Banerjee, A; Chen, RS; Meadows, ME; Sengupta, D; Pathak, S; Xia, ZL; Mal, S (2021). Tracking 21st century climate dynamics of the Third Pole: An analysis of topo-climate impacts on snow cover in the central Himalaya using Google Earth Engine. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 103, 102490.
Abstract
Research on the Himalayan cryosphere has increasingly focused on climate change, considering aspects such as snow cover dynamics, precipitation and temperature trends. The Uttarakhand Himalaya is hydrologically very significant and a more comprehensive understanding of its response to climate change is needed. This paper analyses of elevation-dependent distribution and trends in snow-covered area (SCA), precipitation and temperature for the period 2000-2020 employing MODIS-Terra data, together with reanalysis (CHIRPS) and Landsat-8 data products within the Google Earth Engine (GEE) platform. The study reveals a significant increasing trend in annual, seasonal and monthly precipitation (except November) at different elevations, while SCA and temperatures exhibited more variable trends during the period. Digital elevation and spectral reflectance models reveal the effects of topography and surface attributes on snow cover. Statistical analyses reveal a significant relationship between precipitation and SCA (R2 = 0.78), while seasonal changes in temperature are apparent in an emerging pattern of warmer winters and a cooler pre-monsoon. SCA trends vary markedly between elevation zones in response to precipitation and temperature fluctuations. At higher altitudes, SCA decreased from 2000 to 2020 since, although precipitation increased slightly, marginally higher temperatures led to more snowmelt. Reduced snow cover and increased temperature are also associated with a decline in downstream fluvial during the period for which such data are available (2000 to 2005). The analysis of snow cover dynamics across different elevations improves our understanding of the overall hydrological conditions in the region and enable more reliable flood forecasting and management of water resources.
DOI:
10.1016/j.jag.2021.102490
ISSN:
1569-8432