)))
    
       ! Prevent an increase in the sd of lambda???
@@ -1026,7 +1026,7 @@
 DD = var_p(3)*mode_p(3)
 EE = (CC + BB + DD + mode_p(9) + 6.0_r8*sqrt(3.0_r8)*AA*var_p(3)) / var_p(3)
 
-beta = (7.0_r8*var*mode + mode_p(3))/(3.0_r8*var)                           + &
+beta = (7.0_r8*var*mode + mode_p(3))/(3.0_r8*var)                               + &
        EE**(1.0_r8/3.0_r8)/3.0_r8 + mode_p(2)*(var_p(2) + 14.0_r8*var*mode_p(2) + &
        mode_p(4)) / (3.0_r8*var_p(2)*EE**(1.0_r8/3.0_r8))
 
@@ -1047,14 +1047,15 @@
 else
   det = 'random-noise,'
 endif
-if (inflation_handle%sd_lower_bound > inflation_handle%inf_lower_bound) then
-   det = trim(det) // ' covariance adaptive,'
-endif
 if (inflation_handle%inf_lower_bound < 1.0_r8) then
    det = trim(det) // ' deflation permitted,'
 endif
 if (inflation_handle%minmax_sd(2) > 0.0_r8) then
   tadapt = ' time-adaptive,'
+   if (inflation_handle%sd_lower_bound < inflation_handle%minmax_sd(2) .or. &
+       inflation_handle%inflation_sub_flavor == 5) then
+      tadapt = trim(tadapt) // ' time-rate adaptive,'
+   endif
 else
   tadapt = ' time-constant,'
 endif
@@ -1159,6 +1160,8 @@
    call send_minmax_to(minmax_mean, map_pe_to_task(ens_handle, 0), global_val)
    if (ens_handle%my_pe == 0) inflation_handle%minmax_mean = global_val
 
+else
+   if (ens_handle%my_pe == 0) inflation_handle%minmax_mean = inflation_handle%inflate
 endif
 
 if (inflation_handle%sd_from_restart) then
@@ -1170,7 +1173,8 @@
    ! collect on pe 0
    call send_minmax_to(minmax_sd, map_pe_to_task(ens_handle, 0), global_val)
    if (ens_handle%my_pe == 0) inflation_handle%minmax_sd = global_val
-
+else
+   if (ens_handle%my_pe == 0) inflation_handle%minmax_sd = inflation_handle%sd 
 endif
 
 end subroutine get_minmax_task_zero