Journal of Geo-information Science ›› 2015, Vol. 17 ›› Issue (8): 895-901.doi: 10.3724/SP.J.1047.2015.00895

• Orginal Article • Previous Articles     Next Articles

Analysis on High Accuracy Surface Modeling in Regional Rainfall Estimation Combined with TRMM Data

ZHANG Tao1,2(), LI Baolin1,3,*(), ZHAO Na1, XU Lili1,2   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2015-01-18 Revised:2015-03-05 Online:2015-08-10 Published:2015-08-05
  • Contact: LI Baolin;
  • About author:

    *The author: SHEN Jingwei,


High Accuracy Surface Modeling (HASM) method has theoretically solved issues of hill peak smoothing and oscillation phenomenon at edges, and its modeling accuracy is much better than the traditional interpolation methods such as Inverse Distance Weighting (IDW), Spline and Kriging. HASM has been successfully applied to the spatial mapping in multiple fields, such as population density, soil properties and climatic elements, etc. However, as the number and distribution of meteorological rain gauges are limited, getting the accurate precipitation distribution maps based on HASM is still a challenge. Additionally, remote sensing rainfall estimation data, which can provide better spatial information of the precipitation, but without accurate rainfall values, may play an important role. Therefore, in this study, we combine these two data sets together based on HASM model to estimate regional rainfall. Central and western China (25°~35°N, 105°~115°E), which are featured by extensive high mountains and plains, is chosen as the study area to model the spatial distribution of its total precipitation in 2010. Using satellite rainfall estimation, the Tropical Rainfall Measuring Mission (TRMM) 3B43 data is chosen as the background field for HASM modeling. Then, we compare its results with respect to the classical methods (including IDW, Spline and Kriging) based (also used as background fields) HASM modeling. Results show that TRMM based HASM method has higher accuracy and its results exhibit a better spatial pattern for precipitation simulation than those from the other methods. The MAE and RMSE of TRMM based HASM simulation results are 125.15 mm and 155.80 mm, respectively. The simulation errors of the best simulation results using the other methods are respectively 53.6% and 54.5% higher than TRMM based HASM simulation results. Besides, its relative error in each sub-region is also smaller than the other methods. In the multiple applications of spatial elements modeling, e.g. meteorological elements modeling, where there is not enough sampling sites to characterize the spatial structure of an element, the accuracy of HASM modeling will be limited. Therefore, combining it with supplementary information to compensate the deficiency of limited sampling sites will contribute to the production of better results for HASM applications.

Key words: high accuracy surface modeling (HASM), TRMM, spatial interpolation, precipitation