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- W4225619904 abstract "Statistical downscaling is the technique of linking large-scale predictors and local-scale predictands through a relationship that is assumed to be helpful to generate local-scale climate change information from global climate model (GCM) driven large-scale future projection. The present study investigates downscaled seasonal and annual rainfall change scenarios over different locations of the Western Himalaya Region (WHR) of India using common predictors from ten GCMs of CMIP5 (Coupled Model Intercomparison Project phase 5) and reanalysis datasets from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research); and predictands from the IMD (India Meteorological Department) rain gauge stations. The combined EOF (Empirical Orthogonal Function) approach was used to develop location-specific statistical downscaling models over the WHR, and later on, some statistical skill scores based on error and agreement analysis were used to validate the model performance. Downscaled precipitation scenario using a multi-model ensemble of GCM under RCP4.5 (Representative Concentration Pathways 4.5) reveals a wetter climate during the 2020s, 2050s, and 2080s in the annual and monsoon time scale, whereas a drier climate is expected in the winter. Results show a possible intensification of the southwest monsoon and decrease in the frequency of western disturbances in the twenty-first century as the percentage changes of rainfall in monsoon will be higher than annual and winter time scale. The uncertainty in the monthly precipitation is projected to increase as time progresses from the 2020s to the 2080s. Higher uncertainty in precipitation is expected in the late pre-monsoon and early post-monsoon over WHR." @default.
- W4225619904 created "2022-05-05" @default.
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- W4225619904 date "2022-04-12" @default.
- W4225619904 modified "2023-09-26" @default.
- W4225619904 title "Is the Western Himalayan region vulnerable with respect to downscaled precipitation?" @default.
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- W4225619904 doi "https://doi.org/10.1007/s00704-022-04048-x" @default.
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