Browsing by Author "Atar Singh"

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Assessment of precipitation and its extreme precipitation changes over the Himalayan Bhilangana River Basin, India
(Springer, 2025) Bhupendra Joshi; Vishal Kumar Kumar Singh; Veerendra Kumar Chandola; Atar Singh
Precipitation is a dominant driver of hydrological processes, and its reliable estimation is particularly important in the Himalayan region, where climate variability exerts strong control on water resources. This study evaluated changes in extreme precipitation over the Bhilangana River Basin, India, using multiple gridded datasets. Dataset performance was first assessed against station observation, with APHRODITE demonstrating the strongest agreement, followed by IMD, ERA5, and GPM. To refine accuracy, a hybrid statistical reconstruction was applied to generate a bias-corrected 0.10-degree precipitation dataset, which was subsequently employed to correct CMIP6 model outputs under SSP245 and SSP585 scenarios. A multi-model ensemble was then analysed for ETCCDI-recommended precipitation extremes across two future horizons: near future (2025–2054) and far future (2061–2090). Climate projections results indicate consistent declines in maximum one-day (Rx1day) and five-day (Rx5day) precipitation, reflecting a weakening of short-duration extremes. These reductions are accompanied by fewer consecutive dry days (CDD), while consecutive wet days (CWD) are projected to increase markedly. The most pronounced changes emerge in high-altitude regions, underscoring their elevated sensitivity to future precipitation shifts. These projected alterations highlight potential risks to glacier stability, flood regimes, and hydropower reliability, underscoring the urgency of developing climate-adaptive water management strategies in Himalayan basins. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.
MODIS-based estimates of strong snow surface temperature anomaly related to high altitude earthquakes of 2015
(Elsevier Inc., 2017) Anshuman Bhardwaj; Shaktiman Singh; Lydia Sam; Akanksha Bhardwaj; F. Javier Martín-Torres; Atar Singh; Rajesh Kumar
The high levels of uncertainty associated with earthquake prediction render earthquakes some of the worst natural calamities. Here, we present our observations of MODerate resolution Imaging Spectroradiometer (MODIS)-derived Land Surface Temperature (LST) anomaly for earthquakes in the largest tectonically active Himalayan and Andean mountain belts. We report the appearance of fairly detectable pre-earthquake Snow Surface Temperature (SST) anomalies. We use 16 years (2000–2015) of MODIS LST time-series data to robustly conclude our findings for three of the most destructive earthquakes that occurred in 2015 in the high mountains of Nepal, Chile, and Afghanistan. We propose the physical basis behind higher sensitivity of snow towards geothermal emissions. Although the preliminary appearance of SST anomalies and their amplitudes vary, we propose employing a global-scale monitoring system for detecting and studying such spatio-temporal geophysical signals. With the advent of improved remote sensors, we anticipate that such efforts can be another step towards improved earthquake predictions. © 2016 Elsevier Inc.