Hi,

We are downloading ERA5 grb files for about 160 days. Each day only one hour of data, in 44 pressure levels. The area covers about 10 to 20 degrees in both latitude and longitude. 
The last time when I tried this, in 9 hours, I only got 38 out of 158 grb files.

Not only that time, but I have also downloaded many stacks of ERA5 recently (same number of hours, levels, and spatial coverage), they all turned out to be very slow.

After checking the efficiency tips section on CDS documentation, I think our current way to retrieve data using the CDS API is efficient.

This is our request structure:

https://github.com/insarlab/PyAPS/blob/c4c623e85a63c51b039bab2007224a5be3ce4045/src/pyaps3/autoget.py#L89-L133

And the queueing message:


INFO: You are using the latest ECMWF platform for downloading datasets: https://cds.climate.copernicus.eu/api/v2 Downloading 1 of 27: C:\project\mintpy_output_small\ERA5\ERA5_S40_S20_E120_E140_20170403_21.grb 
{'product_type': 'reanalysis', 'format': 'grib', 'variable': ['geopotential', 'temperature', 'specific_humidity'], 'pressure_level': ['1', '2', '3', '5', '7', '10', '20', '30', '50', '70', '100', '125', '150', 
'175', '200', '225', '250', '300', '350', '400', '450', '500', '550', '600', '650', '700', '750', '775', '800', '825', '850', '875', '900', '925', '950', '975', '1000'], 'year': '2017', 'month': '04', 'day': '03', 
'time': '21:00', 'area': '-20.00/120.00/-40.00/140.00'} 2022-05-01 18:30:24,627 INFO Welcome to the CDS 2022-05-01 18:30:24,627 INFO Sending request to https://cds.climate.copernicus.eu/api/v2/resources/reanalysis-
era5-pressure-levels 2022-05-01 18:30:24,909 INFO Request is queued


I have noticed other recent treads also complained about this:

time to get request is becoming very high


Thanks in advance!

Kai

1 Comment

  1. Hi Kai,

    For hourly ERA5 data, It's most efficient to request 1 month's of data in each CDS API request - have you tried that?

    Thanks,

    Kevin