摘要
基于GIS的面雨量估算方法和基于模式输出的雨量产品都无法解决分辨率过低的问题,并且都不同程度地忽略了中小尺度地形对降水的影响.回顾了各种统计学降尺度方法,使用NCEP/NCAR提供的2011年4—9月的6 h一次的再分析资料,以及江苏省气象台提供的全省20多个常规站降水实况观测资料,结合高分辨率DEM数据,利用偏最小二乘法(PLS)设计了一套考虑地形因子动力作用的面雨量降尺度方案.通过合理选择和构造大尺度预报因子,地形因子动力作用参数化,回归分析与空间插值相结合的面雨量降尺度方案,成功还原了研究区域内代表站的实况降水序列,并绘制出研究区域内高分辨率的面雨量空间分布图.
Both GIS-based areal precipitation estimation and gridded precipitation data from GCM outputs have the problem of poor resolution, and to some extent neglect the influence of small or medium landform on precipitation distribution. A variety of statistical downscaling methods are briefly reviewed in this paper. Taking into account of the dynamic effect of geographic factors, a new downscaling scheme for areal precipitation estimation is proposed u- sing 6 hour temporal resolution re-analysis data of NCEP/NCAR from April to September of 2010, and observational precipitation data from more than 20 weather stations in Jiangsu. The scheme chooses and constructs appropriate large-scale predictor, and retrieves the small-scale geographic factors from high resolution DEM, parameterizes the dynamic effect of geographic factors, and integrates the regression analysis, Partial Least Squares （PLS） and spatial interpolation. The actual precipitation series in the researched weather stations are successfully retrieved by the pro- posed scheme and the high-resolution spatial distribution of areal precipitation are drawn.
出处
《南京信息工程大学学报（自然科学版）》
CAS
2013年第5期439-448,共10页
Journal of Nanjing University of Information Science & Technology（Natural Science Edition）
基金
公益性行业(气象)科研专项(GYHY200806002)
关键词
面雨量
降尺度
地形因子
偏最小二乘
areal precipitation
downscaling
geographic factors
Partial Least Squares （PLS）
