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Revealing four decades of snow cover dynamics in the Hindu Kush Himalaya.
Naegeli, K; Franke, J; Neuhaus, C; Rietze, N; Stengel, M; Wu, X; Wunderle, S.
Afiliación
  • Naegeli K; Institute of Geography and Oeschger Center for Climate Change Research, University of Bern, Hallerstrasse 12, 3012, Bern, Switzerland. kathrin.naegeli@geo.uzh.ch.
  • Franke J; Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland. kathrin.naegeli@geo.uzh.ch.
  • Neuhaus C; Institute of Geography and Oeschger Center for Climate Change Research, University of Bern, Hallerstrasse 12, 3012, Bern, Switzerland.
  • Rietze N; Institute of Geography and Oeschger Center for Climate Change Research, University of Bern, Hallerstrasse 12, 3012, Bern, Switzerland.
  • Stengel M; Institute of Geography and Oeschger Center for Climate Change Research, University of Bern, Hallerstrasse 12, 3012, Bern, Switzerland.
  • Wu X; Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
  • Wunderle S; Deutscher Wetterdienst, Frankfurter Str. 135, 63067, Offenbach am Main, Germany.
Sci Rep ; 12(1): 13443, 2022 08 04.
Article en En | MEDLINE | ID: mdl-35927463
Knowledge about the distribution and dynamics of seasonal snow cover (SSC) is of high importance for climate studies, hydrology or hazards assessment. SSC varies considerably across the Hindu Kush Himalaya both in space and time. Previous studies focused on regional investigations or the influence of snow melt on the local hydrological system. Here, we present a systematic assessment of metrics to evaluate SSC dynamics for the entire HKH at regional and basin scale based on AVHRR GAC data at a 0.05° spatial and daily temporal resolution. Our findings are based on a unique four-decade satellite-based time series of snow cover information. We reveal strong variability of SSC at all time scales. We find significantly decreasing SSC trends in individual summer and winter months and a declining tendency from mid-spring to mid-fall, indicating a shift in seasonality. Thanks to this uniquely spatio-temporally resolved long-term data basis, we can particularly highlight the unique temporally variable character of seasonal snow cover and its cross-disciplinary importance for mountain ecosystems and downstream regions.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nieve / Ecosistema Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nieve / Ecosistema Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido