Exemplo n.º 1
0
    dataset.title='Daily global radiation'
    dataset.comment='Daily global radiation bias corrected (scaled distribution mapping) data of the EURO-CORDEX model. The reference period is 1981-2010, the years 2006-2010 are taken from the corresponding rcp4.5 scenario.'
    
var.grid_mapping = 'latitude_longitude'

# projection information
crs.longitude_of_prime_meridian = 0.0 
crs.semi_major_axis = 6378137.0
crs.inverse_flattening = 298.257223563
crs.comment = 'Latitude and longitude on the WGS 1984 datum'

# write data to netCDF variable
var[:] = ds[param].data
lats[:] = lat1d
lons[:] = lon1d

# fill in times
dates = [startdate+k*timedelta(days=1) for k in range(ds[param].data.shape[0])]
times[:] = date2num(dates, units=times.units, calendar=times.calendar)

# global attributes

dataset.project= "Climaproof, funded by the Austrian Development Agency (ADA) and co-funded by the United Nations Environmental Programme (UNEP)"
dataset.source = 'Bias Correction Method: Switanek et al., 2017, doi.org/10.5194/hess-21-2649-2017, Regridding Method: Higher-order patch recovery (patch) by Earth System Modelling Framework (ESMF) software ESMF_RegridWeightGen (http://www.earthsystemmodeling.org/esmf_releases/public/last/ESMF_refdoc/)'
dataset.contact = 'Maria Wind <*****@*****.**>, Herbert Formayer <*****@*****.**>'
dataset.institution = 'Institute of Meteorology, University of Natural Resources and Life Sciences, Vienna, Austria'
dataset.referencees = 'https://data.ccca.ac.at/group/climaproof'
dataset.conventions = 'CF-1.6'

# close dataset        
dataset.close()
# projection information
crs.longitude_of_prime_meridian = 0.0 
crs.semi_major_axis = 6378137.0
crs.inverse_flattening = 298.257223563
crs.comment = 'Latitude and longitude on the WGS 1984 datum'

# write data to netCDF variable
#print ds[param]
#print var
#exit()
var[:] = ds[param].data
lats[:] = lat1d
lons[:] = lon1d


# fill in times
dates = [startdate+k*timedelta(days=1) for k in range(ds[param].data.shape[0])]
times[:] = date2num(dates, units=times.units, calendar=times.calendar)

# global attributes

dataset.project= "URBANIA, funded by KLIEN"
dataset.source = 'WRF-TEB' #Bias Correction Method: Switanek et al., 2017, doi.org/10.5194/hess-21-2649-2017, Regridding Method: Higher-order patch recovery (patch) by Earth System Modelling Framework (ESMF) software ESMF_RegridWeightGen (http://www.earthsystemmodeling.org/esmf_releases/public/last/ESMF_refdoc/)'
dataset.contact = '*****@*****.**' #Maria Wind <*****@*****.**>, Herbert Formayer <*****@*****.**>'
dataset.institution = 'Institute of Meteorology, University of Natural Resources and Life Sciences, Vienna, Austria'
dataset.referencees = 'http://urbania.boku.ac.at'
dataset.conventions = 'CF-1.6'

# close dataset        
dataset.close()