文化大學機構典藏 CCUR:Item 987654321/41805
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    Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/41805


    Title: The influence of single model ensemble on the simulated extratropical interannual variability
    Authors: Wang, CC (Wang, Chia-Chi)
    Hsu, HH (Hsu, Huang-Hsiung)
    Chen, YL (Chen, Yu-Luen)
    Yang, JK (Yang, Jun-Kai)
    Hung, MP (Hung, Meng-Pai)
    Contributors: 大氣系所
    Keywords: NORTH-ATLANTIC OSCILLATION
    SEA-ICE
    COLD WINTERS
    PRECIPITATION
    TEMPERATURES
    PERFORMANCE
    SYSTEM
    TRENDS
    CMIP5
    Date: 2018-12
    Issue Date: 2019-01-16 10:29:18 (UTC+8)
    Abstract: This study compares the interannual variance of boreal winter near-surface temperature (DJF T2m) with and without performing single model ensemble (SME) in seasonal hindcasts (DEMETER, ENSEMBLES, and NCEP CFSv2) and historical climate simulations (CMIP5). The results demonstrate that the extratropical temperature variability is significantly reduced after performing SME even though the signal in the tropical Pacific remains strong. Cancellation between positive and negative perturbations simulated by individual model members, of both tropical and extratropical origins, leads to the under-simulation. The atmospheric circulation induced by tropical Pacific sea surface temperature is not well represented in global climate models and the simulation is further deteriorated by SME, leading to an unrealistically weak interannual variance of simulated winter temperature in North America. Similar effect was also found in North Eurasia where winter temperature is strongly influenced by atmospheric internal variability and its interaction with land and ice/snow in the middle-high latitudes. The SME procedure should be avoided when evaluating the model performance in simulating the higher-order long-term statistics (such as variance). Variance of individual models should be calculated first and then averaged among members. Models used in seasonal forecast and long-term climate simulation already have good capability in simulating the long-term statistics of stochastic processes in the extratropics, although the capability in accurately simulating the temporal variation is still poor.
    Appears in Collections:[Department of Atmospheric Sciences & Graduate Institute of Earth Science / Atmospheric Science ] journal articles

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