研究论文

误差订正空间分解法在中国的应用

  • 王林 ,
  • 陈文
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  • 1.中国科学院大气物理研究所季风系统研究中心, 北京, 100190; 2.中国科学院大学, 北京, 100049
王林(1986-),男,河南洛阳人,博士研究生,主要从事干旱研究. E-mail: wang_lin@mail.iap.ac.cn

收稿日期: 2013-04-25

  网络出版日期: 2013-10-10

基金资助

国家自然科学基金项目“东亚冬季风系统变异及其内动力学机理研究”(编号:41025017)和“全球变暖背景下两类太平洋增温型对东亚冬、夏季风和台风活动的影响及其机理”(编号:41230527)资助.

Application of Bias Correction and Spatial Disaggregation in Removing Model Biases and Downscaling over China

  • Wang Lin ,
  • Chen Wen
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  • 1. Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100190; 2. University of Chinese Academy of Sciences, Beijing, 100049

Received date: 2013-04-25

  Online published: 2013-10-10

摘要

目前全球气候模式在区域尺度上存在较大的模拟系统偏差和空间分辨率低的缺陷, 误差订正空间分解法(BCSD)可以有效去除其系统误差, 并能应用到降尺度研究中, 在国际上得到了广泛应用。在系统介绍BCSD方法基本理论和步骤的基础上, 基于耦合模式比较计划第五阶段(CMIP5)的多模式数据集研究了该方法在中国区域降水模拟订正和降尺度的适用性。结果表明, 该方法能够很好地降低全球气候模式在中国区域降水的模拟误差, 并且该方法不具有模式依赖性, 对34个模式的模拟都有很好的改进, 显示出很好的应用前景。进一步讨论了BCSD方法的适用范围, 并利用该方法和CMIP5模拟资料构建了一套经过误差订正和降尺度的未来中国区域降水多模式、多情景的数据集。

本文引用格式

王林 , 陈文 . 误差订正空间分解法在中国的应用[J]. 地球科学进展, 2013 , 28(10) : 1144 -1153 . DOI: 10.11867/j.issn.1001-8166.2013.10.1144

Abstract

Global Climate Models (GCM) are the primary tools for studying past climate change and evaluating the projected future response of climate system to changing atmospheric composition. However, the stateofart GCMs contain large biases in regional or local scales and are often characterized by low resolution which is too coarse to provide the regionalscale information required for regional climate change impact assessment. A popular technique, Bias Correction and Spatial Disaggregation (BCSD), are widespreadly employed to improve the quality of the raw model output and downscaling throughout the world. Unfortunately, this method has not been applied in China. Consequently, the detailed principle and procedure of BCSD are introduced systematically in this study. Furthermore, the applicability of BCSD over China is also examined based on an ensemble of climate models from phase five of the Coupled Model Intercomparison Project (CMIP5), though the excellent performance of it has been validated for other parts of the world in many works. The result shows that BCSD is an effective, modelindependent approach to removing biases of model and downscaling. Finally, application scope of BCSD is discussed, and a suite of fineresolution multimodel climate projections over China is developed based on 34 climate models and two emissions scenarios (RCP4.5 and RCP8.5) from CMIP5.

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