MetPy是一个Python工具集合库，用于阅读、可视化和执行天气数据的计算。
本文介绍如何在python中通过metpy计算水汽通量散度。
数据：
- 1、比湿数据
- 2、风速分量U
- 3、风速分量V
主要函数：
- 1、metpy.calc.divergence(u, v, *, dx=None, dy=None, x_dim=- 1, y_dim=- 2)
计算矢量的水平散度。 - 2、metpy.calc.lat_lon_grid_deltas(longitude, latitude, x_dim=- 1, y_dim=- 2, geod=None)计算纬度/经度格式的网格点之间的实际增量。
注意点
- 1、使用merpy计算过程中需要带上单位
- 2、最好先选取部分区域进行测试，然后再对全球进行循环
- 3、注意及时保存数据，避免浪费时间
- 4、数据的分辨率保持一致
代码：
# -*- coding: utf-8 -*- """ introduction : keep learning althongh walk slowly """ # # # import package import xarray as xr import numpy as np from metpy import units import metpy.constants as constants import metpy.calc as mpcalc # # # read data p1=r'D:/sph.nc' p2=r'D:/u.nc' p3=r'D:/v.nc' f_u = xr.open_dataset(p2) f_v = xr.open_dataset(p3) f_q = xr.open_dataset(p1) # # # read variables u = f_u.u v = f_v.v q = f_q.q lat = q.lat lon = q.lon lev = q.level time=q.time # # # qv_u = u*q/constants.g qv_v = v*q/constants.g # # # dx, dy = mpcalc.lat_lon_grid_deltas(lon, lat) div_qv = np.zeros((q.time.shape[0],lev.shape[0],lat.shape[0],lon.shape[0])) for j in range(q.time.shape[0]): print(j) for i in range(lev.shape[0]): div_qv[j,i] = mpcalc.divergence(u = qv_u[j,i],v = qv_v[j,i],dx = dx ,dy = dy) # # # 计算整层水汽通量散度 total_div_qv = np.trapz(div_qv[::-1],lev[::-1],axis=1) # # # save data div_qv_nc = xr.Dataset( { "mfd":(("time",'level',"lat","lon"), div_qv) }, coords={ 'level':lev, "time":time, "lat":lat, "lon":lon, } ) div_qv_nc.attrs["long_name"] = "div-qv" div_qv_nc.to_netcdf("qiv-qv.nc") total_qv_nc = xr.Dataset( { "total_mfd":(("time","lat","lon"), total_div_qv) }, coords={ "time":time, "lat":lat, "lon":lon, } ) total_qv_nc.attrs["long_name"] = "total-div-qv" total_qv_nc.to_netcdf("total-qiv-qv.nc")
一个努力学习python的海洋 水平有限，欢迎指正！！！ 欢迎评论、收藏、点赞、转发、关注。 关注我不后悔，记录学习进步的过程~~
