def get_onset_indices(onset_nm, datafiles, years, data=None):
"""Return monsoon onset/retreat/length indices.
"""
# Options for CHP_MFC and CHP_PCP
lat1, lat2 = 10, 30
lon1, lon2 = 60, 100
chp_opts = [None, lat1, lat2, lon1, lon2]
if onset_nm == 'HOWI':
maxbreak = 10
npts = 100
ds = atm.combine_daily_years(['uq_int', 'vq_int'], datafiles, years,
yearname='year')
index, _ = indices.onset_HOWI(ds['uq_int'], ds['vq_int'], npts,
maxbreak=maxbreak)
index.attrs['title'] = 'HOWI (N=%d)' % npts
elif onset_nm == 'CHP_MFC':
if data is None:
tseries = get_mfc_box(datafiles, None, None, years, *chp_opts)
data = tseries['MFC_ACC']
index['ts_daily'] = tseries['MFC']
index = indices.onset_changepoint(data)
elif onset_nm == 'CHP_PCP':
if data is None:
tseries = get_mfc_box(None, datafiles, None, years, *chp_opts)
data = tseries['PCP_ACC']
index = indices.onset_changepoint(data)
index['ts_daily'] = tseries['PCP']
# Monsoon retreat and length indices
if 'retreat' in index:
index['length'] = index['retreat'] - index['onset']
else:
index['retreat'] = np.nan * index['onset']
index['length'] = np.nan * index['onset']
return index
# ----------------------------------------------------------------------
def saveclose(name, isave, exts):
if isave:
for ext in exts:
atm.savefigs(name, ext)
plt.close('all')
# ----------------------------------------------------------------------
# HOWI index (Webster and Fasullo 2003)
maxbreak = 10
ds = atm.combine_daily_years(['uq_int', 'vq_int'], vimtfiles, years,
yearname='year')
ds_howi = {}
for npts in [50, 100]:
howi, ds_howi[npts] = indices.onset_HOWI(ds['uq_int'], ds['vq_int'], npts,
maxbreak=maxbreak)
howi.attrs['title'] = 'HOWI (N=%d)' % npts
index['HOWI_%d' % npts] = howi
# ----------------------------------------------------------------------
# Wang & LinHo method
def get_onset_WLH(years, days, pcp_sm, threshold, titlestr, pentad=True,
pcp_jan=None):
nyears = len(years)
i_onset = np.zeros(nyears)
i_retreat = np.zeros(nyears)
i_peak = np.zeros(nyears)
for y, year in enumerate(years):
vals = indices.onset_WLH_1D(pcp_sm[y], threshold, precip_jan=pcp_jan)
i_onset[y], i_retreat[y], i_peak[y] = vals
lat1, lat2 = -20, 30
lon1, lon2 = 40, 100
with xray.open_dataset(datafile) as ds:
uq_int = ds['uq_int'].load()
vq_int = ds['vq_int'].load()
npts = 100
#npts = 50
pre_days = 'May 18-24'
post_days = 'June 8-14'
namestr = 'HOWI_%dpts_' % npts
exts = ['png', 'eps']
isave = True
howi, ds = onset_HOWI(uq_int, vq_int, npts)
# ----------------------------------------------------------------------
# MAPS
# ----------------------------------------------------------------------
# Plot climatological VIMT composites
lat = atm.get_coord(ds, 'lat')
lon = atm.get_coord(ds, 'lon')
x, y = np.meshgrid(lon, lat)
axlims = (lat1, lat2, lon1, lon2)
plt.figure(figsize=(12,10))
plt.subplot(221)
m = atm.init_latlon(lat1, lat2, lon1, lon2)
m.quiver(x, y, ds['uq_bar_pre'], ds['vq_bar_pre'])
plt.title(pre_days + ' VIMT Climatology')
plt.subplot(223)
