›› 2012, Vol. 14 ›› Issue (5): 599-610.doi: 10.3724/SP.J.1047.2012.00599

• ARTICLES • Previous Articles     Next Articles

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

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