def get_filenames(datadir, varnm, onset_nm, years, lon1, lon2, nroll):
if nroll is not None:
varnm = varnm + '_nroll%d' % nroll
lonstr = atm.latlon_str(lon1, lon2, 'lon')
yearstr = '_%d-%d.nc' % (min(years), max(years))
filestr = datadir + 'merra_%s_reg_%s_onset_' + onset_nm + yearstr
filenames = {}
filenames['latlon'] = filestr % (varnm, 'latlon')
filenames['sector'] = filestr % (varnm, lonstr)
return filenames
def get_filenames(datadir, varnms, onset_nm, years, lon1, lon2, nroll):
lonstr = atm.latlon_str(lon1, lon2, 'lon')
yearstr = '_%d-%d.nc' % (min(years), max(years))
filestr = datadir + 'merra_%s'
if nroll is not None:
filestr = filestr + '_nroll%d' % nroll
filestr = filestr + '_reg_%s_onset_' + onset_nm + yearstr
filestr2 = datadir + 'merra_%s_dailyrel_' + onset_nm + yearstr
filenames = {}
for varnm in varnms:
filenames[varnm] = {'latlon_reg' : filestr % (varnm, 'latlon'),
'sector_reg' : filestr % (varnm, lonstr),
'latlon_clim' : filestr2 % varnm,
'sector_clim' : filestr2 % varnm}
return filenames
def sector_mean(var, lon1, lon2):
"""Return the sector mean of a variable."""
name = var.name
lonstr = atm.latlon_str(lon1, lon2, 'lon')
if (lon2 - lon1) == 360:
lon1, lon2 = None, None
name_out = name + '_ZON'
else:
name_out = name + '_SEC'
varbar = atm.dim_mean(var, 'lon', lon1, lon2)
varbar.name = name_out
varbar.attrs['varnm'] = name
varbar.attrs['lonstr'] = lonstr
varbar.attrs['filestr'] = '%s_sector_%s' % (name, lonstr)
return varbar
with xray.open_dataset(files[nm]) as ds:
data[nm] = ds[nm].load()
lat = atm.get_coord(data, 'lat')
lon = atm.get_coord(data, 'lon')
psfile = atm.homedir() + 'dynamics/python/atmos-tools/data/topo/ncep2_ps.nc'
ps = atm.get_ps_clim(lat, lon, psfile)
ps = ps / 100
figsize = (7, 9)
omitzero = False
for ssn in ['ANN', 'DJF', 'JJA', 'MAR']:
for lonlims in [(0, 360), (60, 100)]:
lon1, lon2 = lonlims
lonstr = atm.latlon_str(lon1, lon2, 'lon')
suptitle = ssn + ' ' + lonstr
months = atm.season_months(ssn)
v = data['V'].sel(month=months)
if (lon2 - lon1) < 360:
v = atm.subset(v, {'lon' : (lon1, lon2)})
sector_scale = (lon2 - lon1) / 360.0
psbar = atm.dim_mean(ps, 'lon', lon1, lon2)
clev = 10
else:
sector_scale = None
psbar = atm.dim_mean(ps, 'lon')
clev = 20
vssn = v.mean(dim='month')
vssn_bar = atm.dim_mean(vssn, 'lon')
psi1 = atm.streamfunction(vssn, sector_scale=sector_scale)
def get_savefile(version, savedir, varnm, onset_nm, ind_nm, year):
filenm = savedir + version + '_%s_dailyrel' % varnm
if ind_nm == 'retreat':
filenm = filenm + '_retreat'
filenm = filenm + '_%s_%d.nc' % (onset_nm, year)
return filenm
# Lat-lon data files
datafiles = collections.OrderedDict()
for nm in varnms:
datafiles[nm] = [yrlyfile(version, datadir, nm, yr) for yr in years]
# Zonal and sector mean data
for lonlims in [(0, 360), (60, 100)]:
lonstr = atm.latlon_str(lonlims[0], lonlims[1], 'lon')
subset1 = 'sector_' + lonstr
for nm in sector_varnms:
key = nm + '_' + subset1
datafiles[key] = [yrlyfile(version, datadir, nm, yr, subset1)
for yr in years]
# ----------------------------------------------------------------------
# Onset index for each year
with xray.open_dataset(indfile) as index:
index.load()
onset = index['onset']
retreat = index['retreat']
# ----------------------------------------------------------------------
def savefile(version, savedir, year, ndays, lon1, lon2, plev):
lonstr = atm.latlon_str(lon1, lon2, 'lon')
filenm = savedir + version + '_ubudget%d_ndays%d_%s_%d.nc'
filenm = filenm % (plev, ndays, lonstr, year)
return filenm
def latlon_filestr(lat1, lat2, lon1, lon2):
"""Return nicely formatted string for lat-lon range."""
latstr = atm.latlon_str(lat1, lat2, 'lat')
lonstr = atm.latlon_str(lon1, lon2, 'lon')
return lonstr + '_' + latstr
with xray.open_dataset(files[nm]) as ds:
data[nm] = ds[nm].load()
lat = atm.get_coord(data, 'lat')
lon = atm.get_coord(data, 'lon')
psfile = atm.homedir() + 'dynamics/python/atmos-tools/data/topo/ncep2_ps.nc'
ps = atm.get_ps_clim(lat, lon, psfile)
ps = ps / 100
figsize = (7, 9)
omitzero = False
for ssn in ['ANN', 'DJF', 'JJA', 'MAR']:
for lonlims in [(0, 360), (60, 100)]:
lon1, lon2 = lonlims
lonstr = atm.latlon_str(lon1, lon2, 'lon')
suptitle = ssn + ' ' + lonstr
months = atm.season_months(ssn)
v = data['V'].sel(month=months)
if (lon2 - lon1) < 360:
v = atm.subset(v, {'lon': (lon1, lon2)})
sector_scale = (lon2 - lon1) / 360.0
psbar = atm.dim_mean(ps, 'lon', lon1, lon2)
clev = 10
else:
sector_scale = None
psbar = atm.dim_mean(ps, 'lon')
clev = 20
vssn = v.mean(dim='month')
vssn_bar = atm.dim_mean(vssn, 'lon')
psi1 = atm.streamfunction(vssn, sector_scale=sector_scale)