import sys; sys.path.append('../../py_src') from pyOM_gui import pyOM_gui as pyOM #from pyOM_cdf import pyOM_cdf as pyOM from numpy import * from scipy.io.netcdf import netcdf_file as NF class flame_E7(pyOM): """ the 4/3 FLAME Atlantic model """ def set_parameter(self): """set main parameter """ M=self.fortran.main_module (M.nx,M.ny,M.nz) = (87,89,45) M.dt_mom = 3600.0 M.dt_tracer = 3600.0 M.runlen = 86400*365.0 M.coord_degree = 1 M.congr_epsilon = 1e-6 M.congr_max_iterations = 20000 M.enable_streamfunction = 1 I=self.fortran.isoneutral_module I.enable_neutral_diffusion = 1 I.enable_skew_diffusion = 1 I.k_iso_0 = 1000.0 I.k_iso_steep = 200.0 I.iso_dslope = 1./1000.0 I.iso_slopec = 4./1000.0 M.enable_hor_friction = 1 M.a_h = 5e4 M.enable_hor_friction_cos_scaling = 1 M.hor_friction_cosPower = 3 M.enable_tempsalt_sources = 1 M.enable_implicit_vert_friction = 1 T=self.fortran.tke_module T.enable_tke = 1 T.c_k = 0.1 T.c_eps = 0.7 T.alpha_tke = 30.0 T.mxl_min = 1e-8 T.tke_mxl_choice = 2 M.k_gm_0 = 1000.0 #E=self.fortran.eke_module #E.enable_eke = 1 I=self.fortran.idemix_module I.enable_idemix = 1 I.enable_idemix_hor_diffusion = 1 M.eq_of_state_type = 5 return def set_grid(self): M=self.fortran.main_module fid = NF('forcing.cdf','r') (i1,i2) = ( self.if2py(M.is_pe), self.if2py(M.ie_pe) ) M.dxt[i1:i2+1] = fid.variables['dxtdeg'][M.is_pe-1:M.ie_pe] (j1,j2) = ( self.jf2py(M.js_pe), self.jf2py(M.je_pe) ) M.dyt[j1:j2+1] = fid.variables['dytdeg'][M.js_pe-1:M.je_pe] M.dzt[:] = fid.variables['dzt'][::-1] /100.0 M.x_origin = fid.variables['xu'][0] M.y_origin = fid.variables['yu'][0] return def set_coriolis(self): M=self.fortran.main_module for j in range( M.yt.shape[0] ): M.coriolis_t[:,j] = 2*M.omega*sin(M.yt[j]/180.*pi) return def set_topography(self): """ setup topography """ M=self.fortran.main_module fid = NF('forcing.cdf','r') kmt = fid.variables['kmt'][:] M.kbot[:]=1 for j in range(M.js_pe,M.je_pe+1): for i in range(M.is_pe,M.ie_pe+1): (ii,jj) = ( self.if2py(i), self.jf2py(j) ) M.kbot[ii,jj]=min(M.nz,M.nz-kmt[j-1,i-1]+1) if kmt[j-1,i-1] == 0: M.kbot[ii,jj] =0 return def set_initial_conditions(self): """ setup initial conditions """ M=self.fortran.main_module fid = NF('forcing.cdf','r') # initial conditions t = fid.variables['temp_ic'][::-1,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe] s = fid.variables['salt_ic'][::-1,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe] for k in range(M.nz): M.temp[ self.if2py(M.is_pe):self.if2py(M.ie_pe)+1, self.jf2py(M.js_pe):self.jf2py(M.je_pe)+1, k,M.tau-1] = t[k,:,:].transpose() M.salt[ self.if2py(M.is_pe):self.if2py(M.ie_pe)+1, self.jf2py(M.js_pe):self.jf2py(M.je_pe)+1, k,M.tau-1] = s[k,:,:].transpose()*1000+35.0 for d in (M.temp,M.salt): d[...,M.tau-1] = d[...,M.tau-1]*M.maskt d[...,M.taum1-1] = d[...,M.tau-1] # wind stress self.tx = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') self.ty = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') for k in range(12): self.tx[2:-2,2:-2,k] = fid.variables['taux'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose()/10. /M.rho_0 self.ty[2:-2,2:-2,k] = fid.variables['tauy'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose()/10. /M.rho_0 # zero out masks and do boundary exchange for d in (self.tx, self.ty) : d[ d <= -1e10 ] = 0.0 for k in range(12): self.fortran.border_exchg_xy(M.is_pe-M.onx,M.ie_pe+M.onx,M.js_pe-M.onx,M.je_pe+M.onx,d[:,:,k]) self.fortran.setcyclic_xy (M.is_pe-M.onx,M.ie_pe+M.onx,M.js_pe-M.onx,M.je_pe+M.onx,d[:,:,k]) # interpolate from B grid location to C grid for k in range(12): self.tx[:,1:,k] = (self.tx[:,:-1,k] + self.tx[:,1:,k])/(M.maskz[:,:-1,-1]+M.maskz[:,1:,-1]+1e-20) self.ty[1:,:,k] = (self.ty[:-1,:,k] + self.ty[1:,:,k])/(M.maskz[:-1,:,-1]+M.maskz[1:,:,-1]+1e-20) self.tx[:,:,k] = self.tx[:,:,k]*M.masku[:,:,-1] self.ty[:,:,k] = self.ty[:,:,k]*M.maskv[:,:,-1] # heat flux and salinity restoring self.sst_clim = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') self.sss_clim = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') self.sst_rest = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') self.sss_rest = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') for k in range(12): self.sst_clim[2:-2,2:-2,k] = fid.variables['sst_clim'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose() self.sss_clim[2:-2,2:-2,k] = fid.variables['sss_clim'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose()*1000+35 self.sst_rest[2:-2,2:-2,k] = fid.variables['sst_rest'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose()*41868. self.sss_rest[2:-2,2:-2,k] = fid.variables['sss_rest'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose()/100.0 for d in (self.sst_clim, self.sss_clim, self.sst_rest, self.sss_rest): d[ d <= -1e10 ] = 0.0 # sponge layers self.t_star = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, M.nz, 12 ), 'd' , order = 'F') self.s_star = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, M.nz, 12 ), 'd' , order = 'F') self.rest_tscl = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, M.nz ), 'd' , order = 'F') fid = NF('restoring_zone.cdf','r') (i1,j1) = ( self.if2py(M.is_pe ), self.jf2py(M.js_pe) ) (i2,j2) = ( self.if2py(M.ie_pe+1), self.jf2py(M.je_pe+1) ) for k in range(M.nz): self.rest_tscl[i1:i2,j1:j2,k] = fid.variables['tscl'][0,k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose() for n in range(12): for k in range(M.nz): self.t_star[i1:i2,j1:j2,k,n] = fid.variables['t_star'][n,k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose() self.s_star[i1:i2,j1:j2,k,n] = fid.variables['s_star'][n,k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose() I=self.fortran.idemix_module if I.enable_idemix: f = reshape( fromfile('tidal_energy.bin', dtype='>f'), (M.nx,M.ny), order='F' )/M.rho_0 I.forc_iw_bottom[2:-2,2:-2] = f[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe] f = reshape( fromfile('wind_energy.bin', dtype='>f'), (M.nx,M.ny), order='F' )/M.rho_0*0.2 I.forc_iw_surface[2:-2,2:-2] = f[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe] return def get_periodic_interval(self,currentTime,cycleLength,recSpacing,nbRec): """ interpolation routine taken from mitgcm """ locTime = currentTime - recSpacing*0.5 + cycleLength*( 2 - round(currentTime/cycleLength) ) tmpTime = locTime % cycleLength tRec1 = 1 + int( tmpTime/recSpacing ) tRec2 = 1 + tRec1 % int(nbRec) wght2 = ( tmpTime - recSpacing*(tRec1 - 1) )/recSpacing wght1 = 1.0 - wght2 return (wght1,wght2,tRec1,tRec2) def set_forcing(self): M=self.fortran.main_module fxa = 365*86400.0 (f1,f2,n1,n2) = self.get_periodic_interval((M.itt-1)*M.dt_tracer,fxa,fxa/12.,12) M.surface_taux[:]=(f1*self.tx[:,:,n1-1] + f2*self.tx[:,:,n2-1]) M.surface_tauy[:]=(f1*self.ty[:,:,n1-1] + f2*self.ty[:,:,n2-1]) T=self.fortran.tke_module if T.enable_tke: T.forc_tke_surface[1:-1,1:-1] = sqrt( (0.5*(M.surface_taux[1:-1,1:-1]+M.surface_taux[:-2,1:-1]) )**2 \ +(0.5*(M.surface_tauy[1:-1,1:-1]+M.surface_tauy[1:-1,:-2]) )**2 )**(3./2.) cp_0 = 3991.86795711963 M.forc_temp_surface[:]=(f1*self.sst_rest[:,:,n1-1]+f2*self.sst_rest[:,:,n2-1])* \ (f1*self.sst_clim[:,:,n1-1]+f2*self.sst_clim[:,:,n2-1]-M.temp[:,:,-1,M.tau-1])*M.maskt[:,:,-1]/cp_0/M.rho_0 M.forc_salt_surface[:]=(f1*self.sss_rest[:,:,n1-1]+f2*self.sss_rest[:,:,n2-1])* \ (f1*self.sss_clim[:,:,n1-1]+f2*self.sss_clim[:,:,n2-1]-M.salt[:,:,-1,M.tau-1])*M.maskt[:,:,-1] # apply simple ice mask n=nonzero( logical_and( M.temp[:,:,-1,M.tau-1]*M.maskt[:,:,-1] <= -1.8 , M.forc_temp_surface <= 0.0 ) ) M.forc_temp_surface[n]=0.0 M.forc_salt_surface[n]=0.0 if M.enable_tempsalt_sources: M.temp_source[:] = M.maskt*self.rest_tscl*(f1*self.t_star[:,:,:,n1-1]+f2*self.t_star[:,:,:,n2-1] - M.temp[:,:,:,M.tau-1] ) M.salt_source[:] = M.maskt*self.rest_tscl*(f1*self.s_star[:,:,:,n1-1]+f2*self.s_star[:,:,:,n2-1] - M.salt[:,:,:,M.tau-1] ) return def set_diagnostics(self): M=self.fortran.main_module self.register_average(name='temp',long_name='Temperature', units = 'deg C' , grid = 'TTT', var = M.temp) self.register_average(name='salt',long_name='Salinity', units = 'g/kg' , grid = 'TTT', var = M.salt) self.register_average(name='u', long_name='Zonal velocity', units = 'm/s' , grid = 'UTT', var = M.u) self.register_average(name='v', long_name='Meridional velocity', units = 'm/s' , grid = 'TUT', var = M.v) self.register_average(name='w', long_name='Vertical velocity', units = 'm/s' , grid = 'TTU', var = M.w) self.register_average(name='taux',long_name='wind stress', units = 'm^2/s' , grid = 'UT', var = M.surface_taux) self.register_average(name='tauy',long_name='wind stress', units = 'm^2/s' , grid = 'TU', var = M.surface_tauy) self.register_average(name='psi' ,long_name='Streamfunction', units = 'm^3/s' , grid = 'UU', var = M.psi) return def user_defined_signal(self): """ this routine must be called by all processors """ M=self.fortran.main_module a = zeros( (M.nx,M.ny), 'd', order = 'F') a[M.is_pe-1:M.ie_pe,0] = M.xt[2:-2] self.fortran.pe0_recv_2d(a) self.xt_gl = a[:,0].copy() a[0,M.js_pe-1:M.je_pe] = M.yt[2:-2] self.fortran.pe0_recv_2d(a) self.yt_gl = a[0,:].copy() self.psi_gl = zeros( (M.nx,M.ny), 'd', order = 'F') self.psi_gl[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe] = where( M.maskz[2:-2,2:-2,-1] >0, M.psi[2:-2,2:-2,M.tau-1] , NaN) self.fortran.pe0_recv_2d(self.psi_gl) self.temp_gl = zeros( (M.nx,M.ny,M.nz), 'd', order = 'F') for k in range(M.nz): a[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe] = where( M.maskt[2:-2,2:-2,k] >0, M.temp[2:-2,2:-2,k,M.tau-1] , NaN) self.fortran.pe0_recv_2d(a) self.temp_gl[:,:,k]=a.copy() self.salt_gl = zeros( (M.nx,M.ny,M.nz), 'd', order = 'F') for k in range(M.nz): a[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe] = where( M.maskt[2:-2,2:-2,k] >0, M.salt[2:-2,2:-2,k,M.tau-1] , NaN) self.fortran.pe0_recv_2d(a) self.salt_gl[:,:,k]=a.copy() #self.kappa_gl = zeros( (M.nx,M.ny,M.nz), 'd', order = 'F') #for k in range(M.nz): # a[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe] = where( M.maskw[2:-2,2:-2,k] >0, M.kappah[2:-2,2:-2,k] , NaN) # self.fortran.pe0_recv_2d(a) # self.kappa_gl[:,:,k]=a.copy() return def make_plot(self): M=self.fortran.main_module # fortran module with model variables self.figure.clf() self.set_signal('user_defined') # following routine is called by all PEs self.user_defined_signal() ax=self.figure.add_subplot(221) co=ax.contourf(self.yt_gl,M.zt,self.temp_gl[M.nx/2-1,:,:].transpose()) self.figure.colorbar(co) ax.set_title('Temperature [deg C]') ax.set_ylabel('z [m]') ax.axis('tight') ax=self.figure.add_subplot(223) co=ax.contourf(self.yt_gl,M.zt,self.salt_gl[M.nx/2-1,:,:].transpose()) self.figure.colorbar(co) ax.set_title('Salinity [g/kg]') ax.set_ylabel('z [m]') ax.axis('tight') #ax=self.figure.add_subplot(223) #try: # co=ax.contourf(self.yt_gl,M.zw,log10(self.kappa_gl[M.nx/2-1,:,:].transpose()) ) #except: # pass #self.figure.colorbar(co) #ax.set_title('Diffusivity') #ax.set_xlabel('Latitude [deg N]') #ax.set_ylabel('z [m]') #ax.axis('tight') ax=self.figure.add_subplot(222) co=ax.contourf(self.xt_gl,self.yt_gl,self.psi_gl.transpose()*1e-6) self.figure.colorbar(co) ax.set_title('Streamfunction [Sv]') #ax.set_xlabel('Longitude [deg E]') ax.set_ylabel('Latitude [deg N]') ax.axis('tight') ax=self.figure.add_subplot(224) co=ax.contourf(self.xt_gl,self.yt_gl,self.temp_gl[:,:,-1].transpose()) self.figure.colorbar(co) ax.set_title('Sea Surface Temperature [deg C]') #ax.set_xlabel('Longitude [deg E]') ax.set_ylabel('Latitude [deg N]') ax.axis('tight') return if __name__ == "__main__": flame_E7().run(snapint= 86400.0)