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Comment: error in CDS downloads - March 2024


This page is a repository of known issues of the Global Flood Awareness System (GloFAS). Please keep these in mind when using GloFAS and related data.

Known issues include, but are not limited to, forecast issues, production incidents, and data quality deterioration.

GloFAS is an operational system so it is important we are made aware of issues/errors in our system in a timely manner. If you find a problem or any feature missing that you think should be present, and it is not listed here, please let us know by reporting it through the ECMWF Support Portal, mentioning "GloFAS" in the summary.







Incorrect NetCDF data provided for GloFAS datasets on the CDS

GloFAS data downloaded from the CDS in NetCDF format are incorrect between Tuesday, March 19th and Thursday, March 21st, 2024 only. See this forum post for details.

What to do: Download the data again.



Shifted longitudes values when downloading GloFAS data using the sub-region extraction tool to request a domain that includes negative longitude values

When data download is requested for a sub-region contains negative longitude values, the returned longitude value are shifted by 360 compared with the expected values. This occurs both when using the sub-region extraction tool on the CDS and when the data is downloaded directly from MARS using the 'area' keyword.

For instance, requesting an area (N,W,S,E) of: 89.975/-179.975/-59.975/-159.975

Returns a dataset with the following latitudes and longitudes:

latitude    (latitude) float64 89.97 89.92 89.88 ... -59.87 -59.92 -59.98

longitude   (longitude) float64180.0 180.1 180.1 ... 199.9 200.0 200.0

Instead of 

latitude    (latitude) float64 89.97 89.92 89.88 ... -59.87 -59.92 -59.98

longitude   (longitude) float64 -180.0 -180.1 -180.1 ... -160.1 -160.0 160.0

To handle the data correctly, users must apply a longitude shift to their data. This is easily possible for example using xarray assign:

ds["longitude"] = ds["longitude"].where(ds["longitude"] < 180, ds["longitude"] - 360)

The longitude issue is due to the way ecCodes handles longitude since version v2.27.0. 

This will be resolved in the next release of ecCodes (v2.32.0). Please note that unlike the ongoing issue below, this issue cannot be resolved by downgrading your version of ecCodes, as it is caused by the version used at ECMWF internally.



Incorrect final longitude value in GloFAS v3.1 NetCDF data downloaded from the CDS, and possible incorrect final longitude value when reading GRIB data when using cfgrib

This error causes the final longitude value of v3.1 GloFAS NetCDF data from the CDS to be incorrect. When examining the data (for instancing using xarray), it will look like this:

(longitude) float64 -179.9 -179.8 -179.8 ... 179.7 179.8 540.0   (final value should be 179.9)

This occurs because the conversion from GRIB to NetCDF via the CDS currently makes use of a version of ecCodes that contains a bug. ecCodes versions v2.27.0 and later have the issue.

If using the cfgrib library to work with v3.1 GRIB data, the GRIB data may appear to have the same issue. This is because the cfgrib library depends on ecCodes.

Until this is resolved in the next release of ecCodes (v2.32.0), we have removed NetCDF as a format option from the GloFAS CDS entries, and advise users to check the version of ecCodes they have installed if they are working with v3.1 data.

V4.0 GloFAS data is not affected by this issue.


13:00 UTC

Erroneous data returned when an GloFAS v4.0 data is requested with sub-region extraction.

This error caused the CDS to return incorrect GloFAS v4.0 data when an area was selected using the 'sub-region extraction' widget.

The following GloFAS datasets were affected:

Please discard data retrieved between 2023-07-26 to 2023-08-09 (13:00 UTC) if you used the sub-region extraction tool. Users are advised to redownload the data which will now be correct.

GloFAS historical v4.0 data was not affected.



Error when downloading GloFAS forecast data from the CDS in NetCDF format.

It has come to our attention that there was an error in the CDS api downloads of GloFAS forecast and seasonal forecast data, where data requested in NetCDF format was being downloaded as a GRIB file. This error has now been corrected (as of 24/05/2023).



Erroneous upstream area file listed in GloFAS documentation

It has come to our attention that there was an error with the static file for upstream area in our documentation for GloFAS. This error has now been corrected (as of 28/03/2022) and the new file uploaded to the GloFAS wiki pages here. Users are advised to redownload the upstream area file, if previously downloaded before 28 March 2022.



GloFAS forecasts and unconsolidated historical potentially degraded

GloFAS unconsolidated historical and forecast quality may be degraded due to ERA5T data impacted by assimilation of anomalous snow depth observations over Central Asia

The impact of the degradation on GloFAS river discharge simulations is expected to be very localised and of a small magnitude.


The issue in ERA5T was identified on 15th of November and a repair run for ERA5T from September until Near Real Time is on going. Once the repair run is complete, the ERA5T will be reinitialised from the repair run. Issues like this are the exact reason why ERA5 is available in Near Real Time with such a warning that it is subject to change.

GloFAS simulations (unconsolidated historical and forecasts) will continue to be potentially degraded until ERA5T is reinitialised at some point in December. The GloFAS-Seasonal forecasts are expected to get back to normal only in January.

Any degradation in the quality of the GloFAS river discharge simulations is expected to be of small magnitude and localised in Central Asia. However, different reanalysis simulations, such as the ERA5T with or without the assimilated erroneous observations or the consolidated ERA5, are expected to show localised differences anywhere in the world during this September-December period.

These differences are scaled by the size of the uncertainties present in the reanalysis, dependent on the area and the weather conditions. These differences will appear random with potentially large changes locally, such as for example in precipitation, but with very similar values as averages over large areas, not impacting the general quality of the data.

This means, users can continue to use the GloFAS historical and forecast simulations in the impacted period, regardless of the differences (especially outside of Central Asia), as those will not impact the general quality.




Incorrect labeling of data has meant that some users may have not retrieved the data they expected during the release of GloFAS V3.1.For more information see: 2021-06-30: Mislabelling of Glofas versions
*most recent issues are listed at the top of the table