Conference Agenda

Glaciers are important sources of fresh water in particular for the arid lowlands surrounding High Mountain Asia (HMA). However, glaciers are shrinking and losing mass at an on average accelerated rate. There is strong heterogeneity of mass loss with glaciers in the Western Kunlun, Eastern Pamir and Central Karakoram glaciers having lost only little mass. But even in these regions mass loss is now prevailing. Previous studies have shown that the heterogeneity may be caused by different climatic and accumulation regimes, debris cover, glacial lakes and glacier surging.

Within this project we used multi-source satellite data to investigate the glacier changes and its causes in entire HMA in general and in some specific regions in detail.

Frist, we propose a new index entirely based on glacier surface wet snow and firn observations from Sentinel-1 to characterizes the accumulation type. The index is based on the assumption that for summer-accumulation-type glaciers wet snow area ratio is high (normally higher than firn area ratio) in summer during frequent SAR observation, or it is prone to be winter-accumulation type. We show that this index is a powerful indicator of accumulation type and correlates well with specific glacier mass balance (i.e. mass change per unit area). We find that the glaciers in the subregions which accumulate mainly from winter snow are close to equilibrium, while the glacier subregions which mainly accumulate in summer are substantially losing mass.

Then, we used different stereo satellite data including ASTER, SPOT and Pléiades data to assess the mass balance variability and trends in various subregions with different accumulation conditions since about 2000. We found accelerated mass loss in all regions with the highest mass loss in the Langtang valley in Central Himalaya (which is of transitional accumulation type) and western Nyainqêntanglha (summer-accumulation type) with mass loss rates after 2000 between about -0.4 to 0.5 m w.e. a^-1. Glaciers in Muztagh Ata in Eastern Pamir, which are of winter-accumulation type, showed on average balanced mass budgets. But even there mass loss prevailed in recent years.

Finally, we investigated the potential of very-high resolution Pléiades data for to measure glacier-wide mass balance at annual and seasonal scales in the two contrasting regions western Nyainqêntanglha and Muztagh Ata. Annual mass balance in the Muztagh Ata massif between 2019-2020 and 2020-2021 were again negative (-0.24 ±0.19 m w.e. a^-1 and +0.17 ±0.35 m w.e. a^-1, respectively). The 2022 winter (+0.17 ±0.64 m w.e. a^-1) balance provides provisional evidence for a winter accumulation regime, though mass balance uncertainties remain high in some cases due to the short temporal baseline. On the contrary, annual mass balances in the Western Nyainqentanglha Range for similar periods show highly negative conditions (-0.87 ±0.22 m w.e. a^-1 and -0.52 ±0.11 m w.e. a^-1), suggesting much higher mass losses after the year 2019 compared to the previous six decades. With some limitations due to the high uncertainty, the winter (-0.05 ±0.70 m w.e. a^-1) mass balance estimate does not show any mass recovery.

Future work will focus on combining seasonal snow-line observations derived from Sentinel-1 and -2, with geodetic mass balance derived from the high-resolution data, ICESat-2 and velocity calculations to further improve the understanding of the mass balance heterogeneity and its drivers.

High Mountain Asia (HMA) is the region with the largest ice masses in the world. Known as the "Water Tower of Asia", meltwater from snow and glaciers feeds the major rivers of Asia and is an important freshwater resource, affecting the regional water cycle and ecology. We combined Earth System Observations (ESOs) and a novel eco-hydrological model to deliver a new understanding of the cryosphere and water cycle of key water towers of High Mountain Asia (HMA). We focused on blue (runoff) and green (evapotranspiration) water interactions in HMA and integrated water supply changes due to a vanishing cryosphere with the effect of vegetation to dampen or amplify those changes, especially in periods of droughts. Our investigation strategy has included three steps.

In the first step, we produced new data products of cryospheric, vegetation and land surface changes from remote sensing observations at benchmark sites. We generated data on snow cover and glacier extent, glacier mass balance, glacier flow velocity, soil moisture, snow water equivalent, snow and glacier albedo, snow and glacier radiation balance. We studied snow cover variability and its impact on glaciers in the high mountain ranges of the Tarim Basin using multi-temporal remote sensing data. In complex mountainous terrain there is a general overestimation of snow cover by the normalized snow cover index method. We thus used the support vector machine (SVM) classification method to select snow cover training samples of different terrain and shadow conditions on a scene-by-scene basis to monitor snow accumulation from 2013 to 2022. Using Sentinel-2 as a reference, our retrievals gave a correlation coefficient above 0.95, and a relative root mean square error of about 0.1%. We produced a Global Daily-scale Soil Moisture Fusion Dataset (GDSMFD) for the period (2011-2018) at 25km spatial resolution by applying the Triple Collocation Analysis (TCA) and Linear Weight Fusion (LWF) methods. The data set was evaluated against in-situ measurements at 331 sites worldwide, including 57 sites in China, including all the permanent observatories on the Tibetan Plateau. We retrieved glacier albedo in the Western Nyainqentanglha Mountains (WNM) with MODIS data to characterize its spatiotemporal variability from 2001 to 2020. Glacier albedo experienced large inter-annual fluctuations, with an important decreasing trend of 0.043±0.00022 per decade. A new parameterization of snow albedo was developed by combining WRF estimates of snow depth and age with MODIS retrievals of snow albedo. Compared with the default WRF parameterization of snow albedo, this led to significant reductions in relative RMSE and increases in correlation coefficients in WRF predictions of air temperature, albedo, sensible heat flux and snow depth.
Two advanced algorithms to retrieve land surface albedo and aerosol amount and properties were developed to improve: a) the characterization of the land surface background to separate the surface and atmospheric signals in aerosol retrievals and b) the separation of direct and diffuse irradiance in the retrieval of land surface albedo. The correlation of snow and ice albedo with aerosol loading was obtained by comparing the evolution of Aerosol Optical Depth (AOD) at the ITP Nam Co observatory with glacier albedo in the Western Nyainqentanglha Mountains (WNM) during 2009 – 2018. We optimized the procedure to extract a Digital Elevation Model (DEM) from ZiYuan-3 (ZY-3) Three-Line-Array (TLA) stereo images and estimated the geodetic mass balance of glaciers in two areas of the Nyainqentanglha Mountains (NM) using ZY-3 DEMs and the C-band Shuttle Radar Topography Mission (SRTM) DEM in the periods 2000–2013, 2013–2017 and 2000–2017.
A time series of glacier surface velocity in the Parlung Zangbo Basin, southeast Tibetan Plateau, was generated applying the normalized image cross-correlation method to Sentinel 2 (S2) MSI and Landsat-8 (L8) OLI image data from 2013 to 2020.
Enhanced-resolution passive microwave satellite data (PMW) were used to investigate High Mountain Asia Lake Ice Phenology (LIP). The Freeze Onset (FO), Complete Ice Cover (CIC), Melt Onset (MO), and Complete Ice Free (CIF) dates were derived for 109 lakes, including 22 lakes for the period 1978 to 2022 and 87 lakes for 2002 to 2022. Analysis of this long time-series of lake ice phenology revealed that lakes are tending to freeze later and melt earlier especially after 2000.

Our second step of investigation focused on generating glacier-specific altitudinal surface mass balance profiles to provide patterns of changes in glacier mass balance at the project study sites. Our approach is based on high-quality digital elevation change and glacier surface velocity datasets applied to estimate changes in ice thickness through the continuity equation. We derived multidecadal altitudinal mass balance profiles and quantified the equilibrium line altitude and accumulation area ratio for over 5000 glaciers across High Mountain Asia. We applied high resolution Pleiades, Deimos, and UAV datasets to retrieve accurate glacier thinning and velocity datasets for the project selected catchments. These results provide a crucial dataset to validate the eco-hydrological land surface model including its glacier components.

In the third, integrative step, we simulated the land-surface interactions across the cryosphere, hydrosphere and biosphere of the selected study catchments. We used the land-surface model Tethys-Chloris, which describes both vegetation biophysics and cryospheric processes such as snow and ice melt, snow gravitational redistribution and snowpack processes. We have set up the model for five distinct study catchments to date, forced with statistically downscaled ERA5/Land data on 100m grids at hourly timesteps. We carefully validated the model simulations with the multiple datasets obtained in step one and two. Model results from the Nepalese Himalaya in particular demonstrate how the latent heat flux by snow sublimation and evapotranspiration cause water losses to the atmosphere at a similar magnitude as those water inputs provided through ice melt from glaciers.
We synthesized our experiences of this project, by 1) providing an assessment of models that can simulate the cryo-hydro-biosphere continuum and the interactions between spheres in high mountain catchments, going beyond disciplinary separations; and 2) discussing the use of high resolution earth observation data to constrain the meteorological forcing uncertainty and validate land surface models to better understand blue-green-white water fluxes in High Mountain Asia.