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      Spatiotemporal characteristics of dry‐wet abrupt alternation events in China during 1960–2018

      1 , 1 , 2 , 1 , 2
      International Journal of Climatology
      Wiley

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          Abstract

          The dry‐wet abrupt alternation (DWAA) can lead to consecutive drought–flood hazards with high socioeconomic losses. Over the past decades, China has suffered huge economic losses of more than $15 billion due to drought and flood hazards. With the rapid socio‐economic development, the damages caused by DWAA are expected to be more serious. However, the spatiotemporal patterns of DWAA were poorly known at the continental scale. In this study, DWAA was identified by the short‐cycle dry‐wet abrupt alternation index (SDWAI) across eight eco‐regions of China from 1960 to 2018. Results showed that DWAA mainly occurred in humid/semihumid region (III), subtropical humid region (V), and tropical humid region (VI). Seasonally, DWAA is mostly concentrated in summer, with the highest frequency in June and July. Meanwhile, 67% of the total DWAA events were observed in nonsummer seasons. From 1960 to 2018, the intensity of dry to wet (DTW) events has increased by 0.015/10 year. The north and west of China (except region III, V, VI, and VII) experienced an increasing trend in DTW intensity, but a decreasing trend in WTD intensity. DWAA events in some parts of China were frequently observed, which was related to the variability in precipitation patterns caused by climate change. The identification of local hotspots and seasonal distribution of DWAA will support decision‐making for warning and mitigating the drought and flood hazards.

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                Author and article information

                Contributors
                Journal
                International Journal of Climatology
                Intl Journal of Climatology
                Wiley
                0899-8418
                1097-0088
                December 30 2022
                September 19 2022
                December 30 2022
                : 42
                : 16
                : 9612-9625
                Affiliations
                [1 ] Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences Beijing China
                [2 ] University of Chinese Academy of Sciences Beijing China
                Article
                10.1002/joc.7850
                49325e3e-c98d-4210-8763-da65a99f6805
                © 2022

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