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A Global Assessment of Precipitable Water Vapor Derived From GNSS Zenith Tropospheric Delays With ERA5, NCEP FNL, and NCEP GFS Products
Earth and Space Science ( IF 3.1 ) Pub Date : 2021-07-20 , DOI: 10.1029/2021ea001796 Biyan Chen 1, 2 , Wenkun Yu 1 , Wei Wang 1, 2 , Zhetao Zhang 3 , Wujiao Dai 1
Earth and Space Science ( IF 3.1 ) Pub Date : 2021-07-20 , DOI: 10.1029/2021ea001796 Biyan Chen 1, 2 , Wenkun Yu 1 , Wei Wang 1, 2 , Zhetao Zhang 3 , Wujiao Dai 1
Affiliation
In precipitable water vapor (PWV) retrievals from Global Navigation Satellite System (GNSS) data, the two essential parameters, namely, surface pressure (
) and weighted mean temperature (
), are often not available due to the lack of collocated meteorological sensors or improper data retention. Hence, this study presents a comprehensive assessment of the GNSS PWV retrieval using alternative 
and 
data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis 5, National Centers for Environmental Prediction Final (NCEP FNL) Analysis, and NCEP Global Forecast System (GFS) products. The assessment was based on 691 globally distributed GNSS stations over the entire year of 2019. The zenith hydrostatic delay (ZHD) and 
integrated from the three types of numerical weather prediction (NWP) atmospheric profiles achieve varying accuracies in ranges of 2.4–3.0 mm and 1.1–1.5 K, respectively. PWVs estimated using ZHD and 
integrated from the NWP profiles obtain accuracies of about 1.6–2.0 mm. These PWVs are slightly better than those using ZHD and 
calculated by empirical models with surface pressure and temperature from the NWP datasets. The assessment of PWVs with the global pressure and temperature 2 wet model yields a root mean square (RMS) error of 3.73 mm. The relative RMS decreases from 30%-40% at high latitudes (70–80°S/N) to ∼5% around the equator. The monthly variations of relative RMS show that (a) low-latitude regions outperform the high-latitude regions, and (b) winter months have significantly worse performance than other months in both hemispheres.
中文翻译：
使用 ERA5、NCEP FNL 和 NCEP GFS 产品对源自 GNSS 天顶对流层延迟的可降水水汽进行全球评估
在水汽（PWV）从全球导航卫星系统（GNSS）数据，所述两个基本参数，即表面压力（检索）并加权平均温度（），往往不缺乏置气象传感器或不当的可用因数据保留。因此，本研究使用来自欧洲中期天气预报中心 (ECMWF) ReAnalysis 5、国家环境预测中心 (NCEP FNL) 分析和 NCEP 全球预报系统的替代数据和数据，对 GNSS PWV 反演进行了全面评估(GFS) 产品。该评估基于 2019 年全年全球分布的 691 个 GNSS 站。综合三种类型的数值天气预报 (NWP) 大气剖面，分别在 2.4-3.0 毫米和 1.1-1.5 K 范围内实现不同的精度。使用 ZHD 估计并从 NWP 剖面整合的PWV获得约 1.6-2.0 毫米的精度。这些 PWV 比使用 ZHD 和由 NWP 数据集的表面压力和温度经验模型计算得出。使用全球压力和温度 2 湿模型评估 PWV 产生 3.73 毫米的均方根 (RMS) 误差。相对 RMS 从高纬度 (70–80°S/N) 的 30%-40% 降低到赤道周围的 5%。相对 RMS 的月变化表明 (a) 低纬度地区优于高纬度地区，(b) 冬季月份的表现明显低于两个半球的其他月份。
更新日期：2021-08-19
) and weighted mean temperature (), are often not available due to the lack of collocated meteorological sensors or improper data retention. Hence, this study presents a comprehensive assessment of the GNSS PWV retrieval using alternative and data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis 5, National Centers for Environmental Prediction Final (NCEP FNL) Analysis, and NCEP Global Forecast System (GFS) products. The assessment was based on 691 globally distributed GNSS stations over the entire year of 2019. The zenith hydrostatic delay (ZHD) and integrated from the three types of numerical weather prediction (NWP) atmospheric profiles achieve varying accuracies in ranges of 2.4–3.0 mm and 1.1–1.5 K, respectively. PWVs estimated using ZHD and integrated from the NWP profiles obtain accuracies of about 1.6–2.0 mm. These PWVs are slightly better than those using ZHD and calculated by empirical models with surface pressure and temperature from the NWP datasets. The assessment of PWVs with the global pressure and temperature 2 wet model yields a root mean square (RMS) error of 3.73 mm. The relative RMS decreases from 30%-40% at high latitudes (70–80°S/N) to ∼5% around the equator. The monthly variations of relative RMS show that (a) low-latitude regions outperform the high-latitude regions, and (b) winter months have significantly worse performance than other months in both hemispheres.
中文翻译：
使用 ERA5、NCEP FNL 和 NCEP GFS 产品对源自 GNSS 天顶对流层延迟的可降水水汽进行全球评估
在水汽（PWV）从全球导航卫星系统（GNSS）数据，所述两个基本参数，即表面压力（检索
）并加权平均温度（），往往不缺乏置气象传感器或不当的可用因数据保留。因此，本研究使用来自欧洲中期天气预报中心 (ECMWF) ReAnalysis 5、国家环境预测中心 (NCEP FNL) 分析和 NCEP 全球预报系统的替代数据和数据，对 GNSS PWV 反演进行了全面评估(GFS) 产品。该评估基于 2019 年全年全球分布的 691 个 GNSS 站。综合三种类型的数值天气预报 (NWP) 大气剖面，分别在 2.4-3.0 毫米和 1.1-1.5 K 范围内实现不同的精度。使用 ZHD 估计并从 NWP 剖面整合的PWV获得约 1.6-2.0 毫米的精度。这些 PWV 比使用 ZHD 和由 NWP 数据集的表面压力和温度经验模型计算得出。使用全球压力和温度 2 湿模型评估 PWV 产生 3.73 毫米的均方根 (RMS) 误差。相对 RMS 从高纬度 (70–80°S/N) 的 30%-40% 降低到赤道周围的 5%。相对 RMS 的月变化表明 (a) 低纬度地区优于高纬度地区，(b) 冬季月份的表现明显低于两个半球的其他月份。
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