Research of Local Model of Weighted Mean Temperature of CORS Water Vapor Retrieval in Qingdao
-
摘要: 作为区域连续运行参考系统(CORS)反演大气可降水量的关键参数——大气加权平均温度,时空特性明显。为了提高区域CORS反演大气可降水量的精度和可靠性,利用青岛探空站2009-2011年3年的探空数据,分析得到地表温度Ts与加权平均温度Tm的相关系数R为0.877 6,为强线性相关;采用回归分析建立了青岛地区加权平均温度模型;利用该模型计算青岛地区2012年加权平均温度,与由探空数据计算的加权平均温度的平均偏差、标准差和均方根误差分别为0.307 K、3.359 K和3.384 K;将该模型应用在青岛CORS反演大气可降水量的计算中,与临近探空站计算的大气可降水汽相比,平均偏差、标准差和均方根误差分别为0.70 mm、3.48 mm和3.53 mm.研究表明,应用区域探空数据建立加权平均温度模型具有可行性,并可以在一定程度上提高区域CORS反演大气可降水量的精度和可靠性。Abstract: Atmospheric weighted mean temperature is a key parameter in CORS water vapor retrieval, and its variations are obvious in both time and space. In order to improve the accuracy and reliability of the atmospheric CORS, the surface temperature Ts and the weighted mean temperature Tm acquired by radiosonde station during 2009 to 2011 in Qingdao are analyzed. The correlation coefficient R of Ts and Tm is 0.877 6, which is strong linear correlation. The weighted mean temperature model of Qingdao area is established by regression analysis, and the weighted mean temperature in 2012, Qingdao is calculated. Compared to the weighted mean temperature calculated by radiosonde data, the average deviation, standard deviation and root mean square error are respectively 0.307 K, 3.359 K and 3.384 K. The model is applied to CORS water vapor retrieval in Qingdao, and the average deviation, standard deviation and root mean square error are respectively 0.70 mm、3.48 mm and 3.53 mm. The results show that it is feasible to apply the regional radiosonde data to establish the weighted mean temperature model and to improve the accuracy and reliability of the regional CORS water vapor retrieval to a certain extent.
-
[1] 李国平. 地基GPS遥感大气可降水量及其在气象中的应用研究[D]. 成都:西南交通大学, 2007. [2] BAKER H C, DODSON A H, PENNA N T, et al. Ground-based GPS water vapour estimation: potential for meteorological forecasting[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2001, 63(12):1305-1314. [3] WANG J, ZHANG L, DAI A. Global estimates of water-vapor-weighted mean temperature of the atmosphere for GPS applications[J]. Journal of Geophysical Research Atmospheres, 2005, 110(D21):2927-2934. [4] 李国翠,李国平,杜成华,等.华北地区地基GPS水汽反演中加权平均温度模型研究[J]. 南京气象学院学报,2009,32(1):80-86. [5] BEVIS M, BUSINGER S, CHISWELL S, et al. GPS Meteorology: Mapping zenith wet delays onto precipitable water.[J]. Journal of Applied Meteorology, 1994, 33(3):379-386. [6] ROSS R J, ROSENFELD S. Estimating mean weighted temperature [JP]of the atmosphere for Global Positioning System applications[J]. Journal of Geophysical Research Atmospheres, 1997, 102(102):21719-21730. [7] 于胜杰,柳林涛. 水汽加权平均温度回归公式的验证与分析[J]. 武汉大学学报(信息科学版), 2009, 34(6):741-744. [8] 李黎,田莹,谢威,等. 基于探空资料的湖南地区加权平均温度本地化模型研究[J]. 大地测量与地球动力学, 2017, 37(3):282-286. [9] 李建国,毛节泰,李成才,等. 使用全球定位系统遥感水汽分布原理和中国东部地区加权“平均温度”的回归分析[J]. 气象学报, 1999, 57(3):283-292. [10] YAO Y B, ZHU S, YUE S Q. A globally applicable, season-specific model forestimating the weighted mean temperature of the atmosphere[J]. Journal of Geodesy, 2012, 86(12):1125-1135. [11] 姚朝龙,罗志才,刘立龙,等. 顾及地形起伏的中国低纬度地区湿延迟与可降水量转换关系研究[J]. 武汉大学学报(信息科学版), 2015, 40(7):907-912.[12] 刘焱雄,陈永奇,刘经南. 利用地面气象观测资料确定对流层加权平均温度[J]. 武汉大学学报(信息科学版), 2000, 25(5):400-404. [12] 李剑锋,王永前,胡伍生. 地基GPS水汽反演中区域大气加权平均温度模型[J]. 测绘科学技术学报, 2015(1):13-17. [13] DUAN J M. GPS meteorology:Direct estimation of the absolute value of precipitable water.[J]. Journal of Applied Meteorology, 1996, 35(6):830-838. [14] INGOLD T, PETER R, KMPFER N. Weighted mean tropospheric temperature and transmittance determination at millimeter-wave frequencies for ground-based applications[J]. Radio Science, 1998, 33(4):905-918. [15] 谷晓平,王长耀,吴登秀. GPS水汽遥感中的大气加权平均温度的变化特征及局地算式研究[J]. 气象科学, 2005, 25(1):79-83. [16] 宋淑丽,朱文耀,程宗颐,等. GPS信号斜路径方向水汽含量的计算方法[J]. 天文学报, 2004, 45(3):338-346. [17] 刘智敏,窦世标,李斐,等. 青岛CORS站与探空站获取的大气可降水量对比分析[J]. 山东科技大学学报(自然科学版), 2017, 36(1):21-28.
点击查看大图
计量
- 文章访问数: 306
- HTML全文浏览量: 27
- PDF下载量: 70
- 被引次数: 0