No commit message

No commit message

da/cosmo/obs.py

@@ -374,7 +374,8 @@ class Obs(Observations):
             name = name.strip().lower()
 #            print 'PAVLE NAME                  ',name,error, may_localize, may_reject
             error = float(error)
-            may_reject = ("TRUE" in may_reject.upper())
+            may_reject = ("FALSE" in may_reject.upper())
+#            may_reject = ("TRUE" in may_reject.upper())
             may_localize = ("TRUE" in may_localize.upper())
             site_categories[name] = {'category': name, 'error': error, 'may_localize': may_localize, 'may_reject': may_reject}
 

da/cosmo/observationoperator.py

@@ -119,19 +119,16 @@ class ObservationOperator(object):
 #        for ncfile in ncfilelist:
 #            infile = os.path.join(ncfile + '.nc')
 
-        for dt in rrule.rrule(rrule.HOURLY, dtstart=dacycle['time.start'], until=dacycle['time.start']+timedelta(hours=168)):
-            for ens in range(0,self.forecast_nmembers):
-                ens = str(ens).zfill(3)
-                cdo.expr("CO2_GPP_"+ens+"_F=parametermap*CO2_GPP_F -merge /scratch/snx3000/parsenov/projname/input/parameters."+ens+".nc", input = os.path.join(dacycle['da.bio.input'], 'gpp_%s.nc' % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
-                cdo.expr("CO2_RESP_"+ens+"_F=parametermap*CO2_RESP_F -merge /scratch/snx3000/parsenov/projname/input/parameters."+ens+".nc", input = os.path.join(dacycle['da.bio.input'], 'ra_%s.nc' % dt.strftime('%Y%m%d%H')), 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')))
-
-        os.system('python '+dacycle['da.obsoperator.home']+' ctdas '+dacycle['time.start'].strftime('%Y-%m-%d')+' 0 168 -j meteo icbc emissions biofluxes int2lm post_int2lm')
-        # here comes COSMO
-       #     os.system('python '+cosmo+' ctdas '+self['time.start'].strftime('%Y-%m-%d')+' 0 672 -j cosmo')
-       #     extract_model_data(self.forecast_nmembers)
-        sys.exit()
+        #for dt in rrule.rrule(rrule.HOURLY, dtstart=dacycle['time.start'], until=dacycle['time.start']+timedelta(hours=168)):
+         #   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 = "/scratch/snx3000/parsenov/projname/input/parameters."+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 = "/scratch/snx3000/parsenov/projname/input/parameters."+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')))
+  #      os.chdir(dacycle['da.obsoperator.home'])
+#        os.system('python run_chain.py ctdas '+dacycle['time.start'].strftime('%Y-%m-%d')+' 0 168 -j meteo icbc emissions biofluxes int2lm post_int2lm cosmo')
+        self.extract_model_data(dacycle,self.forecast_nmembers)
 
         for i in range(0,self.forecast_nmembers):
             idx=str(i+1)
@@ -168,12 +165,15 @@ class ObservationOperator(object):
         self.prepare_run()
         self.run(dacycle)
 
-    def extract_model_data(ens):
+    def extract_model_data(self,dacycle,ens):
         
         files2cat=[]
-
-        time_stamp = self['time.sample.stamp']
-        cosmo_out = self['da.cosmo_path']+'/'+ens+'/'+time_stamp+'cosmo/output'
+        self.dacycle = dacycle
+#        time_stamp = dacycle['time.sample.stamp']
+        cosmo_time_stamp = dacycle['time.start']+timedelta(hours=168)
+        print(cosmo_time_stamp)
+        sys.exit()
+        cosmo_out = "/scratch/snx3000/parsenov/ctdas/2013040100_0_168/cosmo"
         os.chdir(cosmo_out)
 
         for time in tools.iter_hours(starttime, hstart, hstop):

da/cosmo/statevector.py

@@ -289,6 +289,7 @@ class StateVector(object):
 
         for member in range(1, self.nmembers):
             rands = np.random.randn(self.nparams)
+            rands = np.clip(rands,-1,1)
 
             newmember = EnsembleMember(member)
             newmember.param_values = np.dot(C, rands) + newmean