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三种下垫面温度及结冰预报模型研究
引用本文:牛生杰,李蕊,吕晶晶,孟蕾,柯怡明,杨志彪,熊守权.三种下垫面温度及结冰预报模型研究[J].地球物理学报,2011,54(4):909-917.
作者姓名:牛生杰  李蕊  吕晶晶  孟蕾  柯怡明  杨志彪  熊守权
作者单位:1. 南京信息工程大学气象灾害省部共建教育部重点实验室,大气物理学院,南京 210044; 2. 湖北省气象局,武汉 430074; 3. 湖北省恩施州气象局,湖北恩施 445000
基金项目:科技部科技支撑计划项目,和江苏省青蓝工程云雾降水物理学与气溶胶研究科技创新团队项目资助
摘    要:应用地表热量平衡方程,考虑太阳短波辐射、大气和地面的长波辐射、潜热、感热传输等能量之间的平衡,并考虑水汽、气溶胶、浮尘以及云等对太阳短波辐射的吸收和散射,建立了一种较实用的下垫面温度预报模型.应用湖北省恩施和金沙2009年冬季2月对土壤、水泥、沥青三种不同下垫面温度和自动气象站的常规气象要素观测进行模拟分析,并与该时段...

关 键 词:下垫面温度  热量平衡  数值预报模式  冬季
收稿时间:2010-05-26

Research on a numerical model for predicting three types of underlying surface temperature and ice
NIU Sheng-Jie,LI Rui,L Jing-Jing,MENG Lei,KE Yi-Ming,YANG Zhi-Biao,XIONG Shou-Quan.Research on a numerical model for predicting three types of underlying surface temperature and ice[J].Chinese Journal of Geophysics,2011,54(4):909-917.
Authors:NIU Sheng-Jie  LI Rui  L Jing-Jing  MENG Lei  KE Yi-Ming  YANG Zhi-Biao  XIONG Shou-Quan
Institution:1. Key Laboratory of Meteorological Disaster of Ministry of Education,School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2. Hubei Provincial Meteorological Bureau, Wuhan 430074 China; 3. Enshi Meteorological Bureau, Hubei Enshi 445000, China
Abstract:By using underlying surface energy balance method, considering the balance among solar short-wave radiation, atmospheric and ground long-wave radiations, latent heat fluxes and sensible heat fluxes, a forecasting model for three kinds of underlying surface temperature is established, in which the parameterizations of absorption and scattering of vapor, aerosols, dusts and clouds are also adopted. Based on the observations of three different underlying (including soil, concrete and asphalt) surface temperature and the automatically collected meteorological sensor measurements during January and February of 2009 winter in Enshi and Jinsha, Hubei province, the underlying surface temperature forecasting model is validated. The results show that all the predictions of the three kinds of underlying surface temperature at the two stations are well correlated with the observations more than 0.95, and the standard deviations are smaller than 2, and the frequencies of prediction errors between -3 and 3℃ are so high that respectively reach up to 95.20%, 96.41%, 93.57%, and 91.19%, 94.16%, 88.18%, which indicate the model has a good performance in the forecasts. Besides, the good predictions in three different weather conditions, especially when the underlying surface temperature is below 0℃, prove that it can be quite useful in the prediction of slippery road in winter.
Keywords:Underlying surface temperature  Energy balance  Numerical prediction model  Winter
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