中国降水未来情景的降尺度模拟

Downscaling simulation for the scenarios of precipitation in China

基于长时间序列(1964～2007年)的全国降水观测数据,结合经纬度数据以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均降水降尺度模型的基础上,运用高精度曲面建模(HASM)方法对经过降尺度分析的HadCM3的A1Fi、A2a和B2a三种情景T1～T4时段的全国未来平均降水进行高精度曲面模拟。模拟结果显示,在T1～T4时段内,A1Fi、A2a和B2a三种情景的全国平均降水均呈持续增加趋势。其中,平均降水在A1Fi情景中增加速度最快,B2a情景中增加速度最慢;A1Fi和A2a两种情景的平均降水均呈加速增加趋势,而B2a情景的平均降水则呈减速增加趋势。模拟结果表明,本文构建的降尺度模拟方法可以有效地实现IPCC GCM的低分辨率的降水情景数据降尺度转换成高分辨率的降水数据。

Because of most GCM simulated data with a coarse resolution （about 200-500 kin）, it is difficult to use these data to assess impacts of precipitation change on various ecosystems on regional and local scales, although the data can be used to effectively predict the future precipitation change on a global scale. To address the above issue, the downscaling models of precipitation are developed with the spatial statistical method in this paper, combined with series data of DEM, latitude and longitude, slope and aspect index. For validating the downscaling models, the annual precipitation is simulated under the three scenarios of HadCM3 A1Fi, A2a and B2a during the periods T1 （from 1961 to1990）, T2 （from 2010 to 2039）, T3 （from 2040 to 2069）, and T4 （from 2070 to 2099）. In the simulation process, the data resolution is downscaled from 3.75°× 0. 125° to I km× 1 km by High Accuracy Modeling （HASM）. Simulation results show that annual precipitation would continue to increase in the future 100 years under the three scenarios of HadCM3 the A1Fi, A2a and B2a. During the periods from T1 to T4, the rising rates of annual pre- cipitation is the greatest under scenario A1Fi, the average levels under scenario A2a, and the lowest under scenario B2a, which might increase per decade by 14.48 ram, 10.92 mm, and 7. 21 mm, respectively. Furthermore, annual precipitation would have a changing trend of accelerated increase under scenarios A1Fi and A2a, but the increasing trend would be slowing under scenario B2a in the next 100 years. The results show, which the precipi- tation data with a coarse resolution of IPCC GCM can be effectively downscaled to a highresolution precipitation data that could be used to assess the ecosystems and their services on the regional and local scales.