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da/cosmo/covariances.py

@@ -27,7 +27,7 @@ sys.path.append(os.getcwd())
 
 import logging
 import numpy as np
-from da.cosmo.base_statevector import StateVector, EnsembleMember
+from da.cosmo.statevector import StateVector, EnsembleMember
 
 import da.tools.io4 as io
 

da/cosmo/observationoperator.py

@@ -124,8 +124,8 @@ class ObservationOperator(object):
             logging.info('Multiplying emissions with parameters for lag %d, date %s' % (lag, dt.strftime('%Y%m%d%H')))
             for ens in range(0,self.forecast_nmembers):
                 ens = str(ens).zfill(3)
-                cdo.setunit("'kg m-2 s-1' -expr,GPP_"+ens+"_F=CO2_GPP_F*parametermap -merge "+os.path.join(dacycle['da.bio.input'], 'gpp_%s.nc' % dt.strftime('%Y%m%d%H')), input = os.path.join(dacycle['restartmap.dir'],"parameters_lag"+str(lag)+"."+ens+".nc"), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
-                cdo.setunit("'kg m-2 s-1' -expr,RESP_"+ens+"_F=CO2_RESP_F*parametermap -merge "+os.path.join(dacycle['da.bio.input'], 'ra_%s.nc' % dt.strftime('%Y%m%d%H')), input = os.path.join(dacycle['restartmap.dir'],"parameters_lag"+str(lag)+"."+ens+".nc"), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
+                cdo.setunit("'kg m-2 s-1' -expr,GPP_"+ens+"_F=CO2_GPP_F*parametermap -merge "+os.path.join(dacycle['da.bio.input'], 'gpp_%s.nc' % dt.strftime('%Y%m%d%H')), input = os.path.join(dacycle['restartmap.dir'],"parameters_gpp_lag"+str(lag)+"."+ens+".nc"), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
+                cdo.setunit("'kg m-2 s-1' -expr,RESP_"+ens+"_F=CO2_RESP_F*parametermap -merge "+os.path.join(dacycle['da.bio.input'], 'ra_%s.nc' % dt.strftime('%Y%m%d%H')), input = os.path.join(dacycle['restartmap.dir'],"parameters_resp_lag"+str(lag)+"."+ens+".nc"), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
             cdo.merge(input = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_???_%s.nc" % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_%s.nc" % dt.strftime('%Y%m%d%H')))
             cdo.merge(input = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_???_%s.nc" % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_%s.nc" % dt.strftime('%Y%m%d%H')))
 
@@ -158,7 +158,6 @@ class ObservationOperator(object):
         for j,data in enumerate(zip(ids,obs,mdm)):
             f.variables['obs_num'][j] = data[0]		
             f.variables['flask'][j,:] = model_data[:,j]
-#            print model_data[:,j]
         f.close()
 #### WARNING ACHTUNG PAZNJA POZOR VNEMANIE data[2] is model data mismatch (=1000) by default in tools/io4.py!!! pavle
 

da/cosmo/obspack_globalviewplus2.py

@@ -347,6 +347,7 @@ class ObsPackObservations(Observations):
 
         for obs in self.datalist:  # first loop over all available data points to set flags correctly
 
+#            obs.mdm = 0.05  # default is very high model-data-mismatch, until explicitly set by script
             obs.mdm = 2.5  # default is very high model-data-mismatch, until explicitly set by script
             obs.flag = 0
             identifier = obs.code

da/cosmo/pipeline.py

@@ -269,6 +269,7 @@ def prepare_state(dacycle, statevector):
     nlag = int(dacycle['time.nlag'])
     for l in range(0,nlag):                      # pavle added from here
         statevector.write_members_to_file(l, dacycle['restartmap.dir'])
+        statevector.write_members_for_cosmo(l, dacycle['restartmap.dir'])
 
 def sample_state(dacycle, samples, statevector, obsoperator):
     """ Sample the filter state for the inversion """
@@ -319,6 +320,7 @@ def sample_step(dacycle, samples, statevector, obsoperator, lag, advance=False):
     # type of info needed in your transport model
 
     statevector.write_members_to_file(lag, dacycle['dir.input']) 
+    statevector.write_members_for_cosmo(lag, dacycle['dir.input']) 
 
     samples.setup(dacycle)       
     samples.add_observations() 

template.py

@@ -33,7 +33,7 @@ from da.cosmo.covariances import CO2StateVector
 #from da.cosmo.statevector import StateVector 
 from da.cosmo.obspack_globalviewplus2 import ObsPackObservations
 #from da.cosmo.obs import Obs 
-from da.carbondioxide.optimizer import CO2Optimizer
+from da.cosmo.optimizer import CO2Optimizer
 from da.cosmo.observationoperator import ObservationOperator
 #from da.analysis.expand_fluxes import save_weekly_avg_1x1_data, save_weekly_avg_state_data, save_weekly_avg_tc_data, save_weekly_avg_ext_tc_data
 #from da.analysis.expand_molefractions import write_mole_fractions
@@ -43,8 +43,8 @@ from da.cosmo.observationoperator import ObservationOperator
 # Parse and validate the command line options, start logging
 #################################################################################################
 
-#start_logger()
-start_logger(level=logging.DEBUG)
+start_logger()
+#start_logger(level=logging.DEBUG)
 opts, args = parse_options()
 opts, args = validate_opts_args(opts, args)