The Hindu-Kush Karakoram Himalaya (HKKH) mountains feed the most important Asian river systems, and changes in snow and precipitation dynamics in this area could severely impact on water availability for downstream populations, agriculture and energy production, ecosystems and biodiversity. Despite their importance, precipitation and snowpack characteristics in the HKKH region are still poorly known, owing to the limited availability of surface observations. Global Climate Models (GCMs), despite their coarse spatial resolution, may be effective in providing a smooth, but coherent, picture of the large scale temporal and spatial patterns of these two variables. We investigate how the spatial and temporal variability of precipitation and snowpack in the HKKH region is represented in historical and future simulations of the state-of-the-art GCMs participating in the CMIP5 effort, comparing the results to the main, currently available, observational datasets including surface- and satellitebased observations and reanalysis data.
Historical and future changes in precipitation and snow depth in the Hindu-Kush Karakoram Himalaya region, as seen by CMIP5 models
Elisa Palazzi;Silvia Terzago;Susanna Corti;Antonello Provenzale
2015
Abstract
The Hindu-Kush Karakoram Himalaya (HKKH) mountains feed the most important Asian river systems, and changes in snow and precipitation dynamics in this area could severely impact on water availability for downstream populations, agriculture and energy production, ecosystems and biodiversity. Despite their importance, precipitation and snowpack characteristics in the HKKH region are still poorly known, owing to the limited availability of surface observations. Global Climate Models (GCMs), despite their coarse spatial resolution, may be effective in providing a smooth, but coherent, picture of the large scale temporal and spatial patterns of these two variables. We investigate how the spatial and temporal variability of precipitation and snowpack in the HKKH region is represented in historical and future simulations of the state-of-the-art GCMs participating in the CMIP5 effort, comparing the results to the main, currently available, observational datasets including surface- and satellitebased observations and reanalysis data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.