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  • 1
    Online Resource
    Online Resource
    Wiley ; 2023
    In:  International Journal of Climatology Vol. 43, No. 1 ( 2023-01), p. 219-239
    In: International Journal of Climatology, Wiley, Vol. 43, No. 1 ( 2023-01), p. 219-239
    Abstract: This study evaluates the ability of 23 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating extreme climate events over China. The multimodel ensemble (MME) performs better than most individual models in reproducing the climatological mean distribution of all extreme indices. The MME can reproduce well the climatological mean distributions of five extreme climate indices over China, including annual total precipitation (PTOT), maximum consecutive 5‐day precipitation (RX5), simple daily intensity (SDII), maximum daily maximum temperature (TXX), and minimum daily minimum temperature (TNN), with Taylor skill scores exceeding 0.7. SDII and TXX are the most skilful precipitation and temperature extreme indices simulated by the MME, respectively. The MME has relatively lower skill in simulating the climatological mean distribution of warm days (TX90P) and cold nights (TN10P) over China. Future projections of these extreme climate indices by the end of the 21st century are explored with the MME under the SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 scenarios. The PTOT and RX5 in northwestern China are all projected to increase by more than 30% under SSP5‐8.5. R20 is projected to increase by 4–5 days over southeastern China under SSP5‐8.5. There are fewer (more) consecutive dry days over north China (south China), with a change of 5 days under SSP5‐8.5. The extreme temperature indices, including TX90P, TXX, and TNN, all increase with time and higher SSP scenarios. The three indices increase by 40–55%, 4–6°C, and 4–7°C under SSP5‐8.5 over east China, respectively. The TN10P decreases by more than 6% over east China. The changes in these extreme indices under SSP1‐2.6 and SSP2‐4.5 are similar to those under SSP5‐8.5 but with a smaller magnitude. Large uncertainties still exist in the future projections, especially under the high SSP scenarios.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1491204-1
    detail.hit.zdb_id: 1000947-4
    SSG: 14
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