高速公路路面夜间逐时温度预报方法研究

A Method for Forecasting Hourly Expressway Surface Temperature during Night Time

为了提高高速公路路面的低温预报预警能力,根据地表能量平衡原理、夜间净辐射及路面热特性参数与高速公路路表温度之间变化的关系,建立了基于当日实时温度等相关气象要素观测信息的路表温度变化预报方程。收集了2016年至2017年江苏省高速公路路面逐小时温度等相关气象观测资料,选取具有代表性的13个站点,应用统计方法确定了模型中路面特性参数B0值,分析其路面温度变化特征,确定了其参数并检验其预报效果。结果表明:反演得到的参数B0值变化范围为3. 17~3. 67,随路面建筑材质不同而略有差异,同一高速公路路面比较接近;由其得到的模拟值与实测值相关系数高,平均偏差和标准差小,模型效率高。预报值与实测值偏差在1℃以内的超过50%,预报值与实测值偏差在3℃以内的超过90%,说明提出的预报方程具有较好的实用性和较高的预测精度,预报结果可靠,可以用来做高速公路路面温度的预测。

In order to improve the ability of prediction and early warning of expressway surface temperature,according to the principle of surface energy balance,the relationship among net radiation at night,surface thermal characteristics and surface temperature of expressway,a road surface temperature change forecast equation based on the observation information of relevant meteorological elements such as daily real-time temperature is established.With the collected relevant meteorological observation data such as hourly temperature of expressway road surface in Jiangsu Province from 2016 to 2017,selecting 13 representative stations,the road characteristic parameter B0 in the model is determined by statistical method.Its pavement temperature change characteristics are analyzed,its parameters are determined,and its forecasting effect is tested.The result shows that(1)The parameter B0 obtained by the inversion varies from 3.17 to 3.67,which varies slightly with the pavement construction material,and the values of the same expressway pavement are relatively close.(2)The simulated value obtained from the forecast equation has high correlation coefficient with the measured value,the average deviation and standard deviation are small,and the model efficiency is high.The deviation within 1℃between the forecast value and the measured value is more than 50%,and the deviation within 3℃between the forecast value and the measured value is more than 90%,indicating that the proposed forecast equation has good practicability and high prediction accuracy,it can be used to predict the road surface temperature of expressways.