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 global_4deg(pyOM): """ global 4 deg model with 15 levels """ def set_parameter(self): """set main parameter """ M=self.fortran.main_module (M.nx,M.ny,M.nz) = (90,40,15) M.dt_mom = 1800.0 M.dt_tracer = 86400.0 M.coord_degree = 1 M.enable_cyclic_x = 1 M.congr_epsilon = 1e-8 M.congr_max_iterations = 20000 M.enable_streamfunction = 1 I=self.fortran.isoneutral_module I.enable_neutral_diffusion = 1 I.k_iso_0 = 1000.0 I.k_iso_steep = 1000.0 I.iso_dslope=4./1000.0 I.iso_slopec=1./1000.0 I.enable_skew_diffusion = 1 M.enable_hor_friction = 1; M.a_h = (4*M.degtom)**3*2e-11 M.enable_hor_friction_cos_scaling = 1; M.hor_friction_cosPower=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 T.enable_tke_superbee_advection = 1 E=self.fortran.eke_module E.enable_eke = 1 E.eke_k_max = 1e4 E.eke_c_k = 0.4 E.eke_c_eps = 0.5 E.eke_cross = 2. E.eke_crhin = 1.0 E.eke_lmin = 100.0 E.enable_eke_superbee_advection = 1 I=self.fortran.idemix_module I.enable_idemix = 1 I.enable_idemix_hor_diffusion = 1 I.enable_eke_diss_surfbot = 1 I.eke_diss_surfbot_frac = 0.2 # fraction which goes into bottom I.enable_idemix_superbee_advection = 1 M.eq_of_state_type = 5 return def set_grid(self): M=self.fortran.main_module ddz = array([50.,70.,100.,140.,190.,240.,290.,340.,390.,440.,490.,540.,590.,640.,690.]) M.dzt[:]=ddz[::-1] M.dxt[:] = 4.0 M.dyt[:] = 4.0 M.y_origin = -76.0 M.x_origin = 4.0 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 M.kbot[:]=0 bathy = reshape( fromfile('bathymetry.bin', dtype='>i'), (M.nx,M.ny), order='F' ) lev_s = reshape( fromfile('lev_s.bin', dtype='>f', count=M.nx*M.ny*M.nz), (M.nx,M.ny,M.nz), order='F' )[:,:,::-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) ) for k in range(M.nz-1,-1,-1): if lev_s[i-1,j-1,k] > 0.0: M.kbot[ii,jj]=k+1 if bathy[i-1,j-1] == 0.0: M.kbot[ii,jj] =0 M.kbot[ M.kbot == M.nz] = 0 return def set_initial_conditions(self): """ setup initial conditions """ M=self.fortran.main_module self.taux = zeros( (M.i_blk+2*M.onx,M.j_blk+2*M.onx,12), 'd', order = 'F') self.tauy = zeros( (M.i_blk+2*M.onx,M.j_blk+2*M.onx,12), 'd', order = 'F') self.qnec = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') self.qnet = zeros( ( M.i_blk+2*M.onx, M.j_blk+2*M.onx, 12 ), 'd' , order = 'F') 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') # initial conditions for T and S lev = reshape( fromfile('lev_t.bin', dtype='>f', count=M.nx*M.ny*M.nz), (M.nx,M.ny,M.nz), order='F' ) lev = lev[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,::-1] M.temp[M.onx:-M.onx,M.onx:-M.onx,:,M.tau-1] = lev*M.maskt[M.onx:-M.onx,M.onx:-M.onx,:] M.temp[...,M.taum1-1] = M.temp[...,M.tau-1] lev = reshape( fromfile('lev_s.bin', dtype='>f', count=M.nx*M.ny*M.nz), (M.nx,M.ny,M.nz), order='F' ) lev = lev[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,::-1] M.salt[M.onx:-M.onx,M.onx:-M.onx,:,M.tau-1] = lev*M.maskt[M.onx:-M.onx,M.onx:-M.onx,:] M.salt[...,M.taum1-1] = M.salt[...,M.tau-1] # use Trenberth wind stress from MITgcm instead of ECMWF (also contained in ecmwf_4deg.cdf) tx = reshape( fromfile('trenberth_taux.bin', dtype='>f'), (M.nx,M.ny,12), order='F' )/M.rho_0 ty = reshape( fromfile('trenberth_tauy.bin', dtype='>f'), (M.nx,M.ny,12), order='F' )/M.rho_0 self.taux[M.onx:-M.onx,M.onx:-M.onx,:] = tx[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,:] self.tauy[M.onx:-M.onx,M.onx:-M.onx,:] = ty[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,:] # heat flux fid = NF('ecmwf_4deg_monthly.cdf','r') for k in range(12): self.qnec[M.onx:-M.onx,M.onx:-M.onx,k] = fid.variables['Q3'][k,M.js_pe-1:M.je_pe,M.is_pe-1:M.ie_pe].transpose() self.qnec[ self.qnec <= -1e10 ] = 0.0 q = reshape( fromfile('ncep_qnet.bin', dtype='>f'), (M.nx,M.ny,12), order='F' ) self.qnet[M.onx:-M.onx,M.onx:-M.onx,:] = - q[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,:] self.qnet[ self.qnet <= -1e10 ] = 0.0 fxa = zeros( (1,), 'd', order = 'F') fxb = zeros( (1,), 'd', order = 'F') for n in range(12): fxa = fxa + sum( self.qnet[M.onx:-M.onx,M.onx:-M.onx,n]*M.area_t[M.onx:-M.onx,M.onx:-M.onx] ) fxb = fxb + sum( M.area_t[M.onx:-M.onx,M.onx:-M.onx] ) self.fortran.global_sum(fxa) self.fortran.global_sum(fxb) fxa = fxa[0]/fxb[0] if M.my_pe==0: print ' removing an annual mean heat flux imbalance of %e W/m^2'% fxa for n in range(12): self.qnet[:,:,n] = (self.qnet[:,:,n] - fxa)*M.maskt[:,:,-1] # SST and SSS sst = reshape( fromfile('lev_sst.bin', dtype='>f'), (M.nx,M.ny,12), order='F' ) sss = reshape( fromfile('lev_sss.bin', dtype='>f'), (M.nx,M.ny,12), order='F' ) self.sst_clim[M.onx:-M.onx,M.onx:-M.onx,:] = sst[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,:] self.sss_clim[M.onx:-M.onx,M.onx:-M.onx,:] = sss[M.is_pe-1:M.ie_pe,M.js_pe-1:M.je_pe,:] 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[ M.onx:-M.onx,M.onx:-M.onx] = 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[M.onx:-M.onx,M.onx:-M.onx] = 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 (f1,f2,n1,n2) = self.get_periodic_interval((M.itt-1)*M.dt_tracer,365*86400.0,365*86400./12.,12) # wind stress M.surface_taux[:]=(f1*self.taux[:,:,n1-1] + f2*self.taux[:,:,n2-1]) M.surface_tauy[:]=(f1*self.tauy[:,:,n1-1] + f2*self.tauy[:,:,n2-1]) # tke flux 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.) # heat flux : W/m^2 K kg/J m^3/kg = K m/s cp_0 = 3991.86795711963 sst = f1*self.sst_clim[:,:,n1-1]+f2*self.sst_clim[:,:,n2-1] qnec = f1*self.qnec[:,:,n1-1] +f2*self.qnec[:,:,n2-1] qnet = f1*self.qnet[:,:,n1-1] +f2*self.qnet[:,:,n2-1] M.forc_temp_surface[:] =(qnet+ qnec*(sst-M.temp[:,:,-1,M.tau-1]) )*M.maskt[:,:,-1]/cp_0/M.rho_0 # salinity restoring t_rest= 30*86400.0 sss = f1*self.sss_clim[:,:,n1-1]+f2*self.sss_clim[:,:,n2-1] M.forc_salt_surface[:] =M.dzt[-1]/t_rest*(sss-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.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(222) 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') ax=self.figure.add_subplot(223) 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(224) 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(224) #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') return if __name__ == "__main__": global_4deg().run(snapint= 86400.0*25, runlen = 86400.*365*10)