Merge pull request #79 from sam-hartke-ucar/main

adding ERA5 conversion file

helpers/writeERA5file.py

@@ -0,0 +1,91 @@
+import os
+import numpy as np
+import pandas as pd
+import xarray as xr
+#import qfgrib
+from datetime import timedelta,datetime
+from dateutil.relativedelta import relativedelta
+
+
+era5pl_template = "/glade/collections/rda/data/ds633.0/e5.oper.an.pl/{yr}{mth}/e5.oper.an.pl.{var_id}.{dt}00_{dt}23.grb"
+era5sfc_template = "/glade/collections/rda/data/ds633.0/e5.oper.an.sfc/{yr}{mth}/e5.oper.an.sfc.{var_id}.{dt}00_{dt2}23.grb"
+w_format = "128_135_w.ll025sc"
+v_format = "128_132_v.ll025uv"
+u_format = "128_131_u.ll025uv"
+q_format = "128_133_q.ll025sc"
+t_format = "128_130_t.ll025sc"
+tcrw_format = "228_089_tcrw.ll025sc"
+
+
+
+var_formats = {'v':v_format,
+               'u':u_format,
+               'w':w_format,
+               'q':q_format,
+               't':t_format,
+               'tcrw':tcrw_format,
+                }
+
+# new variable names to match those from CESM LENS 2
+newvarname = {'v':'V',
+               'u':'U',
+               'w':'W',
+               'q':'Q',
+               't':'T',
+               'tcrw':'PRECT',
+                }
+
+def createInputDataset(yr_st,yr_end,varlist):
+
+    m=0
+    for var in varlist:
+        var_files = []
+        dt = datetime(yr_st,1,1)
+        while dt.year <= yr_end:
+            yr = dt.year
+            mth = "%.02d"%dt.month
+            if var in ('u','v','w','q','t'):
+                var_files.append(era5pl_template.format(yr=yr,mth=mth,var_id=var_formats[var],dt=dt.strftime('%Y%m%d')))
+                dt = dt + timedelta(days=1)
+
+            elif var == 'tcrw':
+                dt2 = dt + relativedelta(months=+1) - timedelta(days=1)
+                var_files.append(era5sfc_template.format(yr=yr,mth=mth,var_id=var_formats[var],
+                                                         dt=dt.strftime('%Y%m%d'),dt2=dt2.strftime('%Y%m%d')))
+
+                dt = dt + relativedelta(months=+1)
+
+        vardata = xr.open_mfdataset(var_files,concat_dim='time',combine='nested',
+                                 backend_kwargs={"indexpath":""}).sel(latitude=slice(50,20),
+                                               longitude=slice(360-120,360-60))[var]
+
+        if var in ('u','v','w','q','t'):
+            vardata = vardata.isel(isobaricInhPa=20).drop_vars('isobaricInhPa') #~450 mb
+            vardata = vardata.resample(time='1D').mean()
+
+        else:
+            vardata = vardata.resample(time='1D').sum()
+
+
+        if m==0:
+            era5_ds = vardata.to_dataset()
+        else:
+            era5_ds = era5_ds.assign(var=vardata)
+
+        era5_ds = era5_ds.rename({'var':newvarname[var]})
+
+        m+=1
+
+    if yr_st!=yr_end:
+        outfile = '/glade/scratch/shartke/gard/era5/era5_daily_%d_%d.nc'%(yr_st,yr_end)
+    else:
+        outfile = '/glade/scratch/shartke/gard/era5/era5_daily_%d.nc'%yr_st
+    era5_ds.to_netcdf(outfile)    
+
+
+
+print(datetime.now())
+createInputDataset(1982,1982,['u','v','w','q','t','tcrw'])
+print('1982 dataset complete at: ',datetime.now())
+createInputDataset(1983,1983,['u','v','w','q','t','tcrw'])
+print('1983 dataset complete at: ',datetime.now())