/
mary_soil_model.py
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/
mary_soil_model.py
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import os
import os.path
import numpy as np
import numpy.ma as ma
from datetime import datetime
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import maskoceans
from matplotlib.ticker import FuncFormatter
import netCDF4
from timutils import midpt_norm, scinot_format
from stem_pytools import STEM_parsers as sp
from stem_pytools import na_map
def draw_crop_pct(fname_crop_pct, map_obj, mask = None):
nc = netCDF4.Dataset(fname_crop_pct)
pct = nc.variables['crop_pct'][...].squeeze()
nc.close()
if mask is not None:
pct = ma.masked_where(mask, pct)
# pct = sp.parse_STEM_var(fname_crop_pct, varname='crop_pct')
lon, lat, topo = sp.parse_STEM_coordinates(
os.path.join(os.environ['SARIKA_INPUT'], 'TOPO-124x124.nc'))
cm = map_obj.map.pcolormesh(lon, lat, pct,
cmap=plt.get_cmap('Blues'),
vmin=0.0,
vmax=1.0,
latlon=True)
cb = plt.colorbar(cm, ax=map_obj.ax_map)
cb.solids.set_edgecolor("face")
def get_hybrid_fsoil(fname_hybrid_fsoil):
fsoil_JA = sp.parse_STEM_var(fname_hybrid_fsoil,
t0=datetime(2008, 7, 1),
t1=datetime(2008, 8, 31,
23, 59, 59),
varname='fsoil')
s_per_tstamp = 6 * 60 * 60 # six hours expressed as seconds
mol_per_pmol = 1e-12
n_months = 2
fsoil_itgd = np.sum(fsoil_JA['data'] * mol_per_pmol * s_per_tstamp,
axis=0) / n_months
return(fsoil_itgd.squeeze())
def get_WRF_Tsoil_VWC(fname_wrf):
"""obtain WRF soil T and soil moisture. soil T is masked below 10 C
because Mary's soil flux model fitting data went no lower..
"""
vwc = sp.parse_STEM_var(nc_fname=fname_wrf, varname='SMOIS')
Tsoil = sp.parse_STEM_var(nc_fname=fname_wrf, varname='TSOIL')
ten_C = 273.15 + 10 # 10 C expressed in Kelvins
Tsoil['data'] = ma.masked_less(Tsoil['data'], ten_C)
return(vwc, Tsoil)
def calc_fsoil(vwc, Tsoil):
"""implement Mary Whelan's soil COS flux model described in her email
of 5 Feb 2015.
INPUTS
vwc: soil volumetric water content [fraction]
Tsoil: soil temperature [k]
OUTPUTS:
fsoil: soil COS flux [pmol/m2/sec]
"""
fsoil = (vwc * -28.77873448 + (Tsoil * 0.88867741) - 252.76497309)
return(fsoil)
def integrate_mary_fsoil(fsoil, s_per_tstamp):
"""
convert COS flux from pmol m-2 s-1 to mol m-2
"""
mol_per_pmol = 1e-12
n_months = 2 # July and Aug
fsoil_itgd = np.sum(fsoil * mol_per_pmol * s_per_tstamp,
axis=0)
fsoil_itgd = (fsoil_itgd / n_months).squeeze()
return(fsoil_itgd)
def get_kettle_soil(fname_kettle_fcos):
s_per_tstamp = 60 * 60 * 24 # one day expressed as seconds
n_months = 2 # July and Aug
fsoil_k = sp.parse_STEM_var(fname_kettle_fcos,
t0=datetime(2008, 7, 1),
t1=datetime(2008, 8, 31, 23, 59, 59),
varname='cos')
fsoil_k['data'] = ma.masked_invalid(fsoil_k['data'])
# convert mol m-2 s-1 to mol m-2 mon-1
fsoil_k_itgd = np.sum(fsoil_k['data'] * s_per_tstamp, axis=0)
fsoil_k_itgd = (fsoil_k_itgd / n_months).squeeze()
return(fsoil_k_itgd)
def calc_ratio(fsoil_mary, fsoil_kettle):
lon, lat, topo = sp.parse_STEM_coordinates(
os.path.join(os.environ['SARIKA_INPUT'], 'TOPO-124x124.nc'))
fsoil_mary = maskoceans(lon, lat, fsoil_mary)
fsoil_kettle = maskoceans(lon, lat, fsoil_kettle)
ratio = ma.masked_invalid(fsoil_kettle) / ma.masked_invalid(fsoil_mary)
return(ratio)
def draw_ratio(map, ratio):
lon, lat, topo = sp.parse_STEM_coordinates(
os.path.join(os.environ['SARIKA_INPUT'], 'TOPO-124x124.nc'))
ratio = maskoceans(lon, lat, ratio)
ratio_norm = midpt_norm.MidpointNormalize(midpoint=1.0)
cm = map.map.pcolor(lon, lat, ratio,
vmin=-7, # np.percentile(ratio, 1),
vmax=9, # np.percentile(ratio, 99),
cmap=plt.get_cmap('PuOr'),
norm=ratio_norm,
latlon=True)
cb = plt.colorbar(cm, ax=map.ax_map, extend='both',
ticks=np.arange(-7, 9, 2))
cb.solids.set_edgecolor("face")
def draw_fsoil(map, fsoil, vmin, vmax):
pmol_per_mol = 1e12
fsoil = fsoil * pmol_per_mol
vmin = vmin * pmol_per_mol
vmax = vmax * pmol_per_mol
lon, lat, topo = sp.parse_STEM_coordinates(
os.path.join(os.environ['SARIKA_INPUT'], 'TOPO-124x124.nc'))
fsoil = maskoceans(lon, lat, fsoil)
norm = midpt_norm.MidpointNormalize(midpoint=0.0)
cm = map.map.pcolor(lon, lat, fsoil,
vmin=vmin, # np.nanmin(fsoil),
vmax=vmax, # np.nanmax(fsoil),
norm=norm,
cmap=plt.get_cmap('RdGy_r'),
latlon=True)
cb = plt.colorbar(cm, ax=map.ax_map, extend='both',
format=FuncFormatter(scinot_format.scinot_format))
cb.solids.set_edgecolor("face")
cb.ax.set_title('pmol COS m$^{-2}$ mon$^{-1}$',
fontdict={'fontsize': 8})
def draw_fsoil_maps(fsoil_mary, fsoil_kettle, fsoil_hybrid):
# NAMapFigure arguments to zoom map on the Eastern USA
E_USA = {'lon_0': -88.6275,
'lat_0': 37.0722,
'mapwidth': 3e6,
'mapheight': 2.5e6}
kwargs = E_USA
kwargs = {}
fig, ax = plt.subplots(nrows=1, ncols=5, figsize=(24, 6))
map_m = na_map.NAMapFigure(t_str="Mary's COS F$_{soil}$",
map_axis=ax[0],
cb_axis=None,
**kwargs)
map_k = na_map.NAMapFigure(t_str="Kettle's COS F$_{soil}$",
map_axis=ax[1],
cb_axis=None,
**kwargs)
map_h = na_map.NAMapFigure(t_str="'hybrid' COS F$_{soil}$",
map_axis=ax[2],
cb_axis=None,
**kwargs)
map_c = na_map.NAMapFigure(t_str=("cropland fraction\n"
"[Ramankutty et al (2008)]"),
map_axis=ax[3],
cb_axis=None,
**kwargs)
map_r2 = na_map.NAMapFigure(t_str="Kettle's F$_{soil}$ / "
"hybrid F$_{soil}$",
map_axis=ax[4],
cb_axis=None,
**kwargs)
draw_crop_pct(os.path.join(
os.environ['SARIKA_INPUT'],
'Cropland_pct',
'Ramankutty_etal_Cropland2000_pct_124x124_IOAPI.nc'),
map_c,
mask=np.logical_or(fsoil_kettle.mask, fsoil_mary.mask))
vmin = np.nanmin(np.ma.vstack((fsoil_kettle,
fsoil_hybrid)).flatten())
vmax = np.nanmax(np.ma.vstack((fsoil_kettle,
fsoil_hybrid)).flatten())
draw_fsoil(map_m, fsoil_mary, vmin, vmax)
draw_fsoil(map_k, fsoil_kettle, vmin, vmax)
draw_fsoil(map_h, fsoil_hybrid, vmin, vmax)
# draw_fsoil(map_m, fsoil_mary, np.nanmin(fsoil_kettle), 6e-5)
# draw_fsoil(map_k, fsoil_kettle, np.nanmin(fsoil_kettle), 6e-5)
ratio1 = calc_ratio(fsoil_mary, fsoil_kettle)
ratio2 = calc_ratio(fsoil_hybrid, fsoil_kettle)
draw_ratio(map_r2, ratio2)
return(fig, map_m, map_k, map_h, map_c, map_r2, ratio1, ratio2)
if __name__ == "__main__":
s_per_6hrs = 6 * 60 * 60 # six hours expressed in seconds
fname_wrf = os.path.join(os.environ['SARIKA_INPUT'],
'soil_T_moisture_JulAug.nc')
vwc, Tsoil = get_WRF_Tsoil_VWC(fname_wrf)
fsoil = calc_fsoil(vwc['data'], Tsoil['data'])
fsoil_itgd = integrate_mary_fsoil(fsoil, s_per_6hrs)
fsoil_k_itgd = get_kettle_soil(os.path.join(
os.environ['SARIKA_INPUT'],
'surfem-124x124-kettle-soil-cos_2008_2009.nc'))
fsoil_hybrid_itgd = get_hybrid_fsoil(os.path.join(
os.environ['SARIKA_INPUT'],
'whelan_kettle_hybrid_fsoil_124x124.nc'))
fsoil_hybrid_itgd = ma.masked_where(np.logical_or(fsoil_k_itgd.mask,
fsoil_itgd.mask),
fsoil_hybrid_itgd)
plt.close('all')
fig, map_m, map_k, map_h, map_r1, map_r2, ratio1, ratio2 = draw_fsoil_maps(
fsoil_itgd,
fsoil_k_itgd,
fsoil_hybrid_itgd)
fig.savefig('/tmp/soil_model_maps.png')