广西不同下垫面轨温对比及其与气象条件的关系研究

Comparison of Rail Temperature on Different Underlying Surfaces and Its relationship with Meteorological Conditions in Guangxi

利用广西水体、林地、城市、耕地4种下垫面的钢轨温度(轨温)和常规气象要素,研究不同下垫面轨温的特征及其与气象条件的关系,并在不同条件下建立多元回归拟合方程。结果表明:轨温与气温日最高(最低)值的差值为0~18℃(0~5℃)。不同下垫面的逐日轨温极值与气温极值呈显著的正相关,表明气温是影响轨温变化的决定性因子之一。典型高温、低温过程中,轨温与气温极值变化的同步性较好。与不区分天空类型相比,雾天、多云到阴天、晴天到少云3种不同天空类型下轨温与气温极值的相关性有所提升。在3种条件下利用气温、降水量、相对湿度和风速4个气象因子对4种下垫面的轨温进行多元回归拟合,所得轨温拟合值与观测值的相关系数均超过了0.90,平均绝对误差为0.42~3.33℃,除晴天到少云类型,其余类型的相关值为0.94~0.99,平均绝对误差不超过2.58℃,拟合预测效果可信。

Based on the observation of rail temperature and meteorological measurements under four different underlying surfaces of water,forest,urban and cultivated land in Guangxi,the characteristics of the rail temperature on different underlying surfaces and its relationship with meteorological conditions are analyzed,and then the multiple regression fitting equations under different conditions are established.The results show that the value of difference between the daily maximum(minimum)of rail temperature and the daily maximum(minimum)of the air temperature is 018℃(05℃).There is a significant positive correlation between daily rail temperature extremum and air temperature extremum in different underlying surfaces,indicating that air temperature is one of the decisive factors affecting the change of rail temperature.In typical high temperature and low temperature processes,there is a good synchronization between the extremum of rail temperature and air temperature.Compared to not distinguishing between sky types,the correlation between rail temperature extremum and air temperature extremum is improved under three different sky types:foggy day,cloudy to overcast day and sunny to less cloudy day.Under these three conditions,the four meteorological elements(air temperature,precipitation,relative humidity and wind speed)are used to carry out multiple regression for the rail temperature of the four underlying surfaces.It is found that the correlation coefficients between the calculated and the observed rail temperature all surpass 0.90 and the mean absolute error(MAE)is between 0.42 and 3.33℃.Except for the sunny to less cloudy type,the correlation coefficients of the other types are in the range of 0.940.99,and the MAE is less than 2.58℃,which implies that the fitting prediction effect of rail temperature is reliable.