Recent exacerbation of extreme precipitation events (EPEs) and related massive disasters in western Himalayas (WH) underpins the influence of climate change. Such events introduce significant losses to life, infrastructure, agriculture, in turn the country’s economy. This chapter provides an assessment of long-term (1979–2020) as well as recent changes (2000–2020) in precipitation extremes over WH for summer (JJAS) and winter (DJF) seasons. Different high-resolution multi-source climate datasets have been utilized to compute the spatiotemporal trends in intensity and frequency of EPEs. The hotspots of rising extremes over the region have been quantified using the percentile approach where daily precipitation exceeds the 95th percentile threshold at a given grid. The findings reveal geographically heterogeneous trends among different datasets; however, precipitation intensity and frequency show enhancement both spatially and temporally (though insignificant). For both seasons, dynamic and thermodynamic parameters highlight the role of increased air temperatures and, as a result, available moisture in the atmosphere, signifying the consequences of global warming. Rising precipitation extremes in summer are sustained by enhanced moisture supply combined with increased instability and updraft, due to orography, in the atmosphere whereas winter atmosphere is observing an increase in baroclinicity, available kinetic energy, vertical shear and instability, contributing to a rise in precipitation extremes.
In the present study, dynamically downscaled Weather Research and Forecasting (WRF) model simulations of winter (DJF) seasonal precipitation were evaluated over the Western Himalayas (WH) at grey zone configurations (at horizontal resolutions of 15 km (D01) and 5 km (D02)) and further validated using satellite-based (IMERG; 0.1°), observational (IMD; 0.25°), and reanalysis (ERA5; 0.25° and IMDAA; 0.108°) gridded datasets during 2001–2016. The findings demonstrate that both model resolutions (D01 and D02) are effective at representing precipitation characteristics over the Himalayan foothills. Precipitation features over the region, on the other hand, are much clearer and more detailed, with a significant improvement in D02, emphasizing the advantages of higher model grid resolution. Strong correlations and the lowest biases and root mean square errors indicate a closer agreement between model simulations and reanalyses IMDAA and ERA5. Vertical structures of various dynamical and thermodynamical features further confirm the improved and more realistic in WRF simulations with D02. Moreover, the seasonal patterns of upper tropospheric circulation, vertically integrated moisture transport, surface temperature and cloud cover show more realistic simulation in D02 compared to coarser domain D01. The categorical statistics reveal the efficiency of both D01 and D02 in simulating moderate and heavy precipitation events. Overall, our study emphasizes the significance of high-resolution data for simulating precipitation features specifically over complex terrains like WH.
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