Real time snow recognition from msg satellite for mountainous areas

Date

2008-06-05

Author

Surer, S.
Gokdemir, O.
Beser, O.
Akyürek, Sevda Zuhal
Sorman, A. U.
Erturk, A. G.

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

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In Hydrology Satellite Application Facilities (HydroSAF) Project which is a financially supported project by EUMETSAT, the use of snow products retrieved from satellite images in hydrological applications and to observe the impact of the products are key issues. Turkey is a part of the HydroSAF project, both in developing satellite derived snow products (snow recognition, effective snow cover, and snow water equivalent) for mountainous areas, cal/val of satellite-derived snow products with ground observations and impact studies with hydrological modeling in the mountainous terrain of Europe. The snow recognition product for mountainous regions is evaluated in this paper. An algorithm has been developed for snow recognition over mountainous areas of Europe. The proposed algorithm uses Satellite Application Facility to support Nowcasting and Very Short Range Forecasting's (SAFNWC) cloud products. Two main validation processes have been applied for the snow cover product belonging to 19th January 2008 produced with SEVIRI data. First, the comparison of the SEVIRI snow cover product with the snow cover product produced from a single NOAA AVHRR data for the same date 19th January 2008 has been performed. Second, SEVIRI snow cover product was validated with 43 synoptic weather stations distributed over Europe.

Subject Keywords

Multi-temporal, SAFNWC, NOAA AVHRR, MSG-SEVIRI, Snow

URI

https://hdl.handle.net/11511/36518

DOI

https://doi.org/10.3233/978-1-58603-986-8-86

Collections

Department of Civil Engineering, Conference / Seminar

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Citation Formats

S. Surer, O. Gokdemir, O. Beser, S. Z. Akyürek, A. U. Sorman, and A. G. Erturk, “Real time snow recognition from msg satellite for mountainous areas,” 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36518.