顾及多因子影响的中国区域T_(m)模型精化研究  

Refinement of T_(m) Model Considering the Influence of Multi-Factors in China Region

作　　者：李浩杰 刘立龙 黄良珂 莫智翔 蔡猛 LI Haojie;LIU Lilong;HUANG Liangke;MO Zhixiang;CAI Meng(College of Geomatics and Geoinformation,Guilin University of Technology,319 Yanshan Street,Guilin 541006,China;Guangxi Key Laboratory of Spatial Information and Geomatics,319 Yanshan Street,Guilin 541006,China)

机构地区：[1]桂林理工大学测绘地理信息学院,桂林市541006 [2]广西空间信息与测绘重点实验室,桂林市541006

出　　处：《大地测量与地球动力学》2022年第4期393-397,共5页Journal of Geodesy and Geodynamics

基　　金：国家自然科学基金(42064002);广西自然科学基金(2017GXNSFDA198016);广西“八桂学者”岗位专项。

摘　　要：利用中国区域2015~2017年探空数据,建立一种顾及地表温度、地表水汽压、高程和纬度的中国区域大气加权平均温度T_(m)模型(BET模型)。以2018年探空站T_(m)数据为参考值,分析BET模型精度,并与Bevis模型和GPT3模型进行对比。结果表明,BET模型年均RMSE与bias分别为3.15 K和0.04 K,相比于Bevis模型、1°×1°分辨率的GPT3模型和5°×5°分辨率的GPT3模型,年均RMSE分别降低29.2%、32.8%和39.1%,年均bias分别降低96.4%、96.7%和97.4%,且该模型在中国区域不同高程和纬度上的精度与稳定性优于Bevis模型和GPT3模型。This paper uses sounding data from 2015 to 2017 to establish a China regional T_(m) model(BET model)that considers surface temperature,surface water vapor pressure,elevation and latitude.Using the T_(m) data of sounding station in 2018 as a reference value,we analyze the accuracy of BET model,and compare it with the Bevis and GPT3 models.The results show that the average annual RMSE and bias of BET model are 3.15 K and 0.04 K,respectively.Compared with the Bevis model,the GPT3 models with resolutions of 1°×1°and 5°×5°,the average annual RMSE decreases by 29.2%,32.8%,and 39.1%;the average annual bias decreases by 96.4%,96.7%,and 97.4%,respectively.The accuracy and stability of the model at different elevations and latitudes in China are better than the Bevis and GPT3 models.

关 键 词：大气加权平均温度 水汽压 多因子T_(m)模型 GPT3模型 中国地区 

分 类 号：P228[天文地球—大地测量学与测量工程]