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Drought losses in China might double between the 1.5 °C and 2.0 °C warming.


ABSTRACT: We project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and "intensity-loss rate" function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration pattern for the 1.5 °C and 2.0 °C global warming above the preindustrial at 2020-2039 and 2040-2059, respectively. With increasing drought intensity and areal coverage across China, drought losses will soar. The estimated loss in a sustainable development pathway at the 1.5 °C warming level increases 10-fold in comparison with the reference period 1986-2005 and nearly threefold relative to the interval 2006-2015. However, limiting the temperature increase to 1.5 °C can reduce the annual drought losses in China by several tens of billions of US dollars, compared with the 2.0 °C warming.

SUBMITTER: Su B 

PROVIDER: S-EPMC6196488 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

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Drought losses in China might double between the 1.5 °C and 2.0 °C warming.

Su Buda B   Huang Jinlong J   Fischer Thomas T   Wang Yanjun Y   Kundzewicz Zbigniew W ZW   Zhai Jianqing J   Sun Hemin H   Wang Anqian A   Zeng Xiaofan X   Wang Guojie G   Tao Hui H   Gemmer Marco M   Li Xiucang X   Jiang Tong T  

Proceedings of the National Academy of Sciences of the United States of America 20181001 42


We project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and "intensity-loss rate" function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipita  ...[more]

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