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PYTHON：在底图上覆盖netCDF数据（contourf）

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我是python和netCDF的新手，但是现在已经在以下问题上工作了几天而没有任何进展 . 我的代码基于我读过的各种教程和示例，我无法弄清楚出了什么问题！

基本上我希望能够将一些netCDF数据的图叠加到底图上 . 我的代码（完整）如下：

import numpy as np
from netCDF4 import Dataset
# from scipy.io import netcdf
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap

when = 0 # improve this variable later so that user input can be date/ time

filename = '/net/glusterfs_surft/surft/data/LakeData/JRA55/raw/jra55_tmp.1964010100_1964123121.nc' # input the complete filepath here
# open the file at the address 'filename' for reading:
fopen = Dataset(filename, 'r') # <-- turn on if using netCDF4
# fopen = netcdf.netcdf_file(filename, 'r') <-- turn on if using scipy.io

# variables in JRA-55 are:
# TMP_GDS0_HTGL
# initial_time0_hours
# initial_time0_encoded
# initial_time0
# g0_lon_2 (runs from 0 to 360E in 1.25 deg steps)
# g0_lat_1 (runs from 90 to -90 in 1.25 deg steps)

# now set variables x, y and 'data':
x = fopen.variables['g0_lon_2'][:] # this is a 1D longitude array
y = fopen.variables['g0_lat_1'][:] # this is a 1D latitude array 
data = fopen.variables['TMP_GDS0_HTGL'][:] 
# this is a 3D array with temperature saved at each point in 2D space and time
# reduce data to a 2D array for a specific time:
data_when = data[when,:,:]

#close the file at the address
fopen.close()

# create a basemap to plot onto:
m = Basemap(width=5000000, height=3500000,\
        resolution='l', projection='stere',\
        lat_ts=40, lat_0=50, lon_0=0)
m.drawcoastlines()
m.drawparallels(np.arange(-80.,81,20))
m.drawmeridians(np.arange(-180.,181,20))
# 
#   add other basemap drawing options here 
#

# convert 1D matrices into 2D fill matrices for processing:
xx, yy = np.meshgrid(x, y)

plt.contourf(xx, yy, data_when, latlon=True)

plt.show()

如果我注释掉底图部分，那么我的数据如下所示：

world map, no borders, temperature contours

如果我包括它们（不需要注释 plt.contourf(xx, yy, data_when, latlon=True) ），我得到的图像是：

stereographic projection at lat = 50, lon = 0, with borders, no contours

我希望能够在一个图中显示这些图像的相应部分，但不知道如何 . 使用的 Map 投影不重要，但图像应对应于数据和底图 .

谢谢！希望你能帮忙！

python netcdf matplotlib-basemap

1 回答

  • 0

    以下版本的代码功能齐全 . 感谢sea_hydro在评论中提供的帮助 . 我希望代码的工作版本对希望解决这个问题的其他新手有用！

    import numpy as np
from netCDF4 import Dataset
# from scipy.io import netcdf
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap

when = 0 # improve this variable later so that user input can be date/ time

filename = 'some_filepath' # input the complete filepath here
# open the file at the address 'filename' for reading:
fopen = Dataset(filename, 'r') # <-- turn on if using netCDF4
# fopen = netcdf.netcdf_file(filename, 'r') <-- turn on if using scipy.io

# now set variables x, y and 'data':
x = fopen.variables['lon_var'][:] # this is a 1D longitude array
y = fopen.variables['lat_var'][:] # this is a 1D latitude array 
data = fopen.variables['data_var'][:] 
# this is a 3D array with a value saved at each point in 2D space and time
# reduce data to a 2D array for a specific time:
data_when = data[when,:,:]

#close the file at the address
fopen.close()

# create a basemap to plot onto:
m = Basemap(width=10000000, height=7000000,\
        resolution='l', projection='stere',\
        lat_ts=40, lat_0=50, lon_0=0)
m.drawcoastlines()
m.drawparallels(np.arange(-80.,81,20))
m.drawmeridians(np.arange(-180.,181,20))
# 
#   add other basemap drawing options here 
#

    此代码使用立体 Map 投影 . 其他底图选项可以找到in the matlpotlib basemap toolkit documentation

    # convert 1D matrices into 2D fill matrices for processing:
xx, yy = np.meshgrid(x, y)
xx, yy = m(xx, yy)
plt.contourf(xx, yy, data_when)

plt.show()

    其他图也可以叠加 .

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