气象Issue(1)：66-75,10.DOI:10.7519/j.issn.1000-0526.2014.01.008
基于大尺度模式产品的误差订正与统计降尺度气象要素预报技术
Bias Correction and Statistical Downscaling Meteorological Parameters Forecast Technique Based on Large-Scale Numerical Model Products
摘要
Abstract
Using self-adaption Kalman filter method,bias correction of surface parameter products of large-scale numerical prediction system are done.Through studying the appreciated method of obtaining bias correction coefficient,the filter method is improved and the forecasts of large-scale model parameters such as 2 m temperature and 10 m wind are improved accordingly.Based on corrected large-scale model forecast field and high resolution observatory field,downscaling vector function is obtained,and refined statistical downscaling meteorological parameter forecasts are created and it is an effective way to do high resolution meteorological parameter forecasts.关键词
模式产品误差订正/卡尔曼滤波/统计降尺度/精细化要素预报Key words
bias correction of numerical model products/Kalman filter/statistical downscaling/refined meteorological parameter forecast分类
天文与地球科学引用本文复制引用
佟华,郭品文,朱跃建,王东勇,刘志丽,陈国华,李莉,盛黎..基于大尺度模式产品的误差订正与统计降尺度气象要素预报技术[J].气象,2014,(1):66-75,10.基金项目
公益性行业（气象）科研专项（GYHY201006017）资助 （）
