Deep Convective Cloud (DCC) occurrence over Europe from 1983 to 2024, based on geostationary satellite data

Recent advancements in satellite data re-calibration and homogenization have enabled the development of long-term climatologies of deep convective clouds (DCCs), particularly using geostationary data from two generations of Meteosat satellites. This study presents a comprehensive analysis of DCC occurrence over Europe based on over four decades of satellite observations. For the period 1983–2006, we utilize the Fundamental Climate Data Record (FCDR) from the Meteosat Visible and Infrared Imager (MVIRI) onboard the Meteosat First Generation (MFG), while for 2004–2024, data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) are used.The analysis addresses key challenges in combining the two datasets, including: (1) limited spectral information (only water vapor ~6.2 µm and infrared window ~11.0 µm channels were available for both instruments), requiring careful method selection for DCC detection; (2) differences in spectral response functions, mitigated through spectral band adjustment using IASI observations; and (3) lack of consistent cloud top height (CTH) products, which we overcome by developing a unified CTH estimation method applicable to both MVIRI and SEVIRI. Optimal DCC detection thresholds were calibrated through cross-comparison with CloudSat-CALIPSO observations. Our results provide a consistent climatology of DCC frequencies over Europe, offering valuable insights into long-term convective variability and trends.This research was funded by the National Science Centre of Poland. Grant no. UMO-2020/39/B/ST10/00850. We also acknowledge Polish high-performance computing infrastructure PLGrid (HPC Center: ACK Cyfronet AGH) for providing computer facilities and support within computational grant no. PLG/2025/018115.

Authors

Institutions

Publication Details

Published
2025-08-08
DOI
https://doi.org/10.5194/ecss2025-118
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deep Convective Cloud (DCC) occurrence over Europe from 1983 to 2024, based on geostationary satellite data

Andrzej Z. Kotarba
Atmospheric aerosols and clouds
article

Deep Convective Cloud (DCC) occurrence over Europe from 1983 to 2024, based on geostationary satellite data

Andrzej Z. Kotarba
article en

Abstract

Recent advancements in satellite data re-calibration and homogenization have enabled the development of long-term climatologies of deep convective clouds (DCCs), particularly using geostationary data from two generations of Meteosat satellites. This study presents a comprehensive analysis of DCC occurrence over Europe based on over four decades of satellite observations. For the period 1983–2006, we utilize the Fundamental Climate Data Record (FCDR) from the Meteosat Visible and Infrared Imager (MVIRI) onboard the Meteosat First Generation (MFG), while for 2004–2024, data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) are used.The analysis addresses key challenges in combining the two datasets, including: (1) limited spectral information (only water vapor ~6.2 µm and infrared window ~11.0 µm channels were available for both instruments), requiring careful method selection for DCC detection; (2) differences in spectral response functions, mitigated through spectral band adjustment using IASI observations; and (3) lack of consistent cloud top height (CTH) products, which we overcome by developing a unified CTH estimation method applicable to both MVIRI and SEVIRI. Optimal DCC detection thresholds were calibrated through cross-comparison with CloudSat-CALIPSO observations. Our results provide a consistent climatology of DCC frequencies over Europe, offering valuable insights into long-term convective variability and trends.This research was funded by the National Science Centre of Poland. Grant no. UMO-2020/39/B/ST10/00850. We also acknowledge Polish high-performance computing infrastructure PLGrid (HPC Center: ACK Cyfronet AGH) for providing computer facilities and support within computational grant no. PLG/2025/018115.

Centrum Badań Kosmicznych (PL)
Openalex Percentile: Top 80%
Atmospheric aerosols and clouds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.