| Note | ||
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For the time being and until further notice, ERA-Interim (1st January 1979 to 31st August 2019) shall continue to be accessible through the ECMWF Web API. Keeping in mind that ERA-Interim is published with an offset of about three months from the dataset's reference date, ERA-Interim August 2019 data will be made available towards the end of October 2019. ERA5 is now available from the Climate Data Store (CDS) (What are the changes from ERA-Interim to ERA5?) and users are strongly advised to migrate to ERA5 (How to migrate from ECMWF Web API to CDS API). |
a-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.
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| Code Block | ||||
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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), respectively
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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