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stochy_data_mod.F90
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stochy_data_mod.F90
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!>@brief The module 'stochy_data_mod' contains the initilization routine that read the stochastic phyiscs
!! namelist and determins the number of random patterns.
module stochy_data_mod
! set up and initialize stochastic random patterns.
use spectral_layout_mod, only: len_trie_ls,len_trio_ls,ls_dim,ls_max_node,&
skeblevs,levs,jcap,lonf,latg
use stochy_namelist_def
use constants_mod, only : radius
use spectral_layout_mod, only : me, nodes
use mpi_wrapper, only: mp_bcst, is_master
use stochy_patterngenerator_mod, only: random_pattern, patterngenerator_init,&
getnoise, patterngenerator_advance,ndimspec,chgres_pattern,computevarspec_r
use initialize_spectral_mod, only: initialize_spectral
use stochy_internal_state_mod
! use mersenne_twister_stochy, only : random_seed
use mersenne_twister, only : random_seed
use compns_stochy_mod, only : compns_stochy
implicit none
private
public :: init_stochdata,init_stochdata_ocn
type(random_pattern), public, save, allocatable, dimension(:) :: &
rpattern_sppt,rpattern_shum,rpattern_skeb, rpattern_sfc,rpattern_epbl1,rpattern_epbl2,rpattern_ocnsppt
integer, public :: nepbl=0
integer, public :: nocnsppt=0
integer, public :: nsppt=0
integer, public :: nshum=0
integer, public :: nskeb=0
integer, public :: nlndp=0 ! this is the number of different patterns (determined by the tau/lscale input)
real*8, public,allocatable :: sl(:)
real(kind=kind_dbl_prec),public, allocatable :: vfact_sppt(:),vfact_shum(:),vfact_skeb(:)
real(kind=kind_dbl_prec),public, allocatable :: skeb_vwts(:,:),skeb_vpts(:,:)
real(kind=kind_dbl_prec),public, allocatable :: gg_lats(:),gg_lons(:)
real(kind=kind_dbl_prec),public :: wlon,rnlat,rad2deg
real(kind=kind_dbl_prec),public, allocatable :: skebu_save(:,:,:),skebv_save(:,:,:)
integer,public :: INTTYP
type(stochy_internal_state),public :: gis_stochy,gis_stochy_ocn
contains
!>@brief The subroutine 'init_stochdata' determins which stochastic physics
!!pattern genertors are needed.
!>@details it reads the nam_stochy namelist and allocates necessary arrays
subroutine init_stochdata(nlevs,delt,input_nml_file,fn_nml,nlunit,iret)
!\callgraph
! initialize random patterns. A spinup period of spinup_efolds times the
! temporal time scale is run for each pattern.
use netcdf
implicit none
integer, intent(in) :: nlunit,nlevs
character(len=*), intent(in) :: input_nml_file(:)
character(len=64), intent(in) :: fn_nml
real, intent(in) :: delt
integer, intent(out) :: iret
real :: ones(5)
real :: rnn1
integer :: nn,nspinup,k,nm,spinup_efolds,stochlun,ierr,n
integer :: locl,indev,indod,indlsod,indlsev
integer :: l,jbasev,jbasod
integer :: jcapin,varid1,varid2
real(kind_dbl_prec),allocatable :: noise_e(:,:),noise_o(:,:)
include 'function_indlsod'
include 'function_indlsev'
include 'netcdf.inc'
stochlun=99
levs=nlevs
iret=0
! read in namelist
call compns_stochy (me,size(input_nml_file,1),input_nml_file(:),fn_nml,nlunit,delt,iret)
if (iret/=0) return ! need to make sure that non-zero irets are being trapped.
if(is_master()) print*,'in init stochdata',nodes,lat_s
if ( (.NOT. do_sppt) .AND. (.NOT. do_shum) .AND. (.NOT. do_skeb) .AND. (lndp_type==0) ) return
! initialize the specratl pattern generatore (including gaussian grid decomposition)
! if (nodes.GE.lat_s/2) then
! lat_s=(int(nodes/12)+1)*24
! lon_s=lat_s*2
! ntrunc=lat_s-2
! if (is_master()) print*,'WARNING: spectral resolution is too low for number of mpi_tasks, resetting lon_s,lat_s,and ntrunc to',lon_s,lat_s,ntrunc
! endif
call initialize_spectral(gis_stochy, iret)
if (iret/=0) return
allocate(noise_e(len_trie_ls,2),noise_o(len_trio_ls,2))
! determine number of random patterns to be used for each scheme.
do n=1,size(sppt)
if (sppt(n) > 0) then
nsppt=nsppt+1
else
exit
endif
enddo
if (is_master()) print *,'nsppt = ',nsppt
do n=1,size(shum)
if (shum(n) > 0) then
nshum=nshum+1
else
exit
endif
enddo
if (is_master()) print *,'nshum = ',nshum
do n=1,size(skeb)
if (skeb(n) > 0) then
nskeb=nskeb+1
else
exit
endif
enddo
if (is_master()) print *,'nskeb = ',nskeb
! Draper: nlndp>1 was not properly coded. Hardcode to 1 for now
!do n=1,size(lndp_z0)
! if (lndp_z0(n) > 0 .or. lndp_zt(n)>0 .or. lndp_hc(n)>0 .or. &
! lndp_vf(n)>0 .or. lndp_la(n)>0 .or. lndp_al(n)>0) then
! nlndp=nlndp+1
! else
! exit
! endif
!enddo
if (n_var_lndp>0) nlndp=1
if (is_master()) print *,' nlndp = ', nlndp
if (nsppt > 0) allocate(rpattern_sppt(nsppt))
if (nshum > 0) allocate(rpattern_shum(nshum))
if (nskeb > 0) allocate(rpattern_skeb(nskeb))
! mg, sfc perts
if (nlndp > 0) allocate(rpattern_sfc(nlndp))
! if stochini is true, then read in pattern from a file
if (is_master()) then
if (stochini) then
print*,'opening stoch_ini'
!OPEN(stochlun,file='INPUT/atm_stoch.res.bin',form='unformatted',iostat=ierr,status='old')
ierr=nf90_open('INPUT/atm_stoch.res.nc',nf90_nowrite,ncid=stochlun)
if (ierr .NE. 0) then
write(0,*) 'error opening stoch_ini'
iret = ierr
return
end if
ierr=NF90_GET_ATT(stochlun,NF_GLOBAL,"ntrunc",jcapin)
if (ierr .NE. 0) then
write(0,*) 'error getting ntrunc'
iret = ierr
return
end if
print*,'ntrunc read in',jcapin
endif
endif
! no spinup needed if initial patterns are defined correctly.
spinup_efolds = 0
if (nsppt > 0) then
if (is_master()) then
print *, 'Initialize random pattern for SPPT'
if (stochini) then
ierr=NF90_INQ_VARID(stochlun,"sppt_seed", varid1)
if (ierr .NE. 0) then
write(0,*) 'error inquring SPPT seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"sppt_spec", varid2)
if (ierr .NE. 0) then
write(0,*) 'error inquring SPPT spec'
iret = ierr
return
end if
endif
endif
call patterngenerator_init(sppt_lscale(1:nsppt),spptint,sppt_tau(1:nsppt),sppt(1:nsppt),iseed_sppt,rpattern_sppt, &
lonf,latg,jcap,gis_stochy%ls_node,nsppt,1,0,new_lscale)
do n=1,nsppt
nspinup = spinup_efolds*sppt_tau(n)/spptint
if (stochini) then
call read_pattern(rpattern_sppt(n),jcapin,stochlun,1,n,varid1,varid2,.false.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading SPPT pattern'
iret = ierr
return
end if
else
call getnoise(rpattern_sppt(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_sppt(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_sppt(n)%spec_e(nn,2,1)=noise_e(nn,2)
nm = rpattern_sppt(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_sppt(n)%spec_e(nn,1,1) = rpattern_sppt(n)%stdev*rpattern_sppt(n)%spec_e(nn,1,1)*rpattern_sppt(n)%varspectrum(nm)
rpattern_sppt(n)%spec_e(nn,2,1) = rpattern_sppt(n)%stdev*rpattern_sppt(n)%spec_e(nn,2,1)*rpattern_sppt(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_sppt(n)%spec_o(nn,1,1)=noise_o(nn,1)
rpattern_sppt(n)%spec_o(nn,2,1)=noise_o(nn,2)
nm = rpattern_sppt(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_sppt(n)%spec_o(nn,1,1) = rpattern_sppt(n)%stdev*rpattern_sppt(n)%spec_o(nn,1,1)*rpattern_sppt(n)%varspectrum(nm)
rpattern_sppt(n)%spec_o(nn,2,1) = rpattern_sppt(n)%stdev*rpattern_sppt(n)%spec_o(nn,2,1)*rpattern_sppt(n)%varspectrum(nm)
enddo
do nn=1,nspinup
call patterngenerator_advance(rpattern_sppt(n),1,.false.)
enddo
endif
enddo
endif
if (nshum > 0) then
if (is_master()) then
print *, 'Initialize random pattern for SHUM'
if (stochini) then
ierr=NF90_INQ_VARID(stochlun,"shum_seed", varid1)
if (ierr .NE. 0) then
write(0,*) 'error inquring SHUM seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"shum_spec", varid2)
if (ierr .NE. 0) then
write(0,*) 'error inquring SHUM spec'
iret = ierr
return
end if
endif
endif
call patterngenerator_init(shum_lscale(1:nshum),shumint,shum_tau(1:nshum),shum(1:nshum),iseed_shum,rpattern_shum, &
lonf,latg,jcap,gis_stochy%ls_node,nshum,1,0,new_lscale)
do n=1,nshum
nspinup = spinup_efolds*shum_tau(n)/shumint
if (stochini) then
call read_pattern(rpattern_shum(n),jcapin,stochlun,1,n,varid1,varid2,.false.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading SHUM pattern'
iret = ierr
return
end if
else
call getnoise(rpattern_shum(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_shum(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_shum(n)%spec_e(nn,2,1)=noise_e(nn,2)
nm = rpattern_shum(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_shum(n)%spec_e(nn,1,1) = rpattern_shum(n)%stdev*rpattern_shum(n)%spec_e(nn,1,1)*rpattern_shum(n)%varspectrum(nm)
rpattern_shum(n)%spec_e(nn,2,1) = rpattern_shum(n)%stdev*rpattern_shum(n)%spec_e(nn,2,1)*rpattern_shum(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_shum(n)%spec_o(nn,1,1)=noise_o(nn,1)
rpattern_shum(n)%spec_o(nn,2,1)=noise_o(nn,2)
nm = rpattern_shum(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_shum(n)%spec_o(nn,1,1) = rpattern_shum(n)%stdev*rpattern_shum(n)%spec_o(nn,1,1)*rpattern_shum(n)%varspectrum(nm)
rpattern_shum(n)%spec_o(nn,2,1) = rpattern_shum(n)%stdev*rpattern_shum(n)%spec_o(nn,2,1)*rpattern_shum(n)%varspectrum(nm)
enddo
do nn=1,nspinup
call patterngenerator_advance(rpattern_shum(n),1,.false.)
enddo
endif
enddo
endif
if (nskeb > 0) then
! determine number of skeb levels to deal with temperoal/vertical correlations
skeblevs=nint(skeb_tau(1)/skebint*skeb_vdof)
! backscatter noise.
if (is_master()) then
print *, 'Initialize random pattern for SKEB'
if (stochini) then
ierr=NF90_INQ_VARID(stochlun,"skeb_seed", varid1)
if (ierr .NE. 0) then
write(0,*) 'error inquring SKEB seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"skeb_spec", varid2)
if (ierr .NE. 0) then
write(0,*) 'error inquring SKEB spec'
iret = ierr
return
end if
endif
endif
call patterngenerator_init(skeb_lscale(1:nskeb),skebint,skeb_tau(1:nskeb),skeb(1:nskeb),iseed_skeb,rpattern_skeb, &
lonf,latg,jcap,gis_stochy%ls_node,nskeb,skeblevs,skeb_varspect_opt,new_lscale)
do n=1,nskeb
do k=1,skeblevs
nspinup = spinup_efolds*skeb_tau(n)/skebint
if (stochini) then
call read_pattern(rpattern_skeb(n),jcapin,stochlun,k,n,varid1,varid2,.true.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading SKEB pattern'
iret = ierr
return
end if
else
call getnoise(rpattern_skeb(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_skeb(n)%spec_e(nn,1,k)=noise_e(nn,1)
rpattern_skeb(n)%spec_e(nn,2,k)=noise_e(nn,2)
nm = rpattern_skeb(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_skeb(n)%spec_e(nn,1,k) = rpattern_skeb(n)%stdev*rpattern_skeb(n)%spec_e(nn,1,k)*rpattern_skeb(n)%varspectrum(nm)
rpattern_skeb(n)%spec_e(nn,2,k) = rpattern_skeb(n)%stdev*rpattern_skeb(n)%spec_e(nn,2,k)*rpattern_skeb(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_skeb(n)%spec_o(nn,1,k)=noise_o(nn,1)
rpattern_skeb(n)%spec_o(nn,2,k)=noise_o(nn,2)
nm = rpattern_skeb(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_skeb(n)%spec_o(nn,1,k) = rpattern_skeb(n)%stdev*rpattern_skeb(n)%spec_o(nn,1,k)*rpattern_skeb(n)%varspectrum(nm)
rpattern_skeb(n)%spec_o(nn,2,k) = rpattern_skeb(n)%stdev*rpattern_skeb(n)%spec_o(nn,2,k)*rpattern_skeb(n)%varspectrum(nm)
enddo
endif
enddo
do nn=1,nspinup
call patterngenerator_advance(rpattern_skeb(n),skeblevs,.false.)
enddo
enddo
gis_stochy%kenorm_e=1.
gis_stochy%kenorm_o=1. ! used to convert forcing pattern to wind field.
if (skebnorm==0) then
do locl=1,ls_max_node
l = gis_stochy%ls_node(locl)
jbasev = gis_stochy%ls_node(locl+ls_dim)
indev = indlsev(l,l)
jbasod = gis_stochy%ls_node(locl+2*ls_dim)
indod = indlsod(l+1,l)
do n=l,jcap,2
rnn1 = n*(n+1.)
gis_stochy%kenorm_e(indev) = rnn1/radius**2
indev = indev + 1
enddo
do n=l+1,jcap,2
rnn1 = n*(n+1.)
gis_stochy%kenorm_o(indod) = rnn1/radius**2
indod = indod + 1
enddo
enddo
if (is_master()) print*,'using streamfunction ',maxval(gis_stochy%kenorm_e(:)),minval(gis_stochy%kenorm_e(:))
endif
if (skebnorm==1) then
do locl=1,ls_max_node
l = gis_stochy%ls_node(locl)
jbasev = gis_stochy%ls_node(locl+ls_dim)
indev = indlsev(l,l)
jbasod = gis_stochy%ls_node(locl+2*ls_dim)
indod = indlsod(l+1,l)
do n=l,jcap,2
rnn1 = n*(n+1.)
gis_stochy%kenorm_e(indev) = sqrt(rnn1)/radius
indev = indev + 1
enddo
do n=l+1,jcap,2
rnn1 = n*(n+1.)
gis_stochy%kenorm_o(indod) = sqrt(rnn1)/radius
indod = indod + 1
enddo
enddo
if (is_master()) print*,'using kenorm ',maxval(gis_stochy%kenorm_e(:)),minval(gis_stochy%kenorm_e(:))
endif
! set the even and odd (n-l) terms of the top row to zero
do locl=1,ls_max_node
l = gis_stochy%ls_node(locl)
jbasev = gis_stochy%ls_node(locl+ls_dim)
jbasod = gis_stochy%ls_node(locl+2*ls_dim)
if (mod(l,2) .eq. mod(jcap+1,2)) then
gis_stochy%kenorm_e(indlsev(jcap+1,l)) = 0.
endif
if (mod(l,2) .ne. mod(jcap+1,2)) then
gis_stochy%kenorm_o(indlsod(jcap+1,l)) = 0.
endif
enddo
endif ! skeb > 0
! mg, sfc-perts
if (nlndp > 0) then
if (is_master()) then
print *, 'Initialize random pattern for SFC-PERTS'
if (stochini) then
ierr=NF90_INQ_VARID(stochlun,"sfcpert_seed", varid1)
if (ierr .NE. 0) then
write(0,*) 'error inquring SFC-PERTS seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"sfcpert_spec", varid2)
if (ierr .NE. 0) then
write(0,*) 'error inquring SFC-PERTS spec'
iret = ierr
return
end if
endif
endif
ones = 1.
call patterngenerator_init(lndp_lscale(1:nlndp),delt,lndp_tau(1:nlndp),ones(1:nlndp),iseed_lndp,rpattern_sfc, &
lonf,latg,jcap,gis_stochy%ls_node,nlndp,n_var_lndp,0,new_lscale)
do n=1,nlndp
if (is_master()) print *, 'Initialize random pattern for LNDP PERTS'
do k=1,n_var_lndp
nspinup = spinup_efolds*lndp_tau(n)/delt
if (stochini) then
call read_pattern(rpattern_sfc(n),jcapin,stochlun,k,n,varid1,varid2,.true.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading SHUM pattern'
iret = ierr
return
endif
if (is_master()) print *, 'lndp pattern read',n,k,minval(rpattern_sfc(n)%spec_o(:,:,k)), maxval(rpattern_sfc(n)%spec_o(:,:,k))
else
call getnoise(rpattern_sfc(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_sfc(n)%spec_e(nn,1,k)=noise_e(nn,1)
rpattern_sfc(n)%spec_e(nn,2,k)=noise_e(nn,2)
nm = rpattern_sfc(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_sfc(n)%spec_e(nn,1,k) = rpattern_sfc(n)%stdev*rpattern_sfc(n)%spec_e(nn,1,k)*rpattern_sfc(n)%varspectrum(nm)
rpattern_sfc(n)%spec_e(nn,2,k) = rpattern_sfc(n)%stdev*rpattern_sfc(n)%spec_e(nn,2,k)*rpattern_sfc(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_sfc(n)%spec_o(nn,1,k)=noise_o(nn,1)
rpattern_sfc(n)%spec_o(nn,2,k)=noise_o(nn,2)
nm = rpattern_sfc(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_sfc(n)%spec_o(nn,1,k) = rpattern_sfc(n)%stdev*rpattern_sfc(n)%spec_o(nn,1,k)*rpattern_sfc(n)%varspectrum(nm)
rpattern_sfc(n)%spec_o(nn,2,k) = rpattern_sfc(n)%stdev*rpattern_sfc(n)%spec_o(nn,2,k)*rpattern_sfc(n)%varspectrum(nm)
enddo
do nn=1,nspinup
call patterngenerator_advance(rpattern_sfc(n),k,.false.)
enddo
if (is_master()) print *, 'lndp pattern initialized, ',n, k, minval(rpattern_sfc(n)%spec_o(:,:,k)), maxval(rpattern_sfc(n)%spec_o(:,:,k))
endif ! stochini
enddo ! k, n_var_lndp
enddo ! n, nlndp
endif ! nlndp > 0
if (is_master() .and. stochini) CLOSE(stochlun)
deallocate(noise_e,noise_o)
end subroutine init_stochdata
subroutine init_stochdata_ocn(nlevs,delt,iret)
use netcdf
use compns_stochy_mod, only : compns_stochy_ocn
use mpp_domains_mod, only: mpp_broadcast_domain,MPP_DOMAIN_TIME,mpp_domains_init ,mpp_domains_set_stack_size
! initialize random patterns. A spinup period of spinup_efolds times the
! temporal time scale is run for each pattern.
integer, intent(in) :: nlevs
real, intent(in) :: delt
integer, intent(out) :: iret
integer :: nn,nm,stochlun,n,jcapin
integer :: l,jbasev,jbasod
integer :: indev,indod,indlsod,indlsev,varid1,varid2,varid3,varid4,ierr
real(kind_dbl_prec),allocatable :: noise_e(:,:),noise_o(:,:)
include 'function_indlsod'
include 'function_indlsev'
include 'netcdf.inc'
stochlun=99
levs=nlevs
iret=0
call compns_stochy_ocn (delt,iret)
if(is_master()) print*,'in init stochdata_ocn'
if ( (.NOT. pert_epbl) .AND. (.NOT. do_ocnsppt) ) return
call initialize_spectral(gis_stochy_ocn, iret)
if (iret/=0) return
allocate(noise_e(len_trie_ls,2),noise_o(len_trio_ls,2))
! determine number of random patterns to be used for each scheme.
do n=1,size(epbl)
if (epbl(n) > 0) then
nepbl=nepbl+1
else
exit
endif
enddo
do n=1,size(ocnsppt)
if (ocnsppt(n) > 0) then
nocnsppt=nocnsppt+1
else
exit
endif
enddo
if (nepbl > 0) then
allocate(rpattern_epbl1(nepbl))
allocate(rpattern_epbl2(nepbl))
endif
if (nocnsppt > 0) allocate(rpattern_ocnsppt(nocnsppt))
! if stochini is true, then read in pattern from a file
if (is_master()) then
if (stochini) then
print*,'opening stoch_ini'
ierr=nf90_open('INPUT/ocn_stoch.res.nc',nf90_nowrite,ncid=stochlun)
if (ierr .NE. 0) then
write(0,*) 'error opening stoch_ini'
iret = ierr
return
end if
ierr=NF90_GET_ATT(stochlun,NF_GLOBAL,"ntrunc",jcapin)
if (ierr .NE. 0) then
write(0,*) 'error getting ntrunc'
iret = ierr
return
end if
print*,'ntrunc read in',jcapin
endif
endif
if (nepbl > 0) then
if (is_master()) then
print *, 'Initialize random pattern for epbl'
if (stochini) then
ierr=NF90_INQ_VARID(stochlun,"epbl1_seed", varid1)
if (ierr .NE. 0) then
write(0,*) 'error inquring EPBL1 seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"epbl1_spec", varid2)
if (ierr .NE. 0) then
write(0,*) 'error inquring EPBL1 spec'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"epbl2_seed", varid3)
if (ierr .NE. 0) then
write(0,*) 'error inquring EPBL2 seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"epbl2_spec", varid4)
if (ierr .NE. 0) then
write(0,*) 'error inquring EPBL2 spec'
iret = ierr
return
end if
end if
end if
call patterngenerator_init(epbl_lscale(1:nepbl),epblint,epbl_tau(1:nepbl),epbl(1:nepbl),iseed_epbl,rpattern_epbl1, &
lonf,latg,jcap,gis_stochy_ocn%ls_node,nepbl,1,0,new_lscale)
call patterngenerator_init(epbl_lscale(1:nepbl),epblint,epbl_tau(1:nepbl),epbl(1:nepbl),iseed_epbl2,rpattern_epbl2, &
lonf,latg,jcap,gis_stochy_ocn%ls_node,nepbl,1,0,new_lscale)
do n=1,nepbl
if (stochini) then
call read_pattern(rpattern_epbl1(n),jcapin,stochlun,1,n,varid1,varid2,.false.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading EPBL1 pattern'
iret = ierr
return
end if
call read_pattern(rpattern_epbl2(n),jcapin,stochlun,1,n,varid3,varid4,.false.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading EPBL1 pattern'
iret = ierr
return
end if
else
call getnoise(rpattern_epbl1(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_epbl1(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_epbl1(n)%spec_e(nn,2,1)=noise_e(nn,2)
rpattern_epbl1(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_epbl1(n)%spec_e(nn,2,1)=noise_e(nn,2)
nm = rpattern_epbl1(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_epbl1(n)%spec_e(nn,1,1) = rpattern_epbl1(n)%stdev*rpattern_epbl1(n)%spec_e(nn,1,1)*rpattern_epbl1(n)%varspectrum(nm)
rpattern_epbl1(n)%spec_e(nn,2,1) = rpattern_epbl1(n)%stdev*rpattern_epbl1(n)%spec_e(nn,2,1)*rpattern_epbl1(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_epbl1(n)%spec_o(nn,1,1)=noise_o(nn,1)
rpattern_epbl1(n)%spec_o(nn,2,1)=noise_o(nn,2)
nm = rpattern_epbl1(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_epbl1(n)%spec_o(nn,1,1) = rpattern_epbl1(n)%stdev*rpattern_epbl1(n)%spec_o(nn,1,1)*rpattern_epbl1(n)%varspectrum(nm)
rpattern_epbl1(n)%spec_o(nn,2,1) = rpattern_epbl1(n)%stdev*rpattern_epbl1(n)%spec_o(nn,2,1)*rpattern_epbl1(n)%varspectrum(nm)
enddo
call patterngenerator_advance(rpattern_epbl1(n),1,.false.)
call getnoise(rpattern_epbl2(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_epbl2(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_epbl2(n)%spec_e(nn,2,1)=noise_e(nn,2)
rpattern_epbl2(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_epbl2(n)%spec_e(nn,2,1)=noise_e(nn,2)
nm = rpattern_epbl2(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_epbl2(n)%spec_e(nn,1,1) = rpattern_epbl2(n)%stdev*rpattern_epbl2(n)%spec_e(nn,1,1)*rpattern_epbl2(n)%varspectrum(nm)
rpattern_epbl2(n)%spec_e(nn,2,1) = rpattern_epbl2(n)%stdev*rpattern_epbl2(n)%spec_e(nn,2,1)*rpattern_epbl2(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_epbl2(n)%spec_o(nn,1,1)=noise_o(nn,1)
rpattern_epbl2(n)%spec_o(nn,2,1)=noise_o(nn,2)
nm = rpattern_epbl2(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_epbl2(n)%spec_o(nn,1,1) = rpattern_epbl2(n)%stdev*rpattern_epbl2(n)%spec_o(nn,1,1)*rpattern_epbl2(n)%varspectrum(nm)
rpattern_epbl2(n)%spec_o(nn,2,1) = rpattern_epbl2(n)%stdev*rpattern_epbl2(n)%spec_o(nn,2,1)*rpattern_epbl2(n)%varspectrum(nm)
enddo
call patterngenerator_advance(rpattern_epbl2(n),1,.false.)
endif
enddo
endif
if (nocnsppt > 0) then
if (is_master()) then
if (stochini) then
ierr=NF90_INQ_VARID(stochlun,"ocnsppt_seed", varid1)
if (ierr .NE. 0) then
write(0,*) 'error inquring OCNSPPT seed'
iret = ierr
return
end if
ierr=NF90_INQ_VARID(stochlun,"ocnsppt_spec", varid2)
if (ierr .NE. 0) then
write(0,*) 'error inquring OCNSPPT spec'
iret = ierr
return
end if
endif
endif
if (is_master()) print *, 'Initialize random pattern for ocnsppt'
call patterngenerator_init(ocnsppt_lscale(1:nocnsppt),ocnspptint,ocnsppt_tau(1:nocnsppt),ocnsppt(1:nocnsppt),iseed_ocnsppt,rpattern_ocnsppt, &
lonf,latg,jcap,gis_stochy_ocn%ls_node,nocnsppt,1,0,new_lscale)
do n=1,nocnsppt
if (stochini) then
call read_pattern(rpattern_ocnsppt(n),jcapin,stochlun,1,n,varid1,varid2,.false.,ierr)
if (ierr .NE. 0) then
write(0,*) 'error reading SPPT pattern'
iret = ierr
return
end if
else
call getnoise(rpattern_ocnsppt(n),noise_e,noise_o)
do nn=1,len_trie_ls
rpattern_ocnsppt(n)%spec_e(nn,1,1)=noise_e(nn,1)
rpattern_ocnsppt(n)%spec_e(nn,2,1)=noise_e(nn,2)
nm = rpattern_ocnsppt(n)%idx_e(nn)
if (nm .eq. 0) cycle
rpattern_ocnsppt(n)%spec_e(nn,1,1) = rpattern_ocnsppt(n)%stdev*rpattern_ocnsppt(n)%spec_e(nn,1,1)*rpattern_ocnsppt(n)%varspectrum(nm)
rpattern_ocnsppt(n)%spec_e(nn,2,1) = rpattern_ocnsppt(n)%stdev*rpattern_ocnsppt(n)%spec_e(nn,2,1)*rpattern_ocnsppt(n)%varspectrum(nm)
enddo
do nn=1,len_trio_ls
rpattern_ocnsppt(n)%spec_o(nn,1,1)=noise_o(nn,1)
rpattern_ocnsppt(n)%spec_o(nn,2,1)=noise_o(nn,2)
nm = rpattern_ocnsppt(n)%idx_o(nn)
if (nm .eq. 0) cycle
rpattern_ocnsppt(n)%spec_o(nn,1,1) = rpattern_ocnsppt(n)%stdev*rpattern_ocnsppt(n)%spec_o(nn,1,1)*rpattern_ocnsppt(n)%varspectrum(nm)
rpattern_ocnsppt(n)%spec_o(nn,2,1) = rpattern_ocnsppt(n)%stdev*rpattern_ocnsppt(n)%spec_o(nn,2,1)*rpattern_ocnsppt(n)%varspectrum(nm)
enddo
call patterngenerator_advance(rpattern_ocnsppt(n),1,.false.)
endif
enddo
endif
deallocate(noise_e,noise_o)
end subroutine init_stochdata_ocn
!>@brief This subroutine 'read_pattern' will read in the spectral coeffients from a previous run (stored in stoch_ini,
!!turned on by setting STOCHINI=.true.)
!>@details Data read in are flat binary, so the number of stochastic physics patterns running must match previous run
subroutine read_pattern(rpattern,jcapin,lunptn,k,np,varid1,varid2,slice_of_3d,iret)
!\callgraph
use netcdf
type(random_pattern), intent(inout) :: rpattern
integer, intent(in) :: lunptn,np,varid1,varid2,jcapin
logical, intent(in) :: slice_of_3d
real(kind_dbl_prec),allocatable :: pattern2d(:),pattern2din(:)
real(kind_dbl_prec) :: stdevin,varin
integer nm,nn,iret,ierr,isize,k,ndimspec2
integer, allocatable :: isave(:)
include 'netcdf.inc'
iret=0
ndimspec2=2*ndimspec
allocate(pattern2d(ndimspec2))
pattern2d=0.
call random_seed(size=isize,stat=rpattern%rstate) ! get size of generator state seed array
allocate(isave(isize))
! read only on root process, and send to all tasks
if (is_master()) then
allocate(pattern2din((jcapin+1)*(jcapin+2)))
print*,'reading in random pattern at ',jcapin,ndimspec,size(pattern2din)
!read(lunptn) pattern2din
ierr=NF90_GET_VAR(lunptn,varid1,isave,(/1,np/))
if (ierr .NE. 0) then
write(0,*) 'error reading seed'
iret = ierr
return
end if
if (slice_of_3d) then
ierr=NF90_GET_VAR(lunptn,varid2,pattern2din,(/1,k,np/),(/ndimspec2,1,1/))
else
ierr=NF90_GET_VAR(lunptn,varid2,pattern2din,(/1,np/),(/ndimspec2,1/))
endif
if (ierr .NE. 0) then
write(0,*) 'error reading spec var'
iret = ierr
return
end if
print*,'reading in random pattern (min/max/size/seed)',&
minval(pattern2din),maxval(pattern2din),size(pattern2din),isave(1:4)
if (jcapin .eq. ntrunc) then
pattern2d=pattern2din
else
call chgres_pattern(pattern2din,pattern2d,jcapin,ntrunc) ! chgres of spectral files
! change the standard deviation of the patterns for a resolution change
! needed for SKEB & SHUM
call computevarspec_r(rpattern,pattern2d,varin)
print*,'stddev in and out..',sqrt(varin),rpattern%stdev
stdevin=rpattern%stdev/sqrt(varin)
pattern2d(:)=pattern2d(:)*stdevin
endif
deallocate(pattern2din)
endif
call mp_bcst(isave,isize) ! blast out seed
call mp_bcst(pattern2d,2*ndimspec)
call random_seed(put=isave,stat=rpattern%rstate)
! subset
do nn=1,len_trie_ls
nm = rpattern%idx_e(nn)
if (nm == 0) cycle
rpattern%spec_e(nn,1,k) = pattern2d(nm)
rpattern%spec_e(nn,2,k) = pattern2d(ndimspec+nm)
enddo
do nn=1,len_trio_ls
nm = rpattern%idx_o(nn)
if (nm == 0) cycle
rpattern%spec_o(nn,1,k) = pattern2d(nm)
rpattern%spec_o(nn,2,k) = pattern2d(ndimspec+nm)
enddo
!print*,'after scatter...',me,maxval(pattern2d_e),maxval(pattern2d_o) &
! ,minval(pattern2d_e),minval(pattern2d_o)
deallocate(pattern2d,isave)
end subroutine read_pattern
end module stochy_data_mod