Seasonality and Variability of Snowfall to Total Precipitation Ratio over High Mountain Asia Simulated by the GFDL High-Resolution AM4
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Seasonality and Variability of Snowfall to Total Precipitation Ratio over High Mountain Asia Simulated by the GFDL High-Resolution AM4

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  • Journal Title:
    Journal of Climate
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    The ratio of snowfall to total precipitation (S/P ratio) is an important metric that is widely used to detect and monitor hydrologic responses to climate change over mountainous areas. Changes in the S/P ratio over time have proved to be reliable indicators of climatic warming. In this study, the seasonality and interannual variability of monthly S/P ratios over High Mountain Asia (HMA) have been examined during the period 1950–2014 based on a three-member ensemble of simulations using the latest GFDL AM4 model. The results show a significant decreasing trend in S/P ratios during the analysis period, which has mainly resulted from reductions in snowfall, with increases in total precipitation playing a secondary role. Significant regime shifts in S/P ratios are detected around the mid-1990s, with rainfall becoming the dominant form of precipitation over HMA after the changepoints. Attribution analysis demonstrates that increases in rainfall during recent decades were primarily caused by a transformation of snowfall to rainfall as temperature warmed. A logistic equation is used to explore the relationship between the S/P ratio and surface temperature, allowing calculation of a threshold temperature at which the S/P ratio equals 50% (i.e., precipitation is equally likely to take the form of rainfall or snowfall). These temperature thresholds are higher over higher elevations. This study provides an extensive evaluation of simulated S/P ratios over the HMA that helps clarify the seasonality and interannual variability of this metric over the past several decades. The results have important socioeconomic and environmental implications, particularly with respect to water management in Asia under climate change.
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    Journal of Climate, 35(17), 5573-5589
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    0894-8755;1520-0442;
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