雪
降水
耦合模型比对项目
环境科学
融水
气候学
水当量
水资源
大气科学
气候变化
气候模式
气象学
地理
生态学
地质学
生物
作者
Marianne Cowherd,L. Ruby Leung,Manuela Girotto
标识
DOI:10.1088/1748-9326/acd804
摘要
Abstract Seasonal snow is an integral part of the global water supply and storage system. 
Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. 
These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an early melt. 
The Standardized SWE Index (SWEI) ranks the current status of SWE for a given location compared to a baseline condition and identifies the existence, but not the cause, of snow drought. 
In this work, we use estimates of SWE, temperature, and precipitation from nine Coupled Model Intercomparison Project phase 6 (CMIP6) models to quantify the frequency, severity, and type of snow droughts globally for historical and future scenarios.
Compared to a historical baseline (1850--1900) total snow drought frequency more than doubles under SSP2-4.5 and SSP5-8.5; all of the increase in snow drought frequency comes from an increase in warm droughts.
The probability distribution of future SWEI in major snowy basins around the world are likely to be centered on more negative values, which corresponds to more severe drought and, with only moderate changes in distribution spread, more frequent drought. 
CMIP6 simulations pinpoint snow drought as an emerging global threat to water resources and highlight the need to explore higher resolution future models that better capture complex mountain topography, wildland fires, and snow-forest interactions.
科研通智能强力驱动
Strongly Powered by AbleSci AI