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Assessing the snow cover dynamics and monitoring the anomalies in snow-covered days for paneuropean region using eumetsat hsaf snow products

Urheber*innen

Kuter,  Semih
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Karaman,  Cagri Hasan
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Akpınar,  Mustafa Berkay
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Akyurek,  Zuhal
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Zitation

Kuter, S., Karaman, C. H., Akpınar, M. B., Akyurek, Z. (2023): Assessing the snow cover dynamics and monitoring the anomalies in snow-covered days for paneuropean region using eumetsat hsaf snow products, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-2732


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5019159
Zusammenfassung
Monitoring snow-covered areas is essential for understanding snow dynamics especially in high-altitude mountainous regions with complex topography, where in-situ networks may fall short in catching the spatial variability of the snowpack. EUMETSAT HSAF H10 is a daily operational binary snow cover product retrieved from MSG-SEVIRI and it spatially spans Pan European region with horizontal resolution of 0.05°. The snow cover mapping is based on a multi-channel retrieval algorithm. It exploits the high reflectivity of snow in the visible spectrum and the low reflectivity at shorter wavelengths H10 product was used to obtain the snow-covered areas between the years 2011-2022. Using the long-term average values, anomalies in snow-covered days for January, February, March, and April of 2022 were obtained. The 6-day temporal moving window technique was used on the H10 product to minimize the effects of cloud cover contamination, especially during winter seasons. Monthly snow cover anomalies were determined by subtracting the long-term averages from the monthly-based average values and dividing the result by the standard deviation of the associated long-year average. Additionally, surface temperature anomalies were obtained for January-April 2022 utilizing ERA5-Land atmospheric reanalysis data. The findings indicate a severe negative anomaly in northern Italy and a positive anomaly in eastern Turkey, exhibiting parallel trends with the temperature anomalies. Mean monthly discharge anomalies were also obtained for three sub-basins from Bati Karadeniz, Kizilirmak, and Akarcay basins. The study examines the effect of snow cover day anomalies on mean monthly discharges in these sub-basins with different mean altitudes and basin areas.