globalchange  > 气候减缓与适应
DOI: 10.3390/w11020259
WOS记录号: WOS:000460899600078
论文题名:
The Future of Drought in the Southeastern US: Projections from Downscaled CMIP5 Models
作者: Keellings, David; Engstrom, Johanna
通讯作者: Keellings, David
刊名: WATER
EISSN: 2073-4441
出版年: 2019
卷: 11, 期:2
语种: 英语
英文关键词: consecutive dry days ; climate ; downscaled projections ; Southeast U ; S ; CMIP5
WOS关键词: MULTIMODEL ENSEMBLE ; PRECIPITATION ; CLIMATE ; EXTREMES ; TEMPERATURE ; STATES ; HYDROCLIMATOLOGY ; PROBABILITY ; SIMULATIONS ; VARIABILITY
WOS学科分类: Water Resources
WOS研究方向: Water Resources
英文摘要:

After being repeatedly struck by droughts in the last few decades, water managers and stakeholders in the Southeast U.S. dread the future extremes that climate change might cause. In this study, the length of future dry periods is assessed using a sub-ensemble of downscaled CMIP5 climate models, which are proven to perform well in precipitation estimations. The length of a dry spell with a twenty-year return period is estimated for the cold and warm seasons for two time periods; 2020-2059 and 2060-2099, and considering two emission scenarios: RCP 4.5 and 8.5. The estimates are then compared with historical dry spells and differences in length and geospatial distribution analyzed. Based on the findings of this paper, little change can be expected in dry spell length during the warm season. Greater changes are to be expected in the cold season in the southern half of Florida, where dry spells are expected to be up to twenty days shorter, while dry spells in Alabama, Mississippi and Tennessee are predicted to be up to twenty days longer. The changes predicted by the models are positively associated with emission trajectory and future time period.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/128561
Appears in Collections:气候减缓与适应

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作者单位: Univ Alabama, Dept Geog, 204 Farrah Hall,POB 870322, Tuscaloosa, AL 35487 USA

Recommended Citation:
Keellings, David,Engstrom, Johanna. The Future of Drought in the Southeastern US: Projections from Downscaled CMIP5 Models[J]. WATER,2019-01-01,11(2)
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