NSIDC海冰运动产品-速度矢量场图绘制（数据下载和处理--年、季节平均）【python/basemap】

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已于 2022-11-24 14:43:27 修改 · 2.7k 阅读

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于 2022-11-18 08:37:38 首次发布

本文介绍了一种使用Python绘制北极海冰运动矢量图的方法。通过定义一个类Sim1来处理海冰运动数据，并利用Basemap库绘制不同季节的平均海冰运动矢量图。

【总代码】（简易好理解版本，最后面还有个小升级版）

【总代码】（简易好理解版本，最后面还有个小升级版）

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
import netCDF4 as nc
from pyproj import Proj
import datetime as dt
import xarray as xr
import datetime as dt

class Sim1(object):
    def __init__(self,file_nc):
        self.file_obj = xr.open_dataset(file_nc)

        pass

    def Draw_vector(self,mon,n):
        u_mean,v_mean,speed = self.cal_mean(mon,n)
        m,xi,yi = self.bmap()
        m.quiver(xi[::4,::4],yi[::4,::4],u_mean[::4,::4],v_mean[::4,::4],speed[::4,::4],scale=180,color='r',width=0.002)#scale=80--80m/s设置为箭头单位强度
        plt.savefig(f'sim_{n}.png') 

        pass

    def cal_mean(self,mon,n):
        u = self.file_obj.u
        v = self.file_obj.v
        u = u.loc[u.time.dt.month.isin(mon)]
        v = v.loc[v.time.dt.month.isin(mon)]
        u_mean = np.mean(u,axis=0)
        v_mean = np.mean(v,axis=0)
        speed = np.sqrt(u_mean**2 + v_mean**2)

        return u_mean,v_mean,speed

    def bmap(self):
        m = Basemap(boundinglat=75, lon_0 = 0,projection = 'npstere', round=True)
        m.drawcoastlines(linewidth=0.5)
        m.drawstates() 
        m.drawcountries() 
        lons = self.file_obj.longitude
        lats = self.file_obj.latitude
        xi,yi = m(lons,lats)

        return m,xi,yi

a = Sim1('/mnt/g/st-nsidc/icemotion_daily_nh_25km_20210101_20211231_v4.1.nc')
a.Draw_vector(mon=range(1,13),n='2021')