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Glacier ice-thickness measurement and distribution is one of the essential variables to assess present status of glacier-water equivalent and its volumetric reserve as well as to model the future glacier dynamics under the climate changing scenario. Yet, substantial gaps in ice thickness information exist for the Himalayan glaciers. The present study provides a long-term assessment (1965–2016) of recessional and area change patterns, as well as the detailed field-based (2016–2017) Ground Penetrating Radar(GPR), derived ice-thickness measurement of the Menthosa Glacier, Lahaul Himalaya. Additionally, the study examines whether the modelled ice thickness from remote sensing data is consistent with the field-based GPR measurement and how can it be improved. The extensive field surveys coupled with the multi-temporal high (Corona KH-4A) to medium resolution (Landsat Enhanced Thematic Mapper+ (ETM+)/Operational Land Imager (OLI), Sentinel 2A-Multispectral Instrument (MSI)) remote sensing data and cross-sectional GPR surveyed profile measurements have been used to examine past half a century (1965–2016) glacier fluctuation and the recent ice-thickness estimations, respectively. The results show that the Menthosa Glacier receded by 301.5 ± 19.2 m during the past half a century (1965–2016) with an average annual retreat of 5.9 ± 0.4 m a−1, whereas glacier lost 0.09 km2 ice in the frontal section. Field measurement over the past one decade (2006–2017) also conforms to a continuous recessional pattern and substantial glacier degeneration particularly the extensive surface lowering and significant appearance of ice-cliffs in the ablation and lateral zones over this period. The GPR measurements (2017) show the minimum glacier ice thickness of 24 meters at 4691 m a.s.l. (in the lower part of ablation area) and maximum glacier ice thickness of 55 meters measured at 4758 m a.s.l. (in the upper left-side tributary part of ablation area). Moreover, the modelled ice thickness derived from remotely sensed data is having Root Mean Square Error (RMSE) between 38 to 72 ± 10 m as compared with GPR measured ice thickness. [ABSTRACT FROM AUTHOR]

Rainfall is time concentric in nature. The spatial and temporal distribution of rainfall is changing over the Earth with recent anthropogenic warming. The study explores various characteristics of annual and seasonal concentration of rainfall across India using the precipitation concentration index (PCI) and its trends during the period of 1986–2015, based on a high‐resolution gauge‐based rainfall data (0.25 × 0.25°), obtained from the India Meteorological Department (IMD). An intercomparison is made with 11 other gridded rainfall datasets to infer whether these datasets can reasonably reproduce the spatiotemporal distribution of PCI and its trends in various homogenous rainfall regions of India or not. These datasets are categorized into gauge‐based (APHRODITE, GPCC, CPC), satellite‐derived (CHIRPS, PERSIANN‐CDR), and reanalysis (JRA‐55, MERRA‐2, NCEP‐2, PGF, ERA‐Interim, ERA‐5). On annual scale, about 8.52, 24.1, and 67.38% of area of India are under moderate, irregular, and strongly irregular rainfall distribution, respectively. Spatial variation of PCI in India is influenced by geographical factors such as latitude, longitude, and elevation. Significant increasing and decreasing trends in annual PCI have been observed in the northeast, eastern, and western coasts of India, respectively. Gridded data intercomparison suggests that the gauge‐based APHRODITE, GPCC, and satellite‐derived CHIRPS datasets better perform in capturing the temporal and spatial variation of PCI across India when compared to the IMD gridded dataset, whereas the ERA‐5 performs better among the reanalysis datasets. However, the rainfall datasets exhibited marked differences with the IMD while estimating the annual and seasonal trend and its magnitude across various regions of India. The JRA‐55 overestimated areas of positive trend and its magnitude on annual and seasonal scale. These findings have practical implications for hydroclimatic studies. [ABSTRACT FROM AUTHOR]