Synthetic MFG MVIRI Level 1.5 VIS channel data of Europe from 2006–2020 for long-term climatological research

Geostationary satellites observe the Earth, providing essential data for climate research and weather forecasting. Understanding long-term changes in cloud cover is particularly important, as changes in cloud albedo can affect global temperatures directly. The Meteosat programme has been monitoring Europe and Africa since 1977, providing a good basis for long-term climatological research. Due to their different sensor characteristics, data from different satellites must be harmonized to obtain a consistent time series for long-term research. This study harmonizes the Meteosat First Generation (MFG) broadband solar channel and the two Meteosat Second Generation (MSG) solar channels using a Random Forest model to generate a long-term time series of the MFG solar channel over Central Europe from 2006 to 2020, which can be used to extend the existing MFG MVIRI VIS image time series. The RF model predicts the MVIRI solar channel well (R<sup>2</sup> = 0.93). In complex terrain inaccuracies in predictions may occur. The synthesized MVIRI solar channel time series has no severe discontinuities and is available for long-term research.

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Publication Details

Journal
Scientific Data
Published
2025-08-04
DOI
https://doi.org/10.1038/s41597-025-05578-5
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Synthetic MFG MVIRI Level 1.5 VIS channel data of Europe from 2006–2020 for long-term climatological research

Jörg Bendix, Ivo Jung, Sheetabh Gaurav
Scientific Data
Atmospheric aerosols and clouds
article

Synthetic MFG MVIRI Level 1.5 VIS channel data of Europe from 2006–2020 for long-term climatological research

Jörg Bendix, Ivo Jung, Sheetabh Gaurav
article en

Abstract

Geostationary satellites observe the Earth, providing essential data for climate research and weather forecasting. Understanding long-term changes in cloud cover is particularly important, as changes in cloud albedo can affect global temperatures directly. The Meteosat programme has been monitoring Europe and Africa since 1977, providing a good basis for long-term climatological research. Due to their different sensor characteristics, data from different satellites must be harmonized to obtain a consistent time series for long-term research. This study harmonizes the Meteosat First Generation (MFG) broadband solar channel and the two Meteosat Second Generation (MSG) solar channels using a Random Forest model to generate a long-term time series of the MFG solar channel over Central Europe from 2006 to 2020, which can be used to extend the existing MFG MVIRI VIS image time series. The RF model predicts the MVIRI solar channel well (R<sup>2</sup> = 0.93). In complex terrain inaccuracies in predictions may occur. The synthesized MVIRI solar channel time series has no severe discontinuities and is available for long-term research.

Scientific DataVol. 12(1)
Philipps University of Marburg (DE)
European Commission, Deutsche Forschungsgemeinschaft, European Organization for the Exploitation of Meteorological Satellites
Climate action
Openalex Percentile: Top 82%
Atmospheric aerosols and clouds
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