【python】ERA5逐小时降水数据计算逐日降水

　　自用简单方法

　　参考代码：ERA5: How to calculate daily total precipitation - Copernicus Knowledge Base - ECMWF Confluence Wiki

　　1、先从官网（ERA5-Land hourly data from 1950 to present (copernicus.eu)）下载全年的逐小时降水数据（nc格式）

 　　2、运行代码

import time, sys
from datetime import datetime, timedelta
 
from netCDF4 import Dataset, date2num, num2date
import numpy as np
#设置起始日期和截止日期（逐月做，自行调整）
startdate=20190701
enddate=20190731
for date in range(startdate,enddate+1):
    day = date
    d = datetime.strptime(str(day), '%Y%m%d')
    #输入下载好的逐小时nc数据（计算月末日期，如6月30日时，需用到7月1日0时的数据，可以直接先从官网下载全年的nc数据）
    f_in = 'tp2019.nc'
    # f_in = 'tp_%d-%s.nc' % (day, (d + timedelta(days = 1)).strftime('%Y%m%d'))
    f_out = 'daily-tp_%d.nc' % day
    
    time_needed = []
    for i in range(1, 25):
        time_needed.append(d + timedelta(hours = i))
    
    with Dataset(f_in) as ds_src:
        var_time = ds_src.variables['time']
        time_avail = num2date(var_time[:], var_time.units,
                calendar = var_time.calendar)
    
        indices = []
        for tm in time_needed:
            a = np.where(time_avail == tm)[0]
            if len(a) == 0:
                sys.stderr.write('Error: precipitation data is missing/incomplete - %s!\n'
                        % tm.strftime('%Y%m%d %H:%M:%S'))
                sys.exit(200)
            else:
                print('Found %s' % tm.strftime('%Y%m%d %H:%M:%S'))
                indices.append(a[0])
    
        var_tp = ds_src.variables['tp']
        tp_values_set = False
        for idx in indices:
            if not tp_values_set:
                data = var_tp[idx, :, :]
                tp_values_set = True
            else:
                data += var_tp[idx, :, :]
            
        with Dataset(f_out, mode = 'w', format = 'NETCDF3_64BIT_OFFSET') as ds_dest:
            # Dimensions
            for name in ['latitude', 'longitude']:
                dim_src = ds_src.dimensions[name]
                ds_dest.createDimension(name, dim_src.size)
                var_src = ds_src.variables[name]
                var_dest = ds_dest.createVariable(name, var_src.datatype, (name,))
                var_dest[:] = var_src[:]
                var_dest.setncattr('units', var_src.units)
                var_dest.setncattr('long_name', var_src.long_name)
    
            ds_dest.createDimension('time', None)
            var = ds_dest.createVariable('time', np.int32, ('time',))
            time_units = 'hours since 1900-01-01 00:00:00'
            time_cal = 'gregorian'
            var[:] = date2num([d], units = time_units, calendar = time_cal)
            var.setncattr('units', time_units)
            var.setncattr('long_name', 'time')
            var.setncattr('calendar', time_cal)
    
            # Variables
            var = ds_dest.createVariable(var_tp.name, np.double, var_tp.dimensions)
            var[0, :, :] = data
            var.setncattr('units', var_tp.units)
            var.setncattr('long_name', var_tp.long_name)
    
            # Attributes
            ds_dest.setncattr('Conventions', 'CF-1.6')
            ds_dest.setncattr('history', '%s %s'
                    % (datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
                    ' '.join(time.tzname)))
    
            print('Done! Daily total precipitation saved in %s' % f_out)

　　3、完成！