def get_mu_star_from_glacier(gdir):
""" Reads RACMO data and calculates the mean temperature sensitivity
from RACMO SMB data and snow melt estimates. In a glacier wide average and
a mean value of the entire RACMO time series. Based on the method described
in Oerlemans, J., and Reichert, B. (2000).
Parameters
------------
gdir : :py:class:`oggm.GlacierDirectory`
the glacier directory to process
:returns
Mu_star_racmo mean value in mm.w.e /K-1
"""
fpath = gdir.dir + '/racmo_data.nc'
if os.path.exists(fpath):
with ncDataset(fpath, mode='r') as nc:
smb = nc.variables['smb'][:]
melt = nc.variables['snow_melt'][:]
mu = smb / melt
mean_mu = np.average(mu,
weights=np.repeat(gdir.rgi_area_km2, len(mu)))
else:
print('This glacier has no racmo data ' + gdir.rgi_id)
mean_mu = None
return mean_mu
def get_smb31_from_glacier(gdir):
""" Reads RACMO data and takes a mean over 31 year period of the
surface mass balance
Parameters
------------
gdir : :py:class:`oggm.GlacierDirectory`
the glacier directory to process
:returns
smb_31 mean value in km^3/yr
"""
fpath = gdir.dir + '/racmo_data.nc'
if os.path.exists(fpath):
with ncDataset(fpath, mode='r') as nc:
smb = nc.variables['smb'][:]
if smb.all() == 0:
smb_mean = None
smb_cum = None
smb_calving_mean = None
smb_calving_cum = None
print('This glacier has no racmo data ' + gdir.rgi_id)
else:
smb_mean = np.nanmean(smb)
smb_cum = np.nansum(smb)
smb_calving_mean = calving_flux_km3yr(gdir, smb_mean)
smb_calving_cum = calving_flux_km3yr(gdir, smb_cum)
else:
print('This glacier has no racmo data ' + gdir.rgi_id)
smb_mean = None
smb_cum = None
smb_calving_mean = None
smb_calving_cum = None
return smb_mean, smb_cum, smb_calving_mean, smb_calving_cum
def get_smb31_from_glacier(gdir):
""" Reads RACMO data and takes a mean over a reference period for the
surface mass balance and adds an uncertainty based on the std
over the entire data period.
:param
gdir: `oggm.GlacierDirectory`
:return
out_dic: a dictionary with averages and cumulative estimates of smb in
original units and in frontal ablation units.
It also includes uncertainty.
"""
fpath = gdir.dir + '/racmo_data.nc'
if os.path.exists(fpath):
with ncDataset(fpath, mode='r') as nc:
smb = nc.variables['smb'][:]
std = nc.variables['std'][:]
if smb.all() == 0:
smb_mean = None
smb_std = None
smb_cum = None
smb_calving_mean = None
smb_calving_std = None
smb_calving_cum = None
print('This glacier has no racmo data ' + gdir.rgi_id)
else:
smb_mean = np.nanmean(smb)
smb_std = np.nanmean(std)
smb_cum = np.nansum(smb)
smb_calving_mean = calving_flux_km3yr(gdir, smb_mean)
smb_calving_std = calving_flux_km3yr(gdir, smb_std)
smb_calving_cum = calving_flux_km3yr(gdir, smb_cum)
else:
print('This glacier has no racmo data ' + gdir.rgi_id)
smb_mean = None
smb_std = None
smb_cum = None
smb_calving_mean = None
smb_calving_std = None
smb_calving_cum = None
out_dic = dict(smb_mean=smb_mean,
smb_std=smb_std,
smb_cum=smb_cum,
smb_calving_mean=smb_calving_mean,
smb_calving_std=smb_calving_std,
smb_calving_cum=smb_calving_cum)
return out_dic
def process_racmo_data(gdir, racmo_path, time_start=None, time_end=None):
"""Processes and writes RACMO data in each glacier directory.
Parameters
----------
gdir : :py:class:`oggm.GlacierDirectory`
the glacier directory to process
racmo_path: the main path to the RACMO data
:returns
writes an nc file in each glacier directory with the RACMO data
time series of SMB, precipitation, run off and melt for a 31 reference
period according to X. Fettweis et al. 2017,
Eric Rignot and Pannir Kanagaratnam, 2006.
"""
mask_file = os.path.join(racmo_path,
'Icemask_Topo_Iceclasses_lon_lat_average_1km.nc')
smb_file = os.path.join(
racmo_path, 'smb_rec.1958-2018.BN_RACMO2.3p2_FGRN055_GrIS.MM.nc')
prcp_file = os.path.join(
racmo_path, 'precip.1958-2018.BN_RACMO2.3p2_FGRN055_GrIS.MM.nc')
run_off_file = os.path.join(
racmo_path, 'runoff.1958-2018.BN_RACMO2.3p2_FGRN055_GrIS.MM.nc')
melt_file = os.path.join(
racmo_path, 'snowmelt.1958-2018.BN_RACMO2.3p2_FGRN055_GrIS.MM.nc')
fall_file = os.path.join(
racmo_path, 'snowfall.1958-2018.BN_RACMO2.3p2_FGRN055_GrIS.MM.nc')
# Get files as xarray all units mm. w.e.
# Surface Mass Balance
ds_smb = open_racmo(smb_file, mask_file)
# Total precipitation: solid + Liquid
ds_prcp = open_racmo(prcp_file)
# Run off
ds_run_off = open_racmo(run_off_file)
# water that result from snow and ice melting
ds_melt = open_racmo(melt_file)
# Solid precipitation
ds_fall = open_racmo(fall_file)
# crop the data to glacier outline
smb_sel = crop_racmo_to_glacier_grid(gdir, ds_smb)
prcp_sel = crop_racmo_to_glacier_grid(gdir, ds_prcp)
run_off_sel = crop_racmo_to_glacier_grid(gdir, ds_run_off)
melt_sel = crop_racmo_to_glacier_grid(gdir, ds_melt)
fall_sel = crop_racmo_to_glacier_grid(gdir, ds_fall)
# get RACMO time series in 31 year period centered in t*
smb_31 = get_racmo_time_series(smb_sel,
var_name='SMB_rec',
dim_one='x',
dim_two='y',
dim_three='time',
time_start=time_start,
time_end=time_end)
prcp_31 = get_racmo_time_series(prcp_sel,
var_name='precipcorr',
dim_one='lon',
dim_two='lat',
dim_three='time',
time_start=time_start,
time_end=time_end)
run_off_31 = get_racmo_time_series(run_off_sel,
var_name='runoffcorr',
dim_one='lon',
dim_two='lat',
dim_three='time',
time_start=time_start,
time_end=time_end)
melt_31 = get_racmo_time_series(melt_sel,
var_name='snowmeltcorr',
dim_one='lon',
dim_two='lat',
dim_three='time',
time_start=time_start,
time_end=time_end)
fall_31 = get_racmo_time_series(fall_sel,
var_name='snowfallcorr',
dim_one='lon',
dim_two='lat',
dim_three='time',
time_start=time_start,
time_end=time_end)
fpath = gdir.dir + '/racmo_data.nc'
if os.path.exists(fpath):
os.remove(fpath)
if smb_31 is None:
return print('There is no RACMO file for this glacier ' + gdir.rgi_id)
else:
with ncDataset(fpath, 'w', format='NETCDF4') as nc:
nc.createDimension('time', None)
nc.author = 'B.M Recinos'
nc.author_info = 'Open Global Glacier Model'
timev = nc.createVariable('time', 'i4', ('time', ))
tatts = {'units': 'year'}
calendar = 'standard'
tatts['calendar'] = calendar
timev.setncatts(tatts)
timev[:] = smb_31.time
v = nc.createVariable('smb', 'f4', ('time', ))
v.units = 'mm w.e.'
v.long_name = 'surface mass balance'
v[:] = smb_31
v = nc.createVariable('prcp', 'f4', ('time', ))
v.units = 'mm w.e.'
v.long_name = 'total yearly precipitation amount'
v[:] = prcp_31
v = nc.createVariable('run_off', 'f4', ('time', ))
v.units = 'mm w.e.'
v.long_name = 'total yearly run off amount'
v[:] = run_off_31
v = nc.createVariable('snow_melt', 'f4', ('time', ))
v.units = 'mm w.e.'
v.long_name = 'total yearly snowmelt amount'
v[:] = melt_31
v = nc.createVariable('snow_fall', 'f4', ('time', ))
v.units = 'mm w.e.'
v.long_name = 'total yearly snowfall amount'
v[:] = fall_31