def read_climate_statistics(gdir):
"""Reads the annual cycle of climate for [1985-2015] at the glacier terminus elevation.
Parameters
----------
gdir : the glacier directory
Returns
-------
a pandas Dataframe with monthly average temp and precip
"""
with xr.open_dataset(gdir.get_filepath('climate_monthly')) as ds:
ds = ds.load()
ds = ds.sel(time=slice('1985', '2015'))
dsm = ds.groupby('time.month').mean(dim='time')
odf = pd.DataFrame()
odf['temp_celcius'] = dsm.temp.to_series()
odf['prcp_mm_mth'] = dsm.prcp.to_series()
# We correct for altitude difference
d = utils.glacier_statistics(gdir)
odf['temp_celcius'] += (ds.ref_hgt - d['flowline_min_elev']) * 0.0065
return odf
def compute_climate_statistics(gdir,
tmin='1985',
tmax='2015',
lapse_rate=0.0065):
"""Computes monthly average temperature and precipitation
during the climate period defined by tmin and tmax.
Temperatures are reduced to the terminus elevation assuming
a constant lapse rate.
Parameters
----------
gdir : oggm.GlacierDirectory
the glacier directory defined by oggm
tmin : int
the beginning of the period of interest
tmax : int
the end of the period of interest
Returns
-------
odf : pd.DataFrame
dataframe containing monthly average temperature and precipitation
during tmin-tmax
"""
try:
with xr.open_dataset(gdir.get_filepath('climate_monthly')) as ds:
ds = ds.load()
except FileNotFoundError:
with xr.open_dataset(gdir.get_filepath('climate_historical')) as ds:
ds = ds.load()
ds = ds.sel(time=slice(str(tmin), str(tmax)))
dsm = ds.groupby('time.month').mean(dim='time')
odf = pd.DataFrame()
odf['temp_celcius'] = dsm.temp.to_series()
odf['prcp_mm_mth'] = dsm.prcp.to_series()
# We correct for altitude difference
d = utils.glacier_statistics(gdir)
odf['temp_celcius'] += (ds.ref_hgt - d['flowline_min_elev']) * lapse_rate
return odf