You can use a Python program to extract ERA-Interim and other data remotely from ECMWF's archive system MARS. For an introduction see here.
Daily data
When extracting data from daily data you can specify:
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You can write a date either as YYYY-MM-DD or as YYYYMMDD.
Monthly data
When you extract monthly means, the monthly means are timestamped to the first day of the month, and you have to extract for exactly these dates. So to extract monthly means for all of 2015 you need to use this syntax to specify dates:
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#!/usr/bin/env python
# This script extracts the average daily precipitation for each month.
from datetime import datetime, timedelta
# Change the start and end dates to your desired date range. Monthly data is specified as the 1st of the month.
# For example, to get January 1979 to December 1980, use (1979, 1, 1) and (1980, 12, 1), repectively
start = datetime(1979, 1, 1)
end = datetime(1980, 12, 1)
datelist = [start.strftime('%Y-%m-%d')]
while start <= end:
start += timedelta(days=32)
datelist.append( datetime(start.year, start.month, 1).strftime('%Y-%m-%d') )
datestring = "/".join(datelist)
from ecmwfapi import ECMWFDataServer
server = ECMWFDataServer()
server.retrieve({
"class": "ei",
"dataset": "interim",
"date": datestring,
"expver": "1",
"grid": "0.75/0.75",
"levtype": "sfc",
"param": "tp",
"step": "0-12",
"stream": "mdfa",
"type": "fc",
"area" : "75/-15/30/35",
"format": "netcdf",
"target": "tp-mdfa-197901to198012.nc",
}) |
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