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Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

机译：APCC全球气候模型对亚洲夏季季风降水变化的模拟能力

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摘要

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread among the ensemble members of individual model, strong teleconnection (correlation analysis) with SST, coefficient of variation, inter-annual variability, analysis of Taylor diagram, etc. suggest that there is a need to improve coupled model instead of uncoupled model for the development of a better dynamical seasonal forecast system.
机译：评估了11个亚太经济合作组织气候中心（APCC）全球气候模型（耦合和非耦合）在模拟亚洲（尤其是印度和东亚）的夏季夏季（6月至8月）季风降雨量变化方面的性能。详细信息使用APCC生成的后预报数据（提前3个月）提供，该数据基于多模型集合动态季节预测系统提供区域气候信息产品服务。在21年（1983-2003年）内分别对亚洲每个全球气候模型的技能进行了详细测试，并分别使用了针对印度和东亚陆地的各种统计量度对模拟的亚洲夏季风降雨（ASMR）进行了验证。 。分析发现，与耦合模型（如澳大利亚的预测海洋大气模型，国家环境预测中心和日本气象厅）相比，使用非耦合模型模拟的空间ASMR有很大差异。与非耦合模型相比，耦合模型中的模拟ASMR距离气候预测中心降水合并分析（CMAP）更近，尽管两个模型中的ASMR数量均被低估了。分析还发现在集成成员中模拟ASMR的分布很大（建议该模型的性能高度依赖于其初始条件）。海面温度（SST）与ASMR之间的相关分析表明，与未耦合模型相比，耦合模型与ASMR紧密相关（建议在耦合模型中很好地考虑了海-海相互作用）。使用各种统计手段对降雨进行的分析表明，与单个模型相比，多模型集合（MME）的效果更好，另外的研究表明，与整个亚洲季风降雨相比，印度和东亚的土地质量更有用。各种统计量度的结果，例如多模型合奏的技巧，单个模型的合奏成员之间的大范围分布，与SST的紧密遥相关（相关性分析），变异系数，年际变异性，泰勒图分析等，均表明了这一结果。为了开发更好的动态季节预报系统，需要改进耦合模型而不是非耦合模型。

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  • 来源
    《Theoretical and applied climatology》 |2015年第2期|109-122|共14页
  • 作者

    U. K. Singh; G. P. Singh; Vikas Singh;

  • 作者单位

    Georges Lemaitre Center for Earth and Climate Research, Earth and Life Institute UCL, Louvain-La-Neuve, Belgium,APEC Climate Center, Busan, South Korea;

    Department of Geophysics, Faculty of Science, Banaras Hindu University, Varanasi 221005, India;

    CAIR, Science and Technology Research Institute, University of Hertfordshire, Hatfield, UK;

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