Question

我正在尝试使用cartopy或pyproj重新投影GOES16全盘映像。我想把它变成一个不同的投影。对于此示例，我尝试将其重新投影到Mercator。但是，当我运行代码时，我得到的数据的全球形图像不在Mercator投影中，并且没有任何Cartopy功能。我觉得我错过了一个简单的步骤，但无法弄清楚它到底是什么。下面是一个可复制的示例-我正在使用Python 3.5。

import matplotlib
import matplotlib.pyplot as plt
from siphon.catalog import TDSCatalog, get_latest_access_url
import numpy as np
from datetime import datetime, timedelta
import cartopy.crs as ccrs
import cartopy.feature as cfeature

# query data
nowdate = datetime.utcnow()
cat = TDSCatalog('http://thredds-jumbo.unidata.ucar.edu/thredds/catalog/satellite/goes16/GOES16/Products/SeaSurfaceTemperature/FullDisk/' + \
                  str(nowdate.year) + str("%02d"%nowdate.month) + str("%02d"%nowdate.day) + '/catalog.xml')
dataset_name = sorted(cat.datasets.keys())[-1]
dataset = cat.datasets[dataset_name]

# load netcdf and read variables
nc = dataset.remote_access()
sst = np.array(nc.variables['SST'][:,:])
sst[np.isnan(sst)] = -1
sst = np.ma.array(sst)
sst[sst < 0] = np.ma.masked

X = nc.variables['x'][:]
Y = nc.variables['y'][:]

# define projections
proj_var = nc.variables['goes_imager_projection']
globe = ccrs.Globe(ellipse='sphere', semimajor_axis=proj_var.semi_major_axis,
                   semiminor_axis=proj_var.semi_minor_axis)

# define reprojection target
proj = ccrs.Mercator(central_longitude=proj_var.longitude_of_projection_origin, 
                     latitude_true_scale=proj_var.latitude_of_projection_origin,
                     globe=globe)

# Plot
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(1, 1, 1, projection=proj)
ax.coastlines(resolution='50m', color='black')
ax.add_feature(cfeature.STATES, linestyle=':', edgecolor='black')
ax.add_feature(cfeature.BORDERS, linewidth=2, edgecolor='black')
im = ax.imshow(sst, extent=(X.min(), X.max(), Y.min(), Y.max()), origin='upper')


# try again, this time with pyproj
from pyproj import Proj     
p = Proj(proj='geos', h=proj_var.perspective_point_height, lon_0=proj_var.longitude_of_projection_origin, sweep=proj_var.sweep_angle_axis)

X = nc.variables['x'][:] * proj_var.perspective_point_height
Y = nc.variables['y'][:] * proj_var.perspective_point_height
XX, YY = np.meshgrid(X,Y)
lons, lats = p(XX, YY, inverse=True)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(1, 1, 1, projection=proj)
ax.coastlines(resolution='50m', color='black')
ax.add_feature(cfeature.STATES, linestyle=':', edgecolor='black')
ax.add_feature(cfeature.BORDERS, linewidth=2, edgecolor='black')
im = ax.imshow(sst, extent=(lons.min(), lons.max(), lats.min(), lats.max()), origin='upper')

Answer 1

您的方法是正确的，但是您必须使用pcolormesh而不是imshow。

这应该有效：

from datetime import datetime
import cartopy.feature as cfeature
from siphon.catalog import TDSCatalog
import matplotlib.pyplot as plt
from matplotlib import patheffects
import metpy
from metpy.plots import colortables
import xarray as xr
from xarray.backends import NetCDF4DataStore

%matplotlib inline

nowdate = datetime.utcnow()
cat = TDSCatalog('http://thredds-jumbo.unidata.ucar.edu/thredds/catalog/satellite/goes16/GOES16/Products/SeaSurfaceTemperature/FullDisk/' + \
                  str(nowdate.year) + str("%02d"%nowdate.month) + str("%02d"%nowdate.day) + '/catalog.xml')
dataset_name = sorted(cat.datasets.keys())[-1]
dataset = cat.datasets[dataset_name]
ds = dataset.remote_access(service='OPENDAP')
ds = NetCDF4DataStore(ds)
ds = xr.open_dataset(ds)


dqf = ds.metpy.parse_cf('DQF')
dat = ds.metpy.parse_cf('SST')
proj = dat.metpy.cartopy_crs

dat = dat.where(dqf == 0)
dat = dat.where(dat.variable > 274)
dat = dat.where(dat.variable < 310)
dat = dat - 273.15
# Plot in Mercator
import cartopy.crs as ccrs
newproj = ccrs.Mercator()


fig = plt.figure(figsize=[12, 12], dpi=100)
ax = fig.add_subplot(1,1,1, projection=newproj)
im = ax.pcolormesh(dat['x'], dat['y'], dat, cmap='jet', transform=proj, vmin=-2, vmax=38)
ax.set_extent((dat['x'].min() + 4000000, dat['x'].max()- 3200000, dat['y'].min()+ 5500000, dat['y'].max()- 650000), crs=proj)

用Cartopy和Pyproj重新投影GOES16卫星数据

1 个答案: