广西地区大气水汽转换系数的K值模型  

Modeling for transformation coefficient K value of water vapor in Guangxi

作　　者：刘立龙[1,2,3] 黎峻宇 蔡成辉 林国标[2,3] 黄良珂[1,2,3] LIU Li-long LI Jun-yu CAI Cheng-hui LIN Guo-biao HUANG Liang-ke(Guangxi Scientific Experiment Center of Mining, Metallurgy and Environment College of Geomatics Engineering and Geoinformations Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China)

机构地区：[1]桂林理工大学广西矿冶与环境科学实验中心,广西桂林541004 [2]桂林理工大学测绘地理信息学院,广西桂林541004 [3]桂林理工大学广西空间信息与测绘重点实验室,广西桂林541004

出　　处：《桂林理工大学学报》2017年第1期103-107,共5页Journal of Guilin University of Technology

基　　金：国家自然科学基金项目(41064001);广西自然科学基金项目(2012GXNSFAA053183;2012GXNSFGA060001);广西研究生教育创新计划项目(YCSZ2013077);广西空间信息与测绘重点实验室项目(桂科能1207115-07);广西矿冶与环境科学实验中心课题(KH2012ZD004);广西"八桂学者"岗位专项经费项目

摘　　要：利用中国低纬度地区20个无线电探空站2008—2012年探空资料,分析大气水汽转换系数K值与地理位置间的关系,建立广西地区不需气象资料的K值模型。比较不同模型的精度、适用性,分析逐年增加样本数对预测精度的影响,探索如何更好地建立广西地区K值模型。结果表明:(1)在广西地区,Emardson模型总体的内、外符合精度与高程模型相当,Emardson模型与积分模型计算K值符合较好,总体内符合均方误差为0.002 1,外符合均方误差为0.001 8;(2)与高程模型相比,无需考虑高程因子的Emardson模型在广西地区适用性更强;(3)通过逐年增加样本数进行建模不能保证提高模型的预测精度,用最近的两年数据建模能够更好地预测第3年的K值。According to the 2008 -2012 sounding data of 20 radiosonde stations at the low- latitude of China , this paper analyzed the relationship between the Kvalue and location , built coef ficient K value model without meteorological data in Guangxi region. By comparing the accuracy and applicability of different models,the im-pact on prediction accuracy is analyzed by gradually increased samples year by year, and better ways of model-ing is found for the K value model in Guangxi. The results show that ： （ 1） Emardson model has the same inner precision and outer precision as the elevation model. Emardson is in good agreement with the integral method in calculating the K value. Emardson model＇s overall precision of inner coincidence MSE is 0. 002 1 , outer preci-sion MSE is 0. 001 8.（2） Without elevation factor , Emardson model has stronger appl icabi l i ty than the eleva-tion model. （ 3 ） It is not guaranteed to improve the prediction accuracy of the model by increasing the number of samples each year. With recent two years data, the value of K of the th ird year can be better predicted.

关 键 词：广西地区 K值模型 位置因子 精度 适用性 预测 

分 类 号：P426[天文地球—大气科学及气象学] P407