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scratchpad.py
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scratchpad.py
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import numpy as np
import matplotlib.pyplot as plt
import xarray as xray
import collections
import pandas as pd
import urllib2
from bs4 import BeautifulSoup
import atmos as atm
import merra
# ----------------------------------------------------------------------
# Save 200mb u, v daily data for one month
year = 1979
month = 1
datestr = '%d%02d' % (year, month)
savedir = '/home/jennifer/datastore/merra/daily/'
def filename(varname, datestr, savedir):
return savedir + 'merra_' + varname + '_' + datestr + '.nc'
u = merra.load_daily(year, month, 'u', subset_dict={'plev' : (200, 200)})
atm.save_nc(filename('u200', datestr, savedir), u)
v = merra.load_daily(year, month, 'v', subset_dict={'plev' : (200, 200)})
atm.save_nc(filename('v200', datestr, savedir), v)
# ----------------------------------------------------------------------
url = ('http://goldsmr3.sci.gsfc.nasa.gov/opendap/MERRA_MONTHLY/'
'MAIMCPASM.5.2.0/1979/MERRA100.prod.assim.instM_3d_asm_Cp.197907.hdf')
url2 = ('http://goldsmr2.sci.gsfc.nasa.gov/opendap/MERRA_MONTHLY/'
'MATMNXFLX.5.2.0/1979/MERRA100.prod.assim.tavgM_2d_flx_Nx.197907.hdf')
ds = xray.open_dataset(url)
ds2 = xray.open_dataset(url2)
u = ds['U']
v = ds['V']
q = ds['QV']
lat = get_coord(u, 'lat')
lon = get_coord(u, 'lon')
plev = get_coord(u, 'plev')
# Convert from (kg/m^2)/s to mm/day
SCALE = 60 * 60 * 24
precip = ds2['PRECTOT'] * SCALE
evap = ds2['EVAP'] * SCALE
mfc = av.moisture_flux_conv(u*q, v*q)
lon1, lon2 = 0, 150
lat1, lat2 = 0, 50
axlims = (lat1, lat2, lon1, lon2)
plt.figure(figsize=(7,8))
plt.subplot(211)
ap.pcolor_latlon(precip, cmap='hot_r', axlims=axlims)
plt.title('Total precip')
plt.subplot(212)
ap.pcolor_latlon(evap, cmap='hot_r', axlims=axlims)
plt.title('Evap')
plt.figure(figsize=(7,8))
plt.subplot(211)
ap.pcolor_latlon(precip - evap, axlims=axlims)
plt.title('Net precip')
plt.subplot(212)
ap.pcolor_latlon(mfc, axlims=axlims)
plt.title('MFC')
# ----------------------------------------------------------------------
# Sub-daily data (3-hourly and hourly for surface fluxes)
# Hourly precip
# url3 = ('http://goldsmr2.sci.gsfc.nasa.gov/opendap/MERRA/MAT1NXFLX.5.2.0/'
# '1979/07/MERRA100.prod.assim.tavg1_2d_flx_Nx.19790701.hdf')
# ds3 = xray.open_dataset(url3)
#
# precip = ds3['PRECTOT']