地球信息科学学报

地球信息科学学报 ›› 2012, Vol. 14 ›› Issue (5): 599-610.doi: 10.3724/SP.J.1047.2012.00599

• 本期要文(可全文下载) • 上一篇    下一篇

高精度曲面建模的中国气候降尺度模型

王晨亮1,2, 岳天祥1*, 范泽孟1, 赵娜1,2, 孙晓芳1,2   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101;
    2. 中国科学院大学,北京 100049
  • 收稿日期:2012-05-08 修回日期:2012-08-20 出版日期:2012-10-25 发布日期:2012-10-25
  • 通讯作者: 岳天祥(1963-),男,博士,研究员,研究方向为资源环境地学模型与系统模拟。E-mail: yue@lreis.ac.cn E-mail:yue@lreis.ac.cn
  • 作者简介:王晨亮(1984-),男,山东青岛市人,博士研究生,研究方向为资源环境模型集成与系统模拟。E-mail:wangcl@lreis.ac.cn
  • 基金资助:

    国家杰出青年科学基金项目(40825003);国家重点基础研究计划"973"项目(2010CB950904);国家自然科学基金项目(41023010)资助。

HASM-based Climatic Downscaling Model over China

WANG Chenliang1,2, YUE Tianxiang1*, FAN Zemeng1, ZHAO Na1,2, SUN Xiaofang1,2   

  1. 1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 10010, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-05-08 Revised:2012-08-20 Online:2012-10-25 Published:2012-10-25

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摘要：

与站点统计降尺度插值和动力降尺度相比,高精度曲面建模(HASM)降尺度,具有不需大尺度预报因子,直接从GCM结果构建区域上高空间分辨率的未来气候模拟曲面的优势。HASM降尺度将未来气候,分为历史观测拟合的气候基准值和GCM未来气候变化值进行模拟,精度明显高于传统方法,但常系数全局拟合的气候基准值忽略了降水分布的空间非平稳性,导致降水模拟受到较大影响。为增强降水降尺度的气候背景值的描述能力,通过分析全国尺度降水的非线性非平稳性特点,提出耦合空间变系数气候基准值的HASM空间变系数降尺度模型(HASM-SVDM)以改进HASM对非平稳要素的降尺度能力,并以1961-2010年全国气温降水观测数据结合地形特征信息,利用HASM降尺度方法对HadCM3的A1Fi、A2a和B2a 3种情景的1961-1990、2010-2039、2040-2069和2070-2099时段的全国未来气温与降水进行降尺度模拟。分析表明,耦合全局线性模型的HASM常系数降尺度模型适合全国气温的降尺度模拟,而耦合空间变系数拟合的HASM-SVDM增强了空间非平稳背景值的描述能力,模拟的空间分布更能体现降水总体的非均匀分布趋势,适合全国降水的降尺度模拟。

关键词: 空间插值, 降尺度, 全国尺度, 高精度曲面建模, 空间变系数

Abstract:

Compared with statistical downscaling methods and dynamical downscaling methods, HASM-based downscaling methods, which do not need large-scale predictor, can directly create high-resolution climatic surfaces under GCM scenarios. HASM downscaling methods separate future climate elements into climate base value and prospect climatic change value. This method is termed HASM-Constant Coefficient Downscaling Model (HASM-CDM) because climatic base value is fitted by global constant regression model and climatic change value is interpolated by HASM. Although HASM can obtain higher accuracy than other classical methods, precipitation base value fitted by (HASM-CDM) lost spatial non-stationary features of precipitation, which decreases the accuracy of precipitation simulation. The relationship between precipitation and auxiliary variables such as DEM and some topographical factors may change according to geographical location which can not be represented by HASM-CDM. HASM-Spatially Variable Coefficient Downscaling Model (HASM-SVDM) was developed which integrated with spatially variable coefficient regression model and data transformation in this paper. HASM-SVDM uses variable coefficient regression and data transformation to solve accuracy problem of climatic base value. The mean annual temperature (MAT) and mean annual precipitation (MAP) are constructed under different scenarios of HadCM3 A1Fi, A2a and B2a during the periods T1 (1961-1990), T2 (2010-2039), T3 (2040-2069) and T4 (2070-2099) by HASM downscaling models. The results show that HASM-constant coefficient downscaling model integrated with global linear model is applicable to the temperature downscaling simulation, while HASM-spatially variable coefficient downscaling model improves spatial non-stationary base value, and is appropriate for the precipitation downscaling modeling at the national level.

Key words: high accuracy surface modeling (HASM), downscaling, national level, spatially variable coefficient, spatial interpolation