不同加权平均温度模型对大气可降水量影响分析

Influence analysis of different weighted mean temperature models on precipitable water vapor

加权平均温度(WMT)是地基全球卫星导航系统(GNSS)气象学中解算大气可降水量(PWV)时的一个重要物理量,利用国内四个典型地区2019年的历史气象探空数据计算各剖面的WMT,构建了适合当地的WMT线性统计模型,并对所建模型、工程上常用的几种WMT统计模型及利用其换算得到的PWV进行了对比.根据统计结果可知:对于精度较高的需求,构建适合当地的统计模型是很有必要的,另外,各统计模型中Mao模型和Mendes模型的精度相对较高,在不具备建模条件的情况下可以优先考虑.本统计结果可为其他涉及WMT的工程应用提供参考.

The weighted mean temperature(WMT)is an important parameter to calculate precipitable water vapor in ground based GNSS meteorology.Four local linear statistical models of the WMT were derived from their historical radiosonde data in 2019.The comparison with other WMT models and the precipitable water vapor calculated by them show that Mao model and Mendes model have higher precision in the four cities,and it is necessary to establish local model for high-precision applications.The findings provide valuable reference for engineering fields concerned with the weighted mean temperature.