forked from jkbk2004/stochastic_physics
-
Notifications
You must be signed in to change notification settings - Fork 0
/
get_stochy_pattern.F90
670 lines (613 loc) · 28.3 KB
/
get_stochy_pattern.F90
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
!>@brief The module 'get_stochy_pattern_mod' contains the subroutines to retrieve the random pattern in the cubed-sphere grid
module get_stochy_pattern_mod
use kinddef
use spectral_transforms, only : len_trie_ls, &
len_trio_ls, ls_dim, stochy_la2ga, &
coslat_a, latg, levs, lonf, skeblevs,&
four_to_grid, spec_to_four, dezouv_stochy,dozeuv_stochy
use stochy_namelist_def, only : n_var_lndp, ntrunc, stochini,n_var_spp
use stochy_data_mod, only : gg_lats, gg_lons, inttyp, nskeb, nshum, nsppt, &
nocnsppt,nepbl,nlndp, &
rnlat, rpattern_sfc, rpattern_skeb, &
rpattern_shum, rpattern_sppt, rpattern_ocnsppt,&
rpattern_epbl1, rpattern_epbl2, skebu_save, &
nspp,rpattern_spp, &
skebv_save, skeb_vwts, skeb_vpts, wlon
use stochy_patterngenerator_mod, only: random_pattern, ndimspec, &
patterngenerator_advance
use stochy_internal_state_mod, only: stochy_internal_state
use mpi_wrapper, only : mp_reduce_sum,is_rootpe
use mersenne_twister, only: random_seed
implicit none
private
public get_random_pattern_vector,get_random_pattern_spp
public get_random_pattern_sfc,get_random_pattern_scalar
public write_stoch_restart_atm,write_stoch_restart_ocn
logical :: first_call=.true.
contains
!>@brief The subroutine 'get_random_pattern_sfc' converts spherical harmonics to the gaussian grid then interpolates to the target grid
!>@details This subroutine is for a 2-D (lat-lon) scalar field
subroutine get_random_pattern_sfc(rpattern,npatterns,&
gis_stochy,pattern_3d)
!\callgraph
! generate a random pattern for stochastic physics
implicit none
type(random_pattern), intent(inout) :: rpattern(npatterns)
type(stochy_internal_state), intent(in) :: gis_stochy
integer,intent(in):: npatterns
integer i,j,lat,n,k
real(kind=kind_dbl_prec), dimension(lonf,gis_stochy%lats_node_a,1):: wrk2d
! logical lprint
real(kind=kind_dbl_prec), allocatable, dimension(:,:) :: workg
real (kind=kind_dbl_prec) glolal(lonf,gis_stochy%lats_node_a)
integer kmsk0(lonf,gis_stochy%lats_node_a)
real(kind=kind_dbl_prec),intent(out) :: pattern_3d(gis_stochy%nx,gis_stochy%ny,n_var_lndp)
real(kind=kind_dbl_prec) :: pattern_1d(gis_stochy%nx)
do k=1,n_var_lndp
kmsk0 = 0
glolal = 0.
do n=1,npatterns
call patterngenerator_advance(rpattern(n),k,.false.)
! if (is_rootpe()) print *, 'Random pattern for LNDP PERTS in get_random_pattern_fv3_sfc: k, min, max ',k,minval(rpattern_sfc(n)%spec_o(:,:,k)), maxval(rpattern_sfc(n)%spec_o(:,:,k))
call scalarspect_to_gaugrid(rpattern(n),gis_stochy,wrk2d,k)
glolal = glolal + wrk2d(:,:,1)
enddo
allocate(workg(lonf,latg))
workg = 0.
do j=1,gis_stochy%lats_node_a
lat=gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+j)
do i=1,lonf
workg(i,lat) = glolal(i,j)
enddo
enddo
call mp_reduce_sum(workg,lonf,latg)
! if (is_rootpe()) print *, 'workg after mp_reduce_sum for LNDP PERTS in get_random_pattern_fv3_sfc: k, min, max ',k,minval(workg), maxval(workg)
! interpolate to cube grid
do j=1,gis_stochy%ny
pattern_1d = 0
associate( tlats=>gis_stochy%parent_lats(1:gis_stochy%len(j),j),&
tlons=>gis_stochy%parent_lons(1:gis_stochy%len(j),j))
call stochy_la2ga(workg,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
pattern_3d(:,j,k)=pattern_1d(:)
end associate
enddo
! if (is_rootpe()) print *, '3D pattern for LNDP PERTS in get_random_pattern_fv3_sfc: k, min, max ',k,minval(pattern_3d(:,:,k)), maxval(pattern_3d(:,:,k))
deallocate(workg)
enddo ! loop over k, n_var_lndp
end subroutine get_random_pattern_sfc
!>@brief The subroutine 'get_random_pattern_fv3_vect' converts spherical harmonics to a vector on gaussian grid then interpolates to the target grid
!>@details This subroutine is for a 2-D (lat-lon) vector field
subroutine get_random_pattern_vector(rpattern,npatterns,&
gis_stochy,upattern_3d,vpattern_3d)
!\callgraph
! generate a random pattern for stochastic physics
implicit none
type(stochy_internal_state), intent(in) :: gis_stochy
type(random_pattern), intent(inout) :: rpattern(npatterns)
real(kind=kind_dbl_prec), dimension(len_trie_ls,2) :: vrtspec_e,divspec_e
real(kind=kind_dbl_prec), dimension(len_trio_ls,2) :: vrtspec_o,divspec_o
integer:: npatterns
real(kind=kind_dbl_prec) :: upattern_3d(gis_stochy%nx,gis_stochy%ny,levs)
real(kind=kind_dbl_prec) :: vpattern_3d(gis_stochy%nx,gis_stochy%ny,levs)
real(kind=kind_dbl_prec) :: pattern_1d(gis_stochy%nx)
integer i,j,lat,n,nn,k
real(kind_phys), dimension(lonf,gis_stochy%lats_node_a,1):: wrk2du,wrk2dv
! logical lprint
real(kind_dbl_prec), allocatable, dimension(:,:) :: workgu,workgv
integer kmsk0(lonf,gis_stochy%lats_node_a)
kmsk0 = 0
allocate(workgu(lonf,latg))
allocate(workgv(lonf,latg))
divspec_e = 0; divspec_o = 0.
if (first_call) then
allocate(skebu_save(gis_stochy%nx,gis_stochy%ny,skeblevs))
allocate(skebv_save(gis_stochy%nx,gis_stochy%ny,skeblevs))
do k=2,skeblevs
workgu = 0.
workgv = 0.
do n=1,npatterns
if (.not. stochini) call patterngenerator_advance(rpattern(n),k,first_call)
! ke norm (convert streamfunction forcing to vorticity forcing)
do nn=1,2
vrtspec_e(:,nn) = gis_stochy%kenorm_e*rpattern(n)%spec_e(:,nn,k)
vrtspec_o(:,nn) = gis_stochy%kenorm_o*rpattern(n)%spec_o(:,nn,k)
enddo
! convert to winds
call vrtdivspect_to_uvgrid( divspec_e,divspec_o,vrtspec_e,vrtspec_o,&
wrk2du,wrk2dv, gis_stochy)
do i=1,lonf
do j=1,gis_stochy%lats_node_a
lat=gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+j)
workgu(i,lat) = workgu(i,lat) + wrk2du(i,j,1)
workgv(i,lat) = workgv(i,lat) + wrk2dv(i,j,1)
enddo
enddo
enddo
call mp_reduce_sum(workgu,lonf,latg)
call mp_reduce_sum(workgv,lonf,latg)
! interpolate to cube grid
do j=1,gis_stochy%ny
pattern_1d = 0
associate( tlats=>gis_stochy%parent_lats(1:gis_stochy%len(j),j),&
tlons=>gis_stochy%parent_lons(1:gis_stochy%len(j),j))
call stochy_la2ga(workgu,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
skebu_save(:,j,k)=pattern_1d(:)
call stochy_la2ga(workgv,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
skebv_save(:,j,k)=-1*pattern_1d(:)
end associate
enddo
enddo
endif
do k=1,skeblevs-1
skebu_save(:,:,k)=skebu_save(:,:,k+1)
skebv_save(:,:,k)=skebv_save(:,:,k+1)
do n=1,npatterns
rpattern(n)%spec_e(:,:,k)=rpattern(n)%spec_e(:,:,k+1)
rpattern(n)%spec_o(:,:,k)=rpattern(n)%spec_o(:,:,k+1)
enddo
enddo
! get pattern for last level
workgu = 0.
workgv = 0.
do n=1,npatterns
call patterngenerator_advance(rpattern(n),skeblevs,first_call)
! ke norm (convert streamfunction forcing to vorticity forcing)
divspec_e = 0; divspec_o = 0.
do nn=1,2
vrtspec_e(:,nn) = gis_stochy%kenorm_e*rpattern(n)%spec_e(:,nn,skeblevs)
vrtspec_o(:,nn) = gis_stochy%kenorm_o*rpattern(n)%spec_o(:,nn,skeblevs)
enddo
! convert to winds
call vrtdivspect_to_uvgrid(&
divspec_e,divspec_o,vrtspec_e,vrtspec_o,&
wrk2du,wrk2dv, gis_stochy)
do i=1,lonf
do j=1,gis_stochy%lats_node_a
lat=gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+j)
workgu(i,lat) = workgu(i,lat) + wrk2du(i,j,1)
workgv(i,lat) = workgv(i,lat) + wrk2dv(i,j,1)
enddo
enddo
enddo
call mp_reduce_sum(workgu,lonf,latg)
call mp_reduce_sum(workgv,lonf,latg)
! interpolate to cube grid
do j=1,gis_stochy%ny
pattern_1d = 0
associate( tlats=>gis_stochy%parent_lats(:,j),&
tlons=>gis_stochy%parent_lons(:,j))
call stochy_la2ga(workgu,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
skebu_save(:,j,skeblevs)=pattern_1d(:)
call stochy_la2ga(workgv,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
skebv_save(:,j,skeblevs)=-1*pattern_1d(:)
end associate
enddo
deallocate(workgu)
deallocate(workgv)
! interpolate in the vertical ! consider moving to cubed sphere side, more memory, but less interpolations
do k=1,levs
do j=1,gis_stochy%ny
upattern_3d(:,j,k) = skeb_vwts(k,1)*skebu_save(:,j,skeb_vpts(k,1))+skeb_vwts(k,2)*skebu_save(:,j,skeb_vpts(k,2))
vpattern_3d(:,j,k) = skeb_vwts(k,1)*skebv_save(:,j,skeb_vpts(k,1))+skeb_vwts(k,2)*skebv_save(:,j,skeb_vpts(k,2))
enddo
enddo
first_call=.false.
end subroutine get_random_pattern_vector
!>@brief The subroutine 'get_random_pattern_scalar' converts spherical harmonics to the gaussian grid then interpolates to the target grid
!>@details This subroutine is for a 2-D (lat-lon) scalar field
subroutine get_random_pattern_scalar(rpattern,npatterns,&
gis_stochy,pattern_2d)
! generate a random pattern for stochastic physics
implicit none
type(random_pattern), intent(inout) :: rpattern(npatterns)
type(stochy_internal_state) :: gis_stochy
integer,intent(in):: npatterns
integer i,j,lat,n
real(kind=kind_dbl_prec), dimension(lonf,gis_stochy%lats_node_a,1):: wrk2d
! logical lprint
real(kind=kind_dbl_prec), allocatable, dimension(:,:) :: workg
real (kind=kind_dbl_prec) glolal(lonf,gis_stochy%lats_node_a)
integer kmsk0(lonf,gis_stochy%lats_node_a)
real(kind=kind_dbl_prec) :: pattern_2d(gis_stochy%nx,gis_stochy%ny)
real(kind=kind_dbl_prec) :: pattern_1d(gis_stochy%nx)
kmsk0 = 0
glolal = 0.
do n=1,npatterns
call patterngenerator_advance(rpattern(n),1,.false.)
call scalarspect_to_gaugrid(rpattern(n),gis_stochy, &
wrk2d,1)
glolal = glolal + wrk2d(:,:,1)
enddo
allocate(workg(lonf,latg))
workg = 0.
do j=1,gis_stochy%lats_node_a
lat=gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+j)
do i=1,lonf
workg(i,lat) = glolal(i,j)
enddo
enddo
call mp_reduce_sum(workg,lonf,latg)
! interpolate to cube grid
do j=1,gis_stochy%ny
pattern_1d = 0
associate( tlats=>gis_stochy%parent_lats(1:gis_stochy%len(j),j),&
tlons=>gis_stochy%parent_lons(1:gis_stochy%len(j),j))
call stochy_la2ga(workg,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
pattern_2d(:,j)=pattern_1d(:)
end associate
enddo
deallocate(workg)
end subroutine get_random_pattern_scalar
!>@brief The subroutine 'get_random_pattern_spp' converts spherical harmonics
!to the gaussian grid then interpolates to the target grid
!>@details This subroutine is for a 2-D (lat-lon) scalar field
subroutine get_random_pattern_spp(rpattern,npatterns,&
gis_stochy,pattern_3d)
! generate a random pattern for stochastic physics
implicit none
type(random_pattern), intent(inout) :: rpattern(npatterns)
type(stochy_internal_state) :: gis_stochy
integer,intent(in):: npatterns
integer i,j,lat,n
! logical lprint
real(kind=kind_dbl_prec), allocatable, dimension(:,:) :: workg
real (kind=kind_dbl_prec) glolal(lonf,gis_stochy%lats_node_a)
integer kmsk0(lonf,gis_stochy%lats_node_a)
real(kind=kind_dbl_prec) :: pattern_3d(gis_stochy%nx,gis_stochy%ny,npatterns)
real(kind=kind_dbl_prec) :: pattern_1d(gis_stochy%nx)
allocate(workg(lonf,latg))
do n=1,npatterns
kmsk0 = 0
glolal = 0.
call patterngenerator_advance(rpattern(n),1,.false.)
call scalarspect_to_gaugrid(rpattern(n),gis_stochy, &
glolal,1)
workg = 0.
do j=1,gis_stochy%lats_node_a
lat=gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+j)
do i=1,lonf
workg(i,lat) = glolal(i,j)
enddo
enddo
call mp_reduce_sum(workg,lonf,latg)
! interpolate to cube grid
do j=1,gis_stochy%ny
pattern_1d = 0
associate( tlats=>gis_stochy%parent_lats(1:gis_stochy%len(j),j),&
tlons=>gis_stochy%parent_lons(1:gis_stochy%len(j),j))
call stochy_la2ga(workg,lonf,latg,gg_lons,gg_lats,wlon,rnlat,&
pattern_1d(1:gis_stochy%len(j)),gis_stochy%len(j),tlats,tlons)
pattern_3d(:,j,n)=pattern_1d(:)
end associate
enddo
enddo
deallocate(workg)
end subroutine get_random_pattern_spp
!>@brief The subroutine 'scalarspect_to_gaugrid' converts scalar spherical harmonics to a scalar on a gaussian grid
!>@details This subroutine is for a 2-D (lat-lon) scalar field
subroutine scalarspect_to_gaugrid(rpattern,gis_stochy,datag,n)
!\callgraph
implicit none
type(random_pattern), intent(in) :: rpattern
type(stochy_internal_state), intent(in) :: gis_stochy
integer , intent(in) :: n
real(kind=kind_dbl_prec), intent(out) :: datag(lonf,gis_stochy%lats_node_a)
! local vars
real(kind=kind_dbl_prec) for_gr_a_1(gis_stochy%lon_dim_a,1,gis_stochy%lats_dim_a)
real(kind=kind_dbl_prec) for_gr_a_2(lonf,1,gis_stochy%lats_dim_a)
integer i,k
integer lan,lat
call spec_to_four(rpattern%spec_e(:,:,n), rpattern%spec_o(:,:,n), &
gis_stochy%plnev_a,gis_stochy%plnod_a,&
gis_stochy%ls_node, &
gis_stochy%lats_dim_a,for_gr_a_1,&
gis_stochy%ls_nodes,gis_stochy%max_ls_nodes,&
gis_stochy%lats_nodes_a,gis_stochy%global_lats_a,&
gis_stochy%lats_node_a,gis_stochy%ipt_lats_node_a,1)
do lan=1,gis_stochy%lats_node_a
lat = gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+lan)
call four_to_grid(for_gr_a_1(:,:,lan),for_gr_a_2(:,:,lan),&
gis_stochy%lon_dim_a,1)
enddo
datag = 0.
do lan=1,gis_stochy%lats_node_a
lat = gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+lan)
do i=1,lonf
datag(i,lan) = for_gr_a_2(i,1,lan)
enddo
enddo
return
end subroutine scalarspect_to_gaugrid
!>@brief The subroutine 'write_patterns' writes out a single pattern and the seed associated with the random number sequence in netcdf
!>@brief The subroutine 'write_stoch_restart_atm' writes out the speherical harmonics to a file, controlled by restart_interval
!>@details Only the active patterns are written out
subroutine write_stoch_restart_atm(sfile)
!\callgraph
use netcdf
use stochy_namelist_def, only : do_sppt,do_shum,do_skeb,lndp_type,do_spp
implicit none
character(len=*) :: sfile
integer :: stochlun,k,n,isize,ierr
integer :: ncid,varid1a,varid1b,varid2a,varid2b,varid3a,varid3b,varid4a,varid4b,varid5a,varid5b
integer :: seed_dim_id,spec_dim_id,zt_dim_id,ztsfc_dim_id,np_dim_id,npsfc_dim_id
integer :: ztspp_dim_id,npspp_dim_id
include 'netcdf.inc'
if ( ( .NOT. do_sppt) .AND. (.NOT. do_shum) .AND. (.NOT. do_skeb) .AND. (lndp_type==0 ) .AND. (.NOT. do_spp)) return
stochlun=99
if (is_rootpe()) then
if (nsppt > 0 .OR. nshum > 0 .OR. nskeb > 0 .OR. nlndp>0 .OR. nspp>0 ) then
ierr=nf90_create(trim(sfile),cmode=NF90_CLOBBER,ncid=ncid)
ierr=NF90_PUT_ATT(ncid,NF_GLOBAL,"ntrunc",ntrunc)
call random_seed(size=isize) ! get seed size
ierr=NF90_DEF_DIM(ncid,"len_seed",isize,seed_dim_id)
ierr=NF90_PUT_ATT(ncid,seed_dim_id,"long_name","length of random seed")
ierr=NF90_DEF_DIM(ncid,"num_patterns",NF_UNLIMITED,np_dim_id) ! should be 5
ierr=NF90_PUT_ATT(ncid,np_dim_id,"long_name","number of random patterns (max of 5)")
if (lndp_type .NE. 0) then
ierr=NF90_DEF_DIM(ncid,"num_patterns_sfc",nlndp,npsfc_dim_id) ! should be 5
ierr=NF90_PUT_ATT(ncid,npsfc_dim_id,"long_name","number of random patterns for surface)")
ierr=NF90_DEF_DIM(ncid,"n_var_lndp",n_var_lndp,ztsfc_dim_id)
ierr=NF90_PUT_ATT(ncid,ztsfc_dim_id,"long_name","number of sfc perturbation types")
endif
if (nspp .GT. 0) then
ierr=NF90_DEF_DIM(ncid,"num_patterns_spp",nspp,npspp_dim_id) ! should be 5
ierr=NF90_PUT_ATT(ncid,npspp_dim_id,"long_name","number of random patterns for spp)")
ierr=NF90_DEF_DIM(ncid,"n_var_spp",n_var_spp,ztspp_dim_id)
ierr=NF90_PUT_ATT(ncid,ztspp_dim_id,"long_name","number of spp perturbation types")
endif
ierr=NF90_DEF_DIM(ncid,"ndimspecx2",2*ndimspec,spec_dim_id)
ierr=NF90_PUT_ATT(ncid,spec_dim_id,"long_name","number of spectral cofficients")
if (do_sppt) then
ierr=NF90_DEF_VAR(ncid,"sppt_seed",NF90_DOUBLE,(/seed_dim_id, np_dim_id/), varid1a)
ierr=NF90_PUT_ATT(ncid,varid1a,"long_name","random number seed for SPPT")
ierr=NF90_DEF_VAR(ncid,"sppt_spec",NF90_DOUBLE,(/spec_dim_id, np_dim_id/), varid1b)
ierr=NF90_PUT_ATT(ncid,varid1b,"long_name","spectral cofficients SPPT")
endif
if (do_shum) then
ierr=NF90_DEF_VAR(ncid,"shum_seed",NF90_DOUBLE,(/seed_dim_id, np_dim_id/), varid2a)
ierr=NF90_PUT_ATT(ncid,varid2a,"long_name","random number seed for SHUM")
ierr=NF90_DEF_VAR(ncid,"shum_spec",NF90_DOUBLE,(/spec_dim_id, np_dim_id/), varid2b)
ierr=NF90_PUT_ATT(ncid,varid2b,"long_name","spectral cofficients SHUM")
endif
if (do_skeb) then
ierr=NF90_DEF_DIM(ncid,"skeblevs",skeblevs,zt_dim_id)
ierr=NF90_PUT_ATT(ncid,zt_dim_id,"long_name","number of vertical levels for SKEB")
ierr=NF90_DEF_VAR(ncid,"skeb_seed",NF90_DOUBLE,(/seed_dim_id, zt_dim_id,np_dim_id/), varid3a)
ierr=NF90_PUT_ATT(ncid,varid3a,"long_name","random number seed for SKEB")
ierr=NF90_DEF_VAR(ncid,"skeb_spec",NF90_DOUBLE,(/spec_dim_id, zt_dim_id,np_dim_id/), varid3b)
ierr=NF90_PUT_ATT(ncid,varid3b,"long_name","spectral cofficients SKEB")
endif
if (nlndp>0) then
ierr=NF90_DEF_VAR(ncid,"sfcpert_seed",NF90_DOUBLE,(/seed_dim_id, ztsfc_dim_id, npsfc_dim_id/), varid4a)
ierr=NF90_PUT_ATT(ncid,varid4a,"long_name","random number seed for SHUM")
ierr=NF90_DEF_VAR(ncid,"sfcpert_spec",NF90_DOUBLE,(/spec_dim_id, ztsfc_dim_id, npsfc_dim_id/), varid4b)
ierr=NF90_PUT_ATT(ncid,varid4b,"long_name","spectral cofficients SHUM")
endif
if (nspp>0) then
ierr=NF90_DEF_VAR(ncid,"spp_seed",NF90_DOUBLE,(/seed_dim_id, ztspp_dim_id, npspp_dim_id/), varid5a)
ierr=NF90_PUT_ATT(ncid,varid5a,"long_name","random number seed for SPP")
ierr=NF90_DEF_VAR(ncid,"spp_spec",NF90_DOUBLE,(/spec_dim_id, ztspp_dim_id, npspp_dim_id/), varid5b)
ierr=NF90_PUT_ATT(ncid,varid5b,"long_name","spectral cofficients SPP")
endif
ierr=NF90_ENDDEF(ncid)
if (ierr .NE. 0) then
write(0,*) 'error creating stochastic restart file'
return
end if
endif
endif
if (nsppt > 0) then
do n=1,nsppt
call write_pattern(rpattern_sppt(n),ncid,1,n,varid1a,varid1b,.false.,ierr)
enddo
endif
if (nshum > 0) then
do n=1,nshum
call write_pattern(rpattern_shum(n),ncid,1,n,varid2a,varid2b,.false.,ierr)
enddo
endif
if (nskeb > 0) then
do n=1,nskeb
do k=1,skeblevs
call write_pattern(rpattern_skeb(n),ncid,k,n,varid3a,varid3b,.true.,ierr)
enddo
enddo
endif
if (lndp_type .NE. 0 .AND. nlndp>0) then
do n=1,nlndp
do k=1,n_var_lndp
call write_pattern(rpattern_sfc(n),ncid,k,n,varid4a,varid4b,.true.,ierr)
enddo
enddo
endif
if (nspp > 0) then
do n=1,nspp
call write_pattern(rpattern_spp(n),ncid,1,n,varid5a,varid5b,.true.,ierr)
enddo
endif
if (is_rootpe() ) then
ierr=NF90_CLOSE(ncid)
if (ierr .NE. 0) then
write(0,*) 'error writing patterns and closing file'
return
endif
endif
end subroutine write_stoch_restart_atm
!>@brief The subroutine 'write_stoch_restart_ocn' writes out the speherical harmonics to a file, controlled by restart_interval
!>@details Only the active patterns are written out
subroutine write_stoch_restart_ocn(sfile)
!\callgraph
use netcdf
use stochy_namelist_def, only : do_ocnsppt,pert_epbl
implicit none
character(len=*) :: sfile
integer :: stochlun,k,n,isize,ierr
integer :: ncid,varid1a,varid1b,varid2a,varid2b,varid3a,varid3b
integer :: seed_dim_id,spec_dim_id,np_dim_id
include 'netcdf.inc'
if ( ( .NOT. do_ocnsppt) .AND. (.NOT. pert_epbl) ) return
stochlun=99
if (is_rootpe()) then
ierr=nf90_create(trim(sfile),cmode=NF90_CLOBBER,ncid=ncid)
ierr=NF90_PUT_ATT(ncid,NF_GLOBAL,"ntrunc",ntrunc)
call random_seed(size=isize) ! get seed size
ierr=NF90_DEF_DIM(ncid,"len_seed",isize,seed_dim_id)
ierr=NF90_PUT_ATT(ncid,seed_dim_id,"long_name","length of random seed")
ierr=NF90_DEF_DIM(ncid,"num_patterns",NF_UNLIMITED,np_dim_id) ! should be 5
ierr=NF90_PUT_ATT(ncid,np_dim_id,"long_name","number of random patterns (max of 5)")
ierr=NF90_DEF_DIM(ncid,"ndimspecx2",2*ndimspec,spec_dim_id)
ierr=NF90_PUT_ATT(ncid,spec_dim_id,"long_name","number of spectral cofficients")
if (do_ocnsppt) then
ierr=NF90_DEF_VAR(ncid,"ocnsppt_seed",NF90_DOUBLE,(/seed_dim_id, np_dim_id/), varid1a)
ierr=NF90_PUT_ATT(ncid,varid1a,"long_name","random number seed for SPPT")
ierr=NF90_DEF_VAR(ncid,"ocnsppt_spec",NF90_DOUBLE,(/spec_dim_id, np_dim_id/), varid1b)
ierr=NF90_PUT_ATT(ncid,varid1b,"long_name","spectral cofficients SPPT")
endif
if (pert_epbl) then
ierr=NF90_DEF_VAR(ncid,"epbl1_seed",NF90_DOUBLE,(/seed_dim_id, np_dim_id/), varid2a)
ierr=NF90_PUT_ATT(ncid,varid2a,"long_name","random number seed for EPBL1")
ierr=NF90_DEF_VAR(ncid,"epbl1_spec",NF90_DOUBLE,(/spec_dim_id, np_dim_id/), varid2b)
ierr=NF90_PUT_ATT(ncid,varid2b,"long_name","spectral cofficients EPBL1")
ierr=NF90_DEF_VAR(ncid,"epbl2_seed",NF90_DOUBLE,(/seed_dim_id, np_dim_id/), varid3a)
ierr=NF90_PUT_ATT(ncid,varid3a,"long_name","random number seed for EPBL2")
ierr=NF90_DEF_VAR(ncid,"epbl2_spec",NF90_DOUBLE,(/spec_dim_id, np_dim_id/), varid3b)
ierr=NF90_PUT_ATT(ncid,varid3b,"long_name","spectral cofficients EPBL2")
endif
ierr=NF90_ENDDEF(ncid)
if (ierr .NE. 0) then
write(0,*) 'error creating stochastic restart file'
return
end if
endif
if (nocnsppt > 0) then
do n=1,nocnsppt
call write_pattern(rpattern_ocnsppt(n),ncid,1,n,varid1a,varid1b,.false.,ierr)
enddo
endif
if (nepbl > 0) then
do n=1,nepbl
call write_pattern(rpattern_epbl1(n),ncid,1,n,varid2a,varid2b,.false.,ierr)
call write_pattern(rpattern_epbl2(n),ncid,1,n,varid3a,varid3b,.false.,ierr)
enddo
endif
if (is_rootpe() ) then
ierr=NF90_CLOSE(ncid)
if (ierr .NE. 0) then
write(0,*) 'error writing patterns and closing file'
return
endif
endif
end subroutine write_stoch_restart_ocn
!>@brief The subroutine 'write_patterns' writes out a single pattern and the seed associated with the random number sequence
!>@details Spherical harminoncs are stored with trianglular truncation
subroutine write_pattern(rpattern,outlun,lev,np,varid1,varid2,slice_of_3d,iret)
!\callgraph
use netcdf
implicit none
type(random_pattern), intent(inout) :: rpattern
integer, intent(in) :: outlun,lev
integer, intent(in) :: np,varid1,varid2
logical, intent(in) :: slice_of_3d
integer, intent(out) :: iret
real(kind_phys), allocatable :: pattern2d(:)
integer nm,nn,arrlen,isize,ierr
integer,allocatable :: isave(:)
include 'netcdf.inc'
arrlen=2*ndimspec
iret=0
allocate(pattern2d(arrlen))
pattern2d=0.0
! fill in apprpriate pieces of array
do nn=1,len_trie_ls
nm = rpattern%idx_e(nn)
if (nm == 0) cycle
pattern2d(nm) = rpattern%spec_e(nn,1,lev)
pattern2d(ndimspec+nm) = rpattern%spec_e(nn,2,lev)
enddo
do nn=1,len_trio_ls
nm = rpattern%idx_o(nn)
if (nm == 0) cycle
pattern2d(nm) = rpattern%spec_o(nn,1,lev)
pattern2d(ndimspec+nm) = rpattern%spec_o(nn,2,lev)
enddo
call mp_reduce_sum(pattern2d,arrlen)
! write only on root process
if (is_rootpe()) then
print*,'writing out random pattern (min/max/size)',&
minval(pattern2d),maxval(pattern2d),size(pattern2d)
call random_seed(size=isize) ! get seed size
allocate(isave(isize)) ! get seed
call random_seed(get=isave,stat=rpattern%rstate) ! write seed
ierr=NF90_PUT_VAR(outlun,varid1,isave,(/1,np/))
if (slice_of_3d) then
ierr=NF90_PUT_VAR(outlun,varid2,pattern2d,(/1,lev,np/))
else
ierr=NF90_PUT_VAR(outlun,varid2,pattern2d,(/1,np/))
endif
if (ierr .NE. 0) then
write(0,*) 'error writing to stochastic restart file'
iret = ierr
return
end if
endif
deallocate(pattern2d)
end subroutine write_pattern
!>@brief The subroutine 'vrtdivspect_to_uvgrid' converts vorticty and divergence spherical harmonics to
! zonal and meridional winds on the gaussian grid
!>@details This subroutine is for a 2-D (lat-lon) vector field
subroutine vrtdivspect_to_uvgrid(&
trie_di,trio_di,trie_ze,trio_ze,&
uug,vvg, gis_stochy)
!\callgraph
implicit none
type(stochy_internal_state), intent(in) :: gis_stochy
real(kind=kind_dbl_prec), intent(in) :: trie_di(len_trie_ls,2)
real(kind=kind_dbl_prec), intent(in) :: trio_di(len_trio_ls,2)
real(kind=kind_dbl_prec), intent(in) :: trie_ze(len_trie_ls,2)
real(kind=kind_dbl_prec), intent(in) :: trio_ze(len_trio_ls,2)
real(kind=kind_phys), intent(out) :: uug(lonf,gis_stochy%lats_node_a)
real(kind=kind_phys), intent(out) :: vvg(lonf,gis_stochy%lats_node_a)
! local vars
real(kind=kind_dbl_prec) trie_ls(len_trie_ls,2,2)
real(kind=kind_dbl_prec) trio_ls(len_trio_ls,2,2)
real(kind=kind_dbl_prec) for_gr_a_1(gis_stochy%lon_dim_a,2,gis_stochy%lats_dim_a)
real(kind=kind_dbl_prec) for_gr_a_2(lonf,2,gis_stochy%lats_dim_a)
integer i,k
integer lan,lat
real (kind=kind_phys) tx1
call dezouv_stochy(trie_di(:,:), trio_ze(:,:), &
trie_ls(:,:,1), trio_ls(:,:,2), gis_stochy%epsedn,gis_stochy%epsodn, &
gis_stochy%snnp1ev,gis_stochy%snnp1od,gis_stochy%ls_node)
call dozeuv_stochy(trio_di(:,:), trie_ze(:,:), &
trio_ls(:,:,1), trie_ls(:,:,2), gis_stochy%epsedn,gis_stochy%epsodn, &
gis_stochy%snnp1ev,gis_stochy%snnp1od,gis_stochy%ls_node)
call spec_to_four(trie_ls, trio_ls, &
gis_stochy%plnev_a,gis_stochy%plnod_a,&
gis_stochy%ls_node,&
gis_stochy%lats_dim_a,for_gr_a_1,&
gis_stochy%ls_nodes,gis_stochy%max_ls_nodes,&
gis_stochy%lats_nodes_a,gis_stochy%global_lats_a,&
gis_stochy%lats_node_a,gis_stochy%ipt_lats_node_a,2)
do lan=1,gis_stochy%lats_node_a
lat = gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+lan)
call four_to_grid(for_gr_a_1(:,:,lan),for_gr_a_2(:,:,lan),&
gis_stochy%lon_dim_a,2)
enddo
uug = 0.; vvg = 0.
do lan=1,gis_stochy%lats_node_a
lat = gis_stochy%global_lats_a(gis_stochy%ipt_lats_node_a-1+lan)
tx1 = 1. / coslat_a(lat)
do i=1,lonf
uug(i,lan) = for_gr_a_2(i,1,lan) * tx1
vvg(i,lan) = for_gr_a_2(i,2,lan) * tx1
enddo
enddo
return
end subroutine vrtdivspect_to_uvgrid
end module get_stochy_pattern_mod