气象2017，Vol.43Issue(10)：1241-1248,8.DOI:10.7519/j.issn.1000-0526.2017.10.008
基于BJ-RUC模式预报产品的北京冬半年道面温度预报模型
Models of Road Surface Temperature in the Beijing Region in the Winter Half Year Based on the BJ-RUC Forecast Product
摘要
Abstract
In this paper we made a statistical analysis of the road surface temperature based on observations of the selected five road stations (A1027,A1325,A1412,A1414,A1512) and the meteorological elements output from the Beijing Rapid Update Cycle (BJ-RUC) numerical forecasting model with 3 km resolution from 1 November 2012 to 30 March 2013.We used the stepwise regression model methods to build three types of statistical models for hourly road surface temperature in 24 h in the winter half year for the different initial forecasting times (08:00,14:00,05:00 BT) and the different months.Then the best type is used to forecast the road surface temperature from 1 November 2013 to 30 March 2014.The results are as follows.The road surface temperature is significantly correlated to T2 and the short-wave radiation,but secondarily correlated to the long-wave radiation and humidity output from RUC.Compared to the type of statistical model with the only one factor for the previous day,the type of regression model with meteorological elements of remarkable correlation inserted performs better in terms of the road surface temperature forecast accuracy by more than 25 ％,and the prediction error decreases by 1C.For further enhancing the forecast accuracy rate,we selected the different initial times for verification so as to control error within ±3℃.The result of evaluation shows that the forecast value of the road surface temperature in the daytime is better than that over night,and sunny days are better than any other kinds of weather.关键词
道面温度/北京快速更新循环数值预报系统(BJ-RUC)预报/回归模型Key words
road surface temperature/Beijing Rapid Update Cycle (BJ-RUC) forecast/regression model分类
天文与地球科学引用本文复制引用
董颜,尤焕玲,郭文利,闵晶晶..基于BJ-RUC模式预报产品的北京冬半年道面温度预报模型[J].气象,2017,43(10):1241-1248,8.基金项目
北京市科技计划项目(Z151100002115040)和北京市自然科学基金项目(8174083)共同资助 （Z151100002115040）
