利用python批量下载ERA的数据

偏执的太偏执、 2022-05-09 07:03 329阅读 0赞

终于开始用python了，只学了两天的python小白上线下载数据（被逼的）。

其实这个有一些很好的教程，我直接粘贴好了。[批量下载的教程][Link 1]

其中的一些参数官网的解释很清楚的，可以先试着下载一个月的数据，再获取它的request提供参考

最后是我的一些代码，以及注释

这是下载era-40里面的2mt数据，并且只下载纬度80N以北的数据，注意看参数。格网为0.75

from ecmwfapi import ECMWFDataServer
        
    server = ECMWFDataServer()
    polynya_boundary = "90/-180/80/180"
    day_month_dic = {1:31,2:28,3:31, 4:30, 5:31, 6:30, 7:31, 8:31, 9:30, 10:31, 11:30,12:31}
    
    for year in range(1959, 1979):
        for month in range(1, 13):
            date_varied = "{}-{:0>2d}-01/to/{}-{:0>2d}-{}".format(year, month, year, month, day_month_dic[month])
            
            server.retrieve({
                'stream'    : "oper", 
                'levtype'   : "sfc",
                'param'     : "167.128",
                'dataset'   : "era40",
                'step'      : "0",
                'grid'      : "0.75/0.75",
                'time'      : "00/06/12/18",
                'date'      : date_varied,
                'type'      : "an",
                'class'     : "E4",
                'area'      : polynya_boundary,
                'format'    : "netcdf",
                'target'    : "F:\\ERAInterim\\2TM\\{0}\\{1}_{2:0>2d}.nc".format(year,year,month)
             })

下面这个是下载ERA-Interim的2tm的数据，注意时间，范围基本一致。

from ecmwfapi import ECMWFDataServer
        
    server = ECMWFDataServer()
    polynya_boundary = "90/-180/80/180"
    day_month_dic = {1:31,2:28,3:31, 4:30, 5:31, 6:30, 7:31, 8:31, 9:30, 10:31, 11:30,12:31}
    
    for year in range(2018, 2019):
        for month in range(1, 10):
            date_varied = "{}-{:0>2d}-01/to/{}-{:0>2d}-{}".format(year, month, year, month, day_month_dic[month])
            
            server.retrieve({
                'stream'    : "oper", 
                'levtype'   : "sfc",
                'param'     : "167.128",
                'dataset'   : "interim",
                'step'      : "0",
                'grid'      : "0.75/0.75",
                'time'      : "00/06/12/18",
                'date'      : date_varied,
                'type'      : "an",
                'class'     : "ei",
                'area'      : polynya_boundary,
                'format'    : "netcdf",
                'target'    : "F:\\ERAInterim\\2TM\\{0}\\{1}_{2:0>2d}.nc".format(year,year,month)
             })

[Link 1]: https://blog.csdn.net/hengcall/article/details/81387613