Пример #1
0
def testing(data, lat1, lat2, lon1, lon2, t, k):

    latname = get_coord(data, 'lat', 'name')
    lonname = get_coord(data, 'lon', 'name')

    data_sub = dat.subset(data, latname, lat1, lat2, lonname, lon1, lon2)

    plt.figure()
    ap.pcolor_latlon(data_sub[t, k],
                     axlims=(lat1, lat2, lon1, lon2),
                     cmap='jet')

    avg0 = data_sub.mean(axis=-1).mean(axis=-1)
    avg1 = mean_over_geobox(data, lat1, lat2, lon1, lon2, area_wtd=False)
    avg2 = mean_over_geobox(data, lat1, lat2, lon1, lon2, area_wtd=True)
    avg3 = mean_over_geobox(data,
                            lat1,
                            lat2,
                            lon1,
                            lon2,
                            area_wtd=True,
                            land_only=True)

    print(avg0[t, k].values)
    print(avg1[t, k].values)
    print(avg2[t, k].values)
    print(avg3[t, k].values)
def testing(data, lat1, lat2, lon1, lon2, t, k):

    latname = get_coord(data, 'lat', 'name')
    lonname = get_coord(data, 'lon', 'name')

    data_sub = dat.subset(data, latname, lat1, lat2, lonname, lon1, lon2)

    plt.figure()
    ap.pcolor_latlon(data_sub[t,k], axlims=(lat1,lat2,lon1,lon2), cmap='jet')

    avg0 = data_sub.mean(axis=-1).mean(axis=-1)
    avg1 = mean_over_geobox(data, lat1, lat2, lon1, lon2, area_wtd=False)
    avg2 = mean_over_geobox(data, lat1, lat2, lon1, lon2, area_wtd=True)
    avg3 = mean_over_geobox(data, lat1, lat2, lon1, lon2, area_wtd=True,
                            land_only=True)

    print(avg0[t, k].values)
    print(avg1[t, k].values)
    print(avg2[t, k].values)
    print(avg3[t, k].values)
Пример #3
0
# Correct for topography

u_orig = u
u = correct_for_topography(u_orig, topo)

m, k = 3, 1
plt.figure(figsize=(7, 8))
plt.subplot(211)
ap.pcolor_latlon(u_orig[m, k], cmap='jet')
plt.subplot(212)
ap.pcolor_latlon(u[m, k], cmap='jet')

# ----------------------------------------------------------------------
# Zonal mean zonal wind
season = 'jjas'
lon1, lon2 = 60, 100
cint = 5
months = utils.season_months(season)

uplot = dat.subset(u, 'lon', lon1, lon2, 'mon', months)
uplot = uplot.mean(['lon', 'mon'])

ps_plot = dat.subset(topo, 'lon', lon1, lon2)
ps_plot = ps_plot.mean('lon')

plt.figure()
ap.contour_latpres(uplot, clev=cint, topo=ps_plot)

plt.figure()
ap.contourf_latpres(uplot, clev=cint, topo=ps_plot)
u_orig = u
u = correct_for_topography(u_orig, topo)

m, k = 3, 1
plt.figure(figsize=(7,8))
plt.subplot(211)
ap.pcolor_latlon(u_orig[m,k], cmap='jet')
plt.subplot(212)
ap.pcolor_latlon(u[m,k], cmap='jet')


# ----------------------------------------------------------------------
# Zonal mean zonal wind
season='jjas'
lon1, lon2 = 60, 100
cint = 5
months = utils.season_months(season)

uplot = dat.subset(u, 'lon', lon1, lon2, 'mon', months)
uplot = uplot.mean(['lon', 'mon'])

ps_plot = dat.subset(topo, 'lon', lon1, lon2)
ps_plot = ps_plot.mean('lon')

plt.figure()
ap.contour_latpres(uplot, clev=cint, topo=ps_plot)

plt.figure()
ap.contourf_latpres(uplot,clev=cint, topo=ps_plot)