基于INCA和METRo的江苏省路面高温精细化预报

发布时间：2018-01-27 07:34

  本文关键词： 高速公路 路面温度 精细化预报试验　出处：《应用气象学报》2017年01期 　论文类型：期刊论文

【摘要】：使用INCA(Integrated Nowcasting through Comprehensive Analysis)多源资料融合分析和短临外推预报系统的预报结果作为气象强迫场,驱动一路面温度理论预报模型(Model of the Environment and Temperature of Roads,METRo),开展江苏省高速公路夏季路面高温预报试验,并使用公路沿线逐小时的路面温度观测资料对预报结果进行检验。结果表明:该预报方法能够较好地预报出高速公路沿线日最高路面温度的逐日变化趋势,以及日最高路面温度的大范围空间分布特征。平均日最高路面温度预报绝对偏差为4.1℃,平均相对偏差为10.8%。其中,日最高路面温度预报绝对偏差在5℃以内的站次占总数的64.5%,相对偏差在15%以内的站次占总数的74.6%,比常规业务预报方法分别提高了23.1%和25.3%。但该预报方法对较小的温度波动以及局地性较强的极端温度分布特征的预报技巧还需进一步提高。
[Abstract]:Using INCA(Integrated Nowcasting through Comprehensive Analysis). The forecast results of multi-source data fusion analysis and short-impending extrapolation forecasting system are taken as meteorological forcing fields. Model of the Environment and Temperature of Roads. High temperature prediction test of highway surface in Jiangsu Province in summer was carried out by MET Roo. The results show that the forecast method can well predict the daily variation trend of daily maximum pavement temperature along the highway. The average daily maximum pavement temperature forecast absolute deviation is 4.1 鈩，

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