Estimating the motion of atmospheric water vapor using the Global Positioning System

Water vapor is both an important component in the atmosphere for the transport of energy and a noise source for space geodetic observations of the Earth's surface, such as from GPS and interferometric SAR (InSAR) measurements. GPS data collected from ground receivers are sensitive to the total amount of water vapor above the antenna and data from continuously operating GPS receivers are routinely used to estimate delays caused by atmospheric water vapor. Using these time series of atmospheric delay, we have estimated the motion of atmospheric water vapor above GPS networks. The motion above each site is determined by comparing the time series from different sites and estimating relative time offsets in these time series. These are then used to determine the velocity field of the atmospheric delays as they move across the network. We have compared the results with similar estimates inferred from geostationary satellite data and found clear correlation on several occasions. Such results can be useful for improving the understanding of the energy transport in the atmosphere, the spatial interpolation of water vapor, and for calibrating InSAR observations for delays caused by water vapor. Electronic Publication     

The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction

For lack of sufficient observations, the definition of atmospheric moisture fields (including water vapor and clouds) remains a difficult problem whose solution is essential for improved weather forecasts. Moisture fields are under-observed in time and space, primarily because the distribution of water in the atmosphere is highly variable. Because water is important in weather and climate processes, a significant effort has been expended to develop new or improved remote sensing systems to mitigate this problem. One such system uses ground-based Global Positoning System (GPS) receivers to make accurate all-weather estimates of atmospheric refractivity at very low cost. This largely unanticipated application of GPS had led to a new and potentially significant upper-air observing system for meteorological agencies and researchers around the world (Wolfe & Gutman, 2000). The first and most mature use of GPS for this purpose is in the estimation of integrated (total column) precipitable water vapor above a fixed site (Duan et al., 1996, with improvements by Niell, 1996, and Fang et al., 1998). The techniques currently used by the National Oceanic and Atmospheric Administration's Forecast Systems Laboratory (NOAA/FSL) to collect, process, and distribute GPS water vapor observations are mature and almost ready for transition to operational use. NOAA/FSL has shown that GPS integrated water vapor data can be used effectively in objective (i. e., numerical weather prediction) and subjective weather forecasting. To understand the strengths and limitations of GPS for weather forecasting, it is essential to understant what types of information are currently available to forecasters and modelers, and how models use the data to describe the current and probable future state of the atmosphere. It is also important to understand the current trends in modern weather prediction to ensure that GPS observing system play a significant role in the future. ? 2001 John Wiley & Sons, Inc.     

成都地区地基GPS观测网遥感大气可降水量的初步试验

利用首个成都地区地基GPS观测网2004年7～9月30s间隔的测量数据，通过Bernese GPS SoftwareV4．2解算出30min间隔的天顶总延迟量，结合自动气象站获得的气象资料计算出30min间隔的GPS遥感的大气可降水量。与根据气象探空站探测资料算出的可降水量进行统计对比，确定出本次GPS遥感可降水量试验的精度为3．09mm，两种可降水量时间序列呈现高度的一致性。同时验证了计算对流层加权平均温度的Bevis经验公式在成都地区的适用性。     

Single receiver phase ambiguity resolution with GPS data

Global positioning system (GPS) data processing algorithms typically improve positioning solution accuracy by fixing double-differenced phase bias ambiguities to integer values. These “double-difference ambiguity resolution” methods usually invoke linear combinations of GPS carrier phase bias estimates from pairs of transmitters and pairs of receivers, and traditionally require simultaneous measurements from at least two receivers. However, many GPS users point position a single local receiver, based on publicly available solutions for GPS orbits and clocks. These users cannot form double differences. We present an ambiguity resolution algorithm that improves solution accuracy for single receiver point-positioning users. The algorithm processes dual- frequency GPS data from a single receiver together with wide-lane and phase bias estimates from the global network of GPS receivers that were used to generate the orbit and clock solutions for the GPS satellites. We constrain (rather than fix) linear combinations of local phase biases to improve compatibility with global phase bias estimates. For this precise point positioning, no other receiver data are required. When tested, our algorithm significantly improved repeatability of daily estimates of ground receiver positions, most notably in the east component by approximately 30% with respect to the nominal case wherein the carrier biases are estimated as real values. In this “static” test for terrestrial receiver positions, we achieved daily repeatability of 1.9, 2.1 and 6.0 mm in the east, north and vertical (ENV) components, respectively. For kinematic solutions, ENV repeatability is 7.7, 8.4, and 11.7 mm, respectively, representing improvements of 22, 8, and 14% with respect to the nominal. Results from precise orbit determination of the twin GRACE satellites demonstrated that the inter-satellite baseline accuracy improved by a factor of three, from 6 to 2 mm up to a long-term bias. Jason-2/Ocean Surface Topography Mission precise orbit determination tests results implied radial orbit accuracy significantly below the 10 mm level. Stability of time transfer, in low-Earth orbit, improved from 40 to 7 ps. We produced these results by applying this algorithm within the Jet Propulsion Laboratory’s (JPL’s) GIPSY/OASIS software package and using JPL’s orbit and clock products for the GPS constellation. These products now include a record of the wide-lane and phase bias estimates from the underlying global network of GPS stations. This implies that all GIPSY–OASIS positioning users can now benefit from this capability to perform single-receiver ambiguity resolution.     

Experiment on Driving Precipitable Water Vapor from Ground-Based GPS Network in Chengdu Plain

The estimates of total zenith delay are derived using Bernese GPS Software V4. 2 based on GPS data every 30 s from the first measurement experiment of a ground-based GPS network in Chengdu Plain of Southwest China during the period from July to September 2004. Then the estimates of 0.5 hourly precipitable water vapor (PWV) derived from global positioning system (GPS) are obtained using meteorological data from automatic weather stations (AWS). The comparison of PWV derived from GPS and those from radiosonde observations is given for the Chengdu station, with RMS (root mean square) differences of 3.09m. The consis- tency of precipitable water vapor derived from GPS to those from radiosonde is good. It is concluded that Bevis’ empirical formula for estimating the weighted atmospheric mean temperature can be applicable in Chengdu area because the relationship of GPS PWV with Bevis’ formula and GPS PWV with radiosonde method shows a high correlation. The result of this GPS measurement experiment is helpful both for accumu- lating the study of precipitable water vapor derived from GPS in Chengdu areas located at the eastern side of the Tibetan Plateau and for studying spatial-temporal variations of regional atmospheric water vapor through many disciplines cooperatively.     

A case study of using Raman lidar measurements in high-accuracy GPS applications

This paper investigates the impact of rapid small-scale water vapor fluctuations on GPS height determination. Water vapor measurements from a Raman lidar are used for documenting the water vapor heterogeneities and correcting GPS signal propagation delays in clear sky conditions. We use data from four short observing sessions (6 h) during the VAPIC experiment (15 May–15 June 2004). The retrieval of wet delays from our Raman lidar is shown to agree well with radiosonde retrievals (bias and standard deviation (SD) were smaller than 1 and 2.8 mm, respectively) and microwave radiometers (from two different instruments, bias was 6.0/−6.6 mm and SD 1.3/3.8 mm). A standard GPS data analysis is shown to fail in accurately reproducing fast zenith wet delay (ZWD) variations. The ZWD estimates could be improved when mean post-fit phase residuals were removed. Several methodologies for integrating zenith lidar observations into the GPS data processing are also presented. The final method consists in using lidar wet delays for correcting a priori the GPS phase observations and estimating a scale factor for the lidar wet delays jointly with the GPS station position. The estimation of this scale factor allows correcting for a mis-calibration in the lidar data and provides in the same way an estimate of the Raman lidar instrument constant. The agreement of this constant with an independent determination using radiosonde data is at the level of 1–4%. The lidar wet delays were derived by ray-tracing from zenith pointing measurements: further improvement in GPS positioning is expected from slant path lidar measurements that would properly account for water vapor anisotropy.     

GPS/MET中水汽转换参数本地化研究与时空特性分析

随着全球定位系统(GPS)的高速发展,它在测绘科研领域的应用范围不断扩大,在GPS气象方向,可以通过地基GPS技术计算得到水汽转换参数,从而计算大气可降水量.使用本地化的水汽转换参数能有效提高GPS水汽反演的精度.本文利用中国西南地区2015-2018年12个探空站点数据,计算得到中国西南地区的年、季度、月和每日水汽转换参数,实现了水汽转换参数本地化研究.分析发现,在一定范围内,水汽转换参数Π随着站点高度的增加而逐渐增加,且我国西南地区的水汽转换参数Π的时空分布具有明显的气候分布特点和纬度地带性.     

Experiment on driving precipitable water vapor from ground-based GPS network in Chengdu Plain

The estimates of total zenith delay are derived using Bernese GPS Software V4. 2 based on GPS data every 30 s from the first measurement experiment of a ground-based GPS network in Chengdu Plain of Southwest China during the period from July to September 2004. Then the estimates of 0.5 hourly precipitable water vapor (PWV) derived from global positioning system (GPS) are obtained using meteorological data from automatic weather stations (AWS). The comparison of PWV derived from GPS and those from radiosonde observations is given for the Chengdu station, with RMS (root mean square) differences of 3.09m. The consistency of precipitable water vapor derived from GPS to those from radiosonde is good. It is concluded that Bevis’ empirical formula for estimating the weighted atmospheric mean temperature can be applicable in Chengdu area because the relationship of GPS PWV with Bevis’ formula and GPS PWV with radiosonde method shows a high correlation. The result of this GPS measurement experiment is helpful both for accumulating the study of precipitable water vapor derived from GPS in Chengdu areas located at the eastern side of the Tibetan Plateau and for studying spatial-temporal variations of regional atmospheric water vapor through many disciplines cooperatively.     

基于EMD和WD联合算法的GPS水汽时间序列的周期性振荡分析

水汽在全球水文和气候变化上扮演着非常重要的角色。选取了中国台湾GPS水汽时间序列作为算例数据,分析了水汽与地理环境的对应关系,得到中国台湾地区的大气水汽分布主要受纬度,地形特征和气候条件控制的结论。利用经验模态分解（EMD）和小波分解（WD）联合算法将中国台湾GPS站水汽的长时间序列和短时间序列进行分解,探测出每个GPS站都存在周年、半周年、天、半天的周期振荡,再结合地理、气候因素分析周期振荡产生的物理原因,得出结论:年周期的水汽振荡主要是由于在中国台湾特殊地形条件下年季风周期变化引起的;半周年的振荡主要是由于夏季风与冬季风对中国台湾地区的交替控制所导致的;而导致水汽日变化的原因则是海陆风环流、海陆风-山谷风叠加环流;天顶可降水量（PWV）半日振荡的振幅较小,则主要是因为受到了太阳辐射加热引起的局地热对流的影响所导致。     

利用GPS反解大气水汽含量

介绍地基和空基ＧＰＳ气象技术,简要讨论了ＧＰＳ遥感大气水汽含量对误差源。     

4D GPS water vapor tomography: new parameterized approaches

Water vapor is a key variable in numerical weather prediction, as it plays an important role in atmospheric processes. Nonetheless, the distribution of water vapor in the atmosphere is observed with a coarse resolution in time and space compared to the resolution of numerical weather models. GPS water vapor tomography is one of the promising methods to improve the resolution of water vapor measurements. This paper presents new parameterized approaches for the determination of water vapor distribution in the troposphere by GPS. We present the methods and give first results validating the approaches. The parameterization of voxels (volumetric pixels) by trilinear and spline functions in ellipsoidal coordinates are introduced in this study. The evolution in time of the refractivity field is modeled by a Kalman filter with a temporal resolution of 30 s, which corresponds to the available GPS-data rate. The algorithms are tested with simulated and with real data from more than 40 permanent GPS receiver stations in Switzerland and adjoining regions covering alpine areas. The investigations show the potential of the new parameterized approaches to yield superior results compared to the non parametric classical one. The accuracy of the tomographic result is quantified by the inter-quartile range (IQR), which is decreased by 10–20% with the new approaches. Further, parameterized voxel solutions have a substantially smaller maximal error than the non parameterized ones. Simulations show a limited ability to resolve vertical structures above the top station of the network with GPS tomography.     

利用GPS/BDS/GLONASS/Galileo组合PPP反演大气可降水量

为进一步改善精密单点定位（PPP）探测大气可降水量（PWV）的性能,本文提出采用GPS/BDS/GLONASS/Galileo组合PPP进行PWV反演的方法,并利用国内3个MGEX（multi-GNSS experiment）观测站的实测数据,对GPS/BDS/GLONASS/Galileo组合PPP在大气水汽探测方面的性能进行了评估。试验结果表明：相较于GPS PPP、GPS/BDS组合PPP和GPS/GLONASS组合PPP,GPS/BDS/GLONASS/Galileo组合PPP估计天顶对流层延迟（ZTD）的初始化时间分别缩短了33%、26%、20%,且能获得更高精度的ZTD估值和PWV信息,在大气水汽探测方面的性能更优。     

Remote sensing of water vapor content using ground-based GPS data

Spatial and temporal resolution of water vapor content is useful in improving the accuracy of short-term weather prediction.Dense and continuously tracking regional GPS arrays will play an important role in remote sensing atmospheric water vapor content.In this study,a piecewise linear solution method was proposed to estimate the precipitable water vapor (PWV) content from ground-based GPS observations in Hong Kong.To evaluate the solution accuracy of the water vapor content sensed by GPS,the upper air sounding data (radiosonde) that are collected locally was used to calculate the precipitable water vapor during the same period.One-month results of PWV from both ground-based GPS sensing technique and radiosonde method are in agreement within 1～2 mm.This encouraging result will motivate the GPS meteorology application based on the establishment of a dense GPS array in Hong Kong.     

地基GPS反演水汽影响因素分析

地基GPS(Global Position System)技术日益成熟,气象观测应用此技术逐渐增多,但对此影响因素的分析不是太多。本文首先阐述了地基GPS遥感水汽原理,然后结合雾灵山GPS气象观测试验数据,利用GAMIT软件解算此期间数据的对流层延迟量,主要分析了影响地基GPS遥感水汽的几项因素,得出测站精度与ZTD精度变化趋势图、星历精度与ZTD(Troposphere Zenith Delay)精度变化趋势图和不同参考站对ZTD的影响。其结果对GPS遥感大气水汽有一定的参考价值。     

地基GPS遥感大气水汽含量的误差分析

讨论并分析了利用地基ＧＰＳ遥感大气水汽含量时的误差源及其数值评估。其误差来自三个方面：一是计算ＧＰＳ讯号传输时间中湿延迟的误差;二是将该湿延迟转换为大气水汽含量公式中测定转换因子的误差;三是转换模型的误差。     

GPS可降水汽含量在强降雨过程中的特征分析

针对水汽在大气中易于变化,高时空分辨率水汽资料的欠缺,造成强降雨短时临近的预报水平不高的问题,探讨分析了GPS水汽反演的精度。利用香港CORS数据,通过GAMIT软件解算获得各测站1 h大气可降水量时间序列,将其与探空数据获得的液态水含量（PWV）和实际降水量进行比较分析。结果表明,GPS／PWV与Radio／PWV在整体变化趋势上具有很好的一致性,其相关系数大于0.9;GPS／PWV与Radio／PWV精度相当,两者平均偏差小于1 mm,均方根误差小于3 mm;GPS反演的大气可降水量与实际降水量具有较好的对应关系,能够精确地监测到水汽变化的过程,可以用于水汽的监测和预报研究。      

利用超快速星历进行数值天气预报的可行性研究

实时获取高时空分辨率的大气水汽是制约数值天气预报准确性的关键问题。基于地基GPS遥感大气水汽原理,结合香港CORS网的实测数据进行处理,对由IGU超快速星历、IGS精密星历和探空资料解算的大气可降水量(Precipitable Water Vapor,PWV)序列进行比较分析。实验结果表明,利用超快速星历估计PWV用于数值天气预报是切实可行的。     

Climate applications of a global, 2-hourly atmospheric precipitable water dataset derived from IGS tropospheric products

A global, 2-hourly atmospheric precipitable water (PW) dataset is produced from ground-based GPS measurements of zenith tropospheric delay (ZTD) using the International Global Navigation Satellite Systems (GNSS) Service (IGS) tropospheric products (~80–370 stations, 1997–2006) and US SuomiNet product (169 stations, 2003–2006). The climate applications of the GPS PW dataset are highlighted in this study. Firstly, the GPS PW dataset is used as a reference to validate radiosonde and atmospheric reanalysis data. Three types of systematic errors in global radiosonde PW data are quantified based on comparisons with the GPS PW data, including measurement biases for each of the fourteen radiosonde types along with their characteristics, long-term temporal inhomogeneity and diurnal sampling errors of once and twice daily radiosonde data. The comparisons between the GPS PW data and three reanalysis products, namely the NCEP-NCAR (NNR), ECMWF 40-year (ERA-40) and Japanese reanalyses (JRA), show that the elevation difference between the reanalysis grid box and the GPS station is the primary cause of the PW difference. Secondly, the PW diurnal variations are documented using the 2-hourly GPS PW dataset. The PW diurnal cycle has an annual-mean, peak-to-peak amplitude of 0.66, 0.53 and 1.11 mm for the globe, Northern Hemisphere, and Southern Hemisphere, respectively, with the time of the peak ranging from noon to late evening depending on the season and region. Preliminary analyses suggest that the PW diurnal cycle in Europe is poorly represented in the NNR and JRA products. Several recommendations are made for future improvements of IGS products for climate applications.     

利用BDS数据反演大气可降水量及其精度分析

随着GAMIT软件版本的不断更新,对BDS数据基线解算已成为可能。本文提出了一种基于GAMIT软件的BDS大气可降水量反演方法,并对利用探空数据计算得到的大气可降水量与GPS数据反演结果进行精度验证。结果表明,通过BDS反演得到的大气可降水量与探空数据计算结果之间的平均相对误差、均方根误差均小于2 mm,相关系数大于0.98;与GPS反演结果之间的平均相对误差、均方根误差均小于3 mm,相关系数大于0.96。BDS反演结果精度较高,基本能够满足气象需要。     

Remote sensing of water vapor content using ground-based GPS data

Spatial and temporal resolution of water vapor content is useful in improving the accuracy of short-term weather prediction. Dense and continuously tracking regional GPS arrays will play an important role in remote sensing atmospheric water vapor content. In this study, a piecewise linear solution method was proposed to estimate the precipitable water vapor (PWV) content from ground-based GPS observations in Hong Kong. To evaluate the solution accuracy of the water vapor content sensed by GPS, the upper air sounding data (radiosonde) that are collected locally was used to calculate the precipitable water vapor during the same period. One-month results of PWV from both ground-based GPS sensing technique and radiosonde method are in agreement within 1–2 mm. This encouraging result will motivate the GPS meteorology application based on the establishment of a dense GPS array in Hong Kong.