姚宜斌, 郭健健, 张豹, 胡羽丰. 湿延迟与可降水量转换系数的全球经验模型[J]. 武汉大学学报 ( 信息科学版), 2016, 41(1): 45-51. DOI: 10.13203/j.whugis20140585
引用本文: 姚宜斌, 郭健健, 张豹, 胡羽丰. 湿延迟与可降水量转换系数的全球经验模型[J]. 武汉大学学报 ( 信息科学版), 2016, 41(1): 45-51. DOI: 10.13203/j.whugis20140585
YAO Yibin, GUO Jianjian, ZHANG Bao, HU Yufeng. A Global Empirical Model of the Conversion Factor Between Zenith Wet Delay and Precipitable Water Vapor[J]. Geomatics and Information Science of Wuhan University, 2016, 41(1): 45-51. DOI: 10.13203/j.whugis20140585
Citation: YAO Yibin, GUO Jianjian, ZHANG Bao, HU Yufeng. A Global Empirical Model of the Conversion Factor Between Zenith Wet Delay and Precipitable Water Vapor[J]. Geomatics and Information Science of Wuhan University, 2016, 41(1): 45-51. DOI: 10.13203/j.whugis20140585

湿延迟与可降水量转换系数的全球经验模型

A Global Empirical Model of the Conversion Factor Between Zenith Wet Delay and Precipitable Water Vapor

  • 摘要: 利用2005~2011年的全球大地测量观测系统(global geodetic observing system,GGOS)Atmosphere提供的2.5°×2°(经度×纬度)的天顶湿延迟(zenith wet delay,ZWD)格网数据和欧洲中尺度天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)提供的2.5°×2°可降水量(precipitable water vapor,PWV)格网数据,在全球范围内计算得到各格网点的地基GPS水汽反演关键参数Π-1的时间序列,分析了其时空分布特征,建立了一种转换系数Π的全球经验模型。该模型无需站点气象数据,仅与站点经纬度、年积日和海拔相关。利用未参与建模的2012年的GGOS Atmosphere和ECMWF格网数据、2012年661个无线电探空站的探空资料对模型进行精度检验。结果显示,采用格网数据检验,其偏差的平均值(Bias)为-0.179 mm,均方根误差(root mean square error,RMS)的平均值为1.806 mm;采用无线电探空资料进行检验,其Bias为0.465 mm, RMS为0.789 mm。结果都表现出了较小的系统性偏差与较高的精度,说明所建立的湿延迟与可降水量转换系数模型在全球范围内具有较高的精度与稳定性。

     

    Abstract: We calculated the key parameters of ground-based GPS water vapor inversion in each grid point and got the time series of the conversion factor Π-1by using the global zenith wet delay (ZWD) grid data with a spatial resolution of 2.5°×2°(longitude × latitude) provided by global geodetic observing system (GGOS) Atmosphere and precipitable water vapor (PWV) products with a same spatial resolution provided by European Centre for Medium-Range Weather Forecasts (ECMWF) from 2005 to 2011, followed by the analysis of temporal and spatial characteristic. We establish a global empirical model of Π which is related to the site's latitude, longitude, altitude and the day of year (doy) without meteorological data. Then we used the GGOS Atmosphere and ECMWF grid data that not involved in modeling in 2012, 661 radiosonde stations' data in 2012 to test accuracy of the model. The results show that the mean deviation (Bias) is -0.179 mm and root mean square error (Root Mean Square Error, RMS) is 1.806 mm from the grid data; the Bias is 0.465 mm, RMS is 0.789 mm from radiosonde data. Both of them indicate the accuracy and stability of the model is high with a small systematic bias on a global scale.

     

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