Snow cover mapping with Meteosat thir generation FCI: initial evaluation of the European Organisation for the Exploitation of Meteorological Satellites H SAF H43 snow mask product

Date

2026-01-13

Author

Kuter, Semih
Karaman, Cagri Hasan
Akpinar, Mustafa Berkay
Akyürek, Sevda Zuhal

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This study presents the results of the initial validation of the EUMETSAT H SAF H43 snow cover product, the first operational snow product derived from the Flexible Combined Imager (FCI) onboard Meteosat Third Generation (MTG). The evaluation, covering the period from December 2024 to February 2025, includes a direct comparison with the earlier H34 product, generated from SEVIRI observations onboard Meteosat Second Generation (MSG). Analyses were conducted over three mountainous regions—the Alps, Turkey, and Georgia—using MODIS-based reference snow cover maps and in-situ snow-depth measurements from WMO synoptic stations. As snow cover in mountainous terrain plays a critical role in hydrology and water resources management, special attention was given to high-elevation zones (above 1,000 m), where snow is seasonally persistent and detection accuracy most relevant. The evaluation employed standard accuracy metrics—Probability of Detection (POD), False Alarm Ratio (FAR), and Overall Accuracy (ACC)—to assess performance across elevation, aspect, and land-cover classes. Results indicate that H43 provides consistent yet moderate improvements over H34, with miss-rate reductions of up to 40% above 2,000 m elevation and FAR values remaining below 30% across land-cover types. These improvements are supported by the enhanced radiometric performance and 10-min temporal resolution of the FCI sensor, which enable more effective cloud detection and frequent scene refresh. Combined with its near-real-time availability, these features make H43 a promising tool for operational snow monitoring, hydrological forecasting, and early-warning applications across topographically complex regions.

Subject Keywords

Computational Science, Ecohydrology, Flexible combined imager, Natural Resource Management, Remote sensing of cryosphere, Snow cover mapping, Spatial and Geographic Information Science, VIS/NIR radiometry

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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105028115846&origin=inward
https://hdl.handle.net/11511/118528

Collections

Department of Civil Engineering, Article