相信大家刚接触到micaps数据是一头雾水，还好有对应的可视化库。
今天给大家演示两种micaps站点数据的快速绘制方法。
导入可视化库
import meteva.base as mebimport metpy.calc as mpcalcimport metpy.plots as mpplotsfrom metpy.units import unitsfrom metpy.calc import reduce_point_densityimport matplotlib.pyplot as pltimport numpy as npimport cartopy.crs as ccrsimport cartopy.feature as cfeaturefrom cartopy.io.shapereader import BasicReaderfrom cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTERplt.rcParams['font.sans-serif'] = ['Source Han Sans CN']plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号Warning: ecCode
数据读取：micaps第三类数据
provinces = BasicReader('/home/mw/input/china1656/china_map/china_map/China_Province_2022.shp')filename = "/home/mw/input/meteva2260/t.000" # 替换为你的micaps文件路径sta = meb.read_stadata_from_micaps3(filename)sta.head()
| level | time | dtime | id | lon | lat | data0 |
0 | 0 | 2022-09-04 17:00:00 | 0 | 56473 | 102.77 | 28.95 | 16.8 |
1 | 0 | 2022-09-04 17:00:00 | 0 | 56263 | 101.88 | 30.88 | 11.9 |
2 | 0 | 2022-09-04 17:00:00 | 0 | 56593 | 104.92 | 28.58 | 23.1 |
3 | 0 | 2022-09-04 17:00:00 | 0 | 56491 | 104.57 | 28.70 | 21.7 |
4 | 0 | 2022-09-04 17:00:00 | 0 | 56290 | 104.18 | 30.78 | 19.6 |
数据处理
# 读取经度、纬度、温度lons = sta["lon"].valueslats = sta["lat"].values
方法一：使用metpy站点绘制
创建图形fig = plt.figure(figsize=(15, 12))ax = fig.add_subplot(111,projection=ccrs.PlateCarree())ax.add_feature(cfeature.LAND)ax.add_feature(cfeature.OCEAN)ax.add_feature(cfeature.COASTLINE)ax.set_extent( [110, 120, 20, 25])创建站点图stationplot = mpplots.StationPlot(ax, lons, lats, transform=ccrs.PlateCarree(),fontsize=10)绘制温度分布stationplot.plot_parameter('NW', temperature, formatter=lambda v: format(v, '.1f'))ax.add_geometries(provinces.geometries(), linewidth=.5, edgecolor='black', crs=ccrs.PlateCarree(),facecolor='none')gl = ax.gridlines(draw_labels=True,alpha=0.5,linewidth=1,color='k',linestyle='--')gl.xlabels_top = False # 关闭顶端标签gl.ylabels_right = False # 关闭右侧标签gl.xformatter = LONGITUDE_FORMATTER # x轴设为经度格式gl.yformatter = LATITUDE_FORMATTER # y轴设为纬度格式plt.show()
方法二：使用meteva库内置函数绘制
map_extend = [110, 120, 20, 25]axs = meb.creat_axs(1,map_extend,sup_title="2022年9月4日t2",add_index=["a"],sup_fontsize=8)image = meb.add_scatter_text(axs[0], sta, tag=0, font_size=8,cmap =meb.cmaps.temp_2m)
