Preprints
https://doi.org/10.5194/amt-2022-36
https://doi.org/10.5194/amt-2022-36
 
11 Feb 2022
11 Feb 2022
Status: this preprint is currently under review for the journal AMT.

High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds

Julia Fuchs1,2, Hendrik Andersen1,2, Jan Cermak1,2, Eva Pauli1,2, and Rob Roebeling3 Julia Fuchs et al.
  • 1Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research, Karlsruhe, Germany
  • 2Karlsruhe Institute of Technology (KIT), Institute of Photogrammetry and Remote Sensing, Karlsruhe, Germany
  • 3European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, Germany

Abstract. Continental boundary layer clouds play an essential role in the climate system and are driven by processes linked to the land surface. The observation of boundary layer clouds with high-resolution satellite data can provide comprehensive insights into spatiotemporal patterns of land surface-driven modification of cloud occurrence, such as the diurnal variation of the occurrence of fog holes and cloud enhancements attributed to the impact of the urban heat island. High-resolution satellite-based cloud masking approaches are often based on locally-optimized thresholds that are compared against satellite-observed visible and/or infrared radiances to separate cloudy from clear-sky observations that can be affected by the local surface reflectance. Therefore, spatial differences in surface albedo, as found in and around urban areas or forests, can introduce spatial biases in the detected cloud cover that may impede the analysis of spatial pattern changes due to land surface influences. In this study, two approaches for cloud masking using the High Resolution Visible channel of the Spinning Enhanced Visible and Infrared Imager aboard Meteosat Second Generation are developed and validated for the region of Paris to show and improve applicability for analyses of urban effects on clouds. Firstly, the Local Empirical Cloud Detection Approach (LECDA) uses an optimized threshold to separate the distribution of visible reflectances into cloudy and clear sky for each individual pixel accounting for its locally specific brightness. Secondly, the Regional Empirical Cloud Detection Approach (RECDA) uses visible reflectance thresholds that are independent of surface reflection at the observed location. Validation against in-situ cloud fractions reveals that both approaches perform similarly with a Heidke Skill Score of 0.69 and 0.71, respectively. While the LECDA is representative for the widespread usage of locally-optimized approaches, comparison against RECDA reveals that the cloud masks obtained from LECDA can result in regional biases of +−5 % that are caused by the differences in surface reflectance. This makes the regional approach RECDA a more appropriate choice for the high-resolution satellite-based analysis of cloud cover changes over different surface types and the interpretation of locally induced cloud processes.

Julia Fuchs et al.

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Julia Fuchs et al.

Julia Fuchs et al.

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Short summary
Two cloud masking approaches, a local and a regional approach, using high-resolution satellite data are developed and validated for the region of Paris to improve applicability for analyses of urban effects on low clouds. We found that cloud masks obtained from the regional approach are more appropriate for the high-resolution analysis of locally induced cloud processes. Its applicability is tested for the analysis of typical fog conditions over different surface types.