EGU21-14693
https://doi.org/10.5194/egusphere-egu21-14693
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Long-term spatio-temporal seasonal snow cover variability in the Hindu Kush Himalaya

Kathrin Naegeli1,2, Nils Rietze1,2, Jörg Franke1,2, Martin Stengel3, Christoph Neuhaus1,2, Xiaodan Wu1,4, Carlo Marin5, Valentina Premier5, Gabriele Schwaizer6, and Stefan Wunderle1,2
Kathrin Naegeli et al.
  • 1University of Bern, Institut of Geography (kathrin.naegeli@giub.unibe.ch)
  • 2Oeschger Center for Climate Change Research, Bern, Switzerland
  • 3Deutscher Wetterdienst, Offenbach, Germany
  • 4College of Earth and Environmental Sciences, Lanzhou University, China
  • 5Eurac Institute for Earth Observation, Bolzano, Italy
  • 6ENVEO – Environmental Earth Observation IT GmbH, Innsbruck, Austria

The Hindu Kush Himalaya (HKH), the worlds ‘water tower’, contains the largest volume of snow and ice outside of the polar ice sheets and is the headwater area of Asia’s largest rivers. Due to the complex topography and its great spatial extent the HKH is characterised by variable temperature and precipitation pattern and thus exhibits large heterogeneity in the presence of seasonal snow cover (SSC). Previous studies usually focused on regional studies of snow cover area percentage or the influence of snow melt on the local hydrological system. Here we present a systematic overview of spatio-temporal SSC variability of the entire HKH region on a climate relevant time scale (four decades).

Our results are based on Advanced Very High Resolution (AVHRR) data, collected onboard the polar orbiting satellites NOAA-7 to -19, providing daily, global imagery at a spatial resolution of 5 km since 1982 up to today. This unique dataset is exceptionally valuable to derive pixel-based SSC information using a Normalised Difference Snow Cover (NDSI) approach including additional thresholds related to topography and land cover, and developed in the frame of ESA CCI+ snow.  Calibrated and geocoded reflectance data and a consistent cloud mask, derived in the ESA CCI cloud project, are used. A temporal gap-filling was applied to mitigate the influence of clouds. Reference snow maps from high-resolution optical satellite data as well as in-situ station data were used to validate the time series.

The dataset allows analysis of the state and trends of SSC at regional and sub-regional level. We thus investigated spatio-temporal evolution and long-term variability of SSC for the entire HKH as well as for 14 hydrological basins. We find large spatial difference in the amount of SSC depending on the regional elevation and precipitation characteristics. Furthermore, we investigate SSC phenology, which is directly linked to climate change and thus of high relevance for seasonal water storage and mountain streamflow. Our analysis indicates a significant decline in snow cover area percentage (SCA %) during warm and dry summer month and a decreasing tendency from high winter through spring to early summer. At the hydrological basin level, no significant long-term trend was detected, however, both western and central basins indicate a decrease in SCA % and generally the latest years are strongly negative. Moreover, we examine SCA % anomalies at the highest available temporal frequency (daily information) and reveal an overall shortening of the SSC occurrence and a general decrease of SSC extent in the HKH region.

How to cite: Naegeli, K., Rietze, N., Franke, J., Stengel, M., Neuhaus, C., Wu, X., Marin, C., Premier, V., Schwaizer, G., and Wunderle, S.: Long-term spatio-temporal seasonal snow cover variability in the Hindu Kush Himalaya, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14693, https://doi.org/10.5194/egusphere-egu21-14693, 2021.

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