import numpy as np import xray import pandas as pd import matplotlib.pyplot as plt import atmos as atm import merra from indices import onset_SJKE, summarize_indices, plot_index_years # ---------------------------------------------------------------------- # Compute SJ indices (Boos and Emmanuel 2009) datadir = atm.homedir() + 'datastore/merra/daily/' years = np.arange(1979, 2015) filestr = 'merra_uv850_40E-120E_60S-60N_' datafiles = [datadir + filestr + '%d.nc' % y for y in years] # Read daily data from each year ds = atm.combine_daily_years(['U', 'V'], datafiles, years) # Remove extra dimension from data u = atm.squeeze(ds['U']) v = atm.squeeze(ds['V']) # Calculate OCI index sjke = onset_SJKE(u, v) # Summary plot and timeseries in individual years summarize_indices(years, sjke['onset']) plot_index_years(sjke, suptitle='SJ', yearnm='Year', daynm='Day')
precip_jan)
# ----------------------------------------------------------------------
# OCI index (Wang et al 2009) and SJKE index (Boos and Emmanuel 2009)
ds = atm.combine_daily_years(['U', 'V'], ocifiles, years)
ds = ds.rename({'Year' : 'year', 'Day' : 'day'})
u850 = atm.squeeze(ds['U'])
v850 = atm.squeeze(ds['V'])
# OCI Index
index['OCI'] = indices.onset_OCI(u850, yearnm='year', daynm='day')
index['OCI'].attrs['title'] = 'OCI'
# SJKE Index
index['SJKE'] = indices.onset_SJKE(u850, v850, yearnm='year', daynm='day')
index['SJKE'].attrs['title'] = 'SJKE'
# ----------------------------------------------------------------------
# TT index (Goswami et al 2006)
# *** NOTES ****
# Need to trouble shoot TT index before using in anything final.
# See testing/testing-indices-onset_TT.py for details.
# Select vertical pressure level to use, or None to use 200-600mb
# vertical mean
plev = None
# Read daily data from each year
if plev is None:
