Questions about Meteosat-10 in CERES GEO product.

[imnbakerstreet]

We found that the effective radius (liquid phase) in the CERES GEO products, especially datasets of Meteosat-10 (SatCORPS CERES GEO Edition 4 Meteosat-10 Northern/Southern Hemisphere Version 1.0) are unusually high compared to other Meteosats. We would like to know whether this discrepancy is due to the satellite itself or an issue with the retrieval algorithm.

[ASDC - cheyenne.e.land]

Hello,

We have contacted an expert in CERES GEO products and they will answer your question shortly.

Thanks,
ASDC

[ASDC - rkey]

The SME response is as follows:

The problem you are seeing with overly large effective radius (both water and ice) is an issue with the software that was used to process the data.

The MET10 V01.2 available in 2023 and 2024 do not have this issue.

We are sorry for any inconvenience this issue is causing you.

Best Regards

[imnbakerstreet]

The SME response is as follows:

The problem you are seeing with overly large effective radius (both water and ice) is an issue with the software that was used to process the data.

The MET10 V01.2 available in 2023 and 2024 do not have this issue.

We are sorry for any inconvenience this issue is causing you.

Best Regards

Thank you for your reply!

We have also noticed that the cloud property from the same satellite varies in different regions. The cloud optical thickness (CLOT) from GOES-16 datasets (CER_GEO_Ed4_GOE16_SH_V01.2) in the Brazil region (50°W ~ 30°W, 17°S ~ 2°S) shows abnormally low values compared to other GOES-EAST series geostationary satellites, while there are no sudden changes observed in the Peruvian stratus region (10°-20°S, 80°-90°W). Is this also a software issue? Additionally, will there be a correctional dataset for Meteosat-10/GOES-16 after the software issues are resolved?

This would be extremely helpful for us. Thank you!

[ASDC - cheyenne.e.land]

Hello,

The analysis approach that was employed was not designed to derive consistent cloud properties across satellite platforms with varying imager characteristics. Therefore, this data should not be used in time series analyses across satellites since this version is not designed for climate data records. For example, the 16-band imager on GOES-16 is much different than the earlier 5-band imagers over the GOES-E ___domain. These have different sensitivities to clouds and were analyzed with different algorithms using different spectral information to derive the most accurate information possible for each satellite, which could lead to larger inconsistencies for some cloud regimes and geographic regions than for others.

The corrected Meteosat-10 dataset will be available online soon.

Regards,
ASDC