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python读取gpm卫星降水并绘制降水分布图

2019-07-21  本文已影响0人  zengsk

引言

好久好久没有更新了,来杭州的这几天真的是快把人烤熟了,好在学校的空调给力,连厕所都是中央空调,有钱真的会玩呀......

继上一篇博客《Python处理GPM(IMERG/GSMaP)卫星降水数据》 下面说说如何利用python读取GPM IMERG降水数据并绘制降水分布图

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @File   : gpm_mapping.py
# @Author : zengsk in HHU
# @Time   : 2019/7/21 13:40

import h5py
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from netCDF4 import Dataset as ncdataset
from mpl_toolkits.basemap import Basemap

####### 绘制GPM日降水分布图  ###########
'''
自定义色带(可替换 map.contourf()函数的cmap参数) 
ps:我自己定义的实在难看,还是用自带的吧^-^
'''
def colormap():
    ColorList = ['#DDDDFF','#7D7DFF','#0000C6','#000079','#CEFFCE',
                 '#28FF28','#007500','#FFFF93','#8C8C00','#FFB5B5',
                 '#FF0000','#CE0000','#750000']
    return mpl.colors.LinearSegmentedColormap.from_list('cmap', ColorList, 256)


filename = r'../assets/3B-DAY.MS.MRG.3IMERG.20001026-S000000-E235959.V06.nc4'

# 这部分是读取小时分辨率数据的代码
# fHander = h5py.File(filename, mode='r')
# precip = fHander['/Grid/precipitationCal'][:]
# precip = np.transpose(precip * 0.5)
# lat = fHander['/Grid/lat'][:]
# lon = fHander['/Grid/lon'][:]

dst = ncdataset(filename)
precip = dst.variables['precipitationCal'][:]
precip = precip.reshape(3600, 1800)
precip = np.transpose(precip)
precip[np.isnan(precip)] = -999

lat = dst.variables['lat'][:]
lon = dst.variables['lon'][:]

# Plot the figure, define the geographic bounds
fig = plt.figure(3, dpi=300)
map = Basemap()
# Draw coastlines, state and country boundaries, edge of map.
map.drawcoastlines(linewidth=1.2, linestyle='solid', color='k', antialiased=3)
map.drawcountries(linewidth=0.8, linestyle='solid', color='k', antialiased=3)
# map.bluemarble(scale=3) # 加载蓝色大理石背景
# map.shadedrelief(scale=2) # 加载地形阴影
# map.etopo(scale=3) # 加载地形包括海洋

# Draw filled contours.
clevs = np.arange(0, 100, 10)
# color scale changing
# clevs = [0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]

# Define the latitude and longitude data
x, y = np.float32(np.meshgrid(lon, lat))
# Mask the values less than 0 because there is no data to plot.
masked_array = np.ma.masked_where(precip < 0, precip)
# Plot every masked value as white

# colormap
cmap = plt.cm.get_cmap('jet')
cmap.set_bad('w', .8)

# Plot the data
cs = map.contourf(x, y, precip, clevs, cmap=cmap, latlon=True)
parallels = np.arange(-60., 61, 20.)
map.drawparallels(parallels, labels=[True, False, True, False])
meridians = np.arange(-180., 180., 60.)
map.drawmeridians(meridians, labels=[False, False, False, True])
# 设置标题和字体
plt.title('GPM IMERG Daily Rainfall( mm )')
font = {'weight': 'bold', 'size': 6}
plt.rc('font', **font)
# 加载色带
cbar = map.colorbar(cs, location='right', pad="5%")
cbar.set_label('mm/daily')
plt.savefig('../output/gpm.jpg', dpi=300)  # change to your directory
plt.show()
print(" ###### 数据处理完成 ###### ")

结果展示:

image.png

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