模式地形高度偏差对地面2m气温预报的影响
投稿时间: 2018-03-23  最后修改时间: 2018-03-29  点此下载全文
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作者单位E-mail
智协飞 南京信息工程大学 zhi@nuist.edu.cn 
吴佩 南京信息工程大学  
俞剑蔚 江苏省气象台  
慕建利 中国气象局公共气象服务中心  
赵倩 中国气象局公共气象服务中心  
基金项目:北极阁开放研究基金南京大气科学联合研究中心重点项目(NJCAR2016ZD04);中国气象局公共气象服务中心委托项目"基于统计降尺度的多模式精细化预报系统”;江苏高校优势学科建设工程资助项目(PAPD)
中文摘要:本文利用2016年1月1日-12月31日全球预报系统(GFS, Global Forecasting System)1-5d的2m气温预报资料,以及同期中国地面气象站2m气温观测资料,研究模式地形高度偏差对地面2m气温预报的影响。结果表明:模式地形高度偏差太大可严重影响模式预报性能,导致预报误差太大。随着模式预报时效延长,预报均方根误差也略有增加。比较模式地形高度偏差和预报时效对于模式预报性能的影响,发现模式地形高度偏差对于模式预报效果的影响更加显著。二种地形订正方案,即不做温度垂直订正的线性回归以及对温度进行垂直订正的线性回归都能显著减小模式预报的误差,后者的订正效果更好。
中文关键词:2m气温  预报  统计降尺度  模式地形高度偏差  订正
 
The effect of the topographic altitude bias of the numerical model on the 2m air temperature forecast
Abstract:Based on the 1-5-day forecasts of Global Forecasting System (GFS), as well as the observations from meteorological stations in China, the effect of the model topographic altitude bias (TAB) on the surface air temperature forecast has been investigated. The results showed that if the TAB is too large, it may severely affect the forecast skill, and lead to too large forecast error. As the forecast lead time becomes longer, the root-mean-square error (RMSE) of the 2m air temperature forecast increases slightly as well. By comparing the effect of the TAB and the increasing forecast lead time on the model forecast performance, the effect of the TAB on the model forecast skill is more significant. Both two types of calibration schemes, namely the linear regression without vertical correction and with vertical correction can reduce the model forecast errors, and the latter has better calibration performance.
keywords:2m air temperature, forecast, statistical downscaling, model topographic altitude bias, correction
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