GPS水汽在雾霾天气监测中的应用研究

雾霾天气的形成与天气条件密切相关。GPS技术作为一种新的水汽探测手段,能高时效、高时空分辨率、自动实时、全天候地获取空气中的水汽含量。首先统计分析了雾霾的形成原因与变化规律,然后从GPS水汽、雾霾指数与空气相对湿度等方面进行了定性的相关性分析。研究结果表明,GPS水汽与雾霾天气的形成存在一定的相关性,GPS水汽在一定程度上可用于雾霾天气的监测与预报,而且气象部门可依据GPS水汽含量开展人工增雨（雪）来减缓雾霾天气的持续影响,进而为改善空气质量提供科学依据。     

地基GPS水汽层析的投影面算法

水汽层析技术在研究气候变化、极端天气预警、辅助数值天气预报等方面发挥着重要作用。常规的水汽层析技术在计算层析方程系数时,需要进行大量的求交运算。对此,本文提出了一种投影面算法,提高了运算速度和反演的精度。本文采用的试验数据是香港卫星定位参考站网(SatRef)提供的GPS信号数据,与传统算法相比,投影面算法的计算速度更快、计算量更小,不受层析区域大小影响,水汽层析的结果与探空数据具有良好的一致性。     

基于水汽密度比例因子的三维水汽层析算法

针对传统水汽密度层析方法的缺点,设计并实现了一种基于水汽密度比例因子的三维水汽层析算法,提高了观测数据的利用率。利用香港CORS网的实测GPS和气象数据,并结合研究区域内45004探空站的探空数据,验证了该算法用于实测数据的可行性及精度,并分析了不同天气对层析新算法的影响。试验结果表明:该算法在观测数据的利用率上远大于传统层析方法,以探空数据为参考基准,RMS、水汽廓线相关系数和误差分布均优于传统方法。此外,降水天气对层析结果影响要比无降水天气的影响大。     

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.     

利用选权拟合法进行GPS水汽层析解算

附加约束条件的层析解算方法是克服GPS水汽层析观测方程不适定性的主要方法,为了避免该方法中水平约束方程权阵的选取不当对水汽层析结果产生的不良影响,将选权拟合法应用到对流层水汽参数反演中。首先利用水汽参数在空间的分布规律构建参数权矩阵,并利用L曲线法确定正则化参数,然后利用模拟实验对该方法在水汽层析解算中的应用进行了验证。结果表明,该方法可以有效地克服观测方程的不适定性,反演得到符合客观实际的结果。     

Voxel-optimized regional water vapor tomography and comparison with radiosonde and numerical weather model

Water vapor tomography has been developed as a powerful tool to model spatial and temporal distribution of atmospheric water vapor. Global navigation satellite systems (GNSS) water vapor tomography refers to the 3D structural construction of tropospheric water vapor using a large number of GNSS signals that penetrate the tomographic modeling area from different positions. The modeling area is usually discretized into a number of voxels. A major issue involved is that some voxels are not crossed by any GNSS signal rays, resulting in an undetermined solution to the tomographic system. To alleviate this problem, the number of voxels crossed by GNSS signal rays should be as large as possible. An important way to achieve this is to optimize the geographic distribution of tomographic voxels. We propose an approach to optimize voxel distribution in both vertical and horizontal domains. In the vertical domain, water vapor profiles derived from radiosonde data are exploited to identify the maximum height of tomography and the optimal vertical resolution. In the horizontal domain, the optimal horizontal distribution of voxels is obtained by searching the maximum number of ray-crossing voxels in both latitude and longitude directions. The water vapor tomography optimization procedures are implemented using GPS water vapor data from the Hong Kong Satellite Positioning Reference Station Network. The tomographic water vapor fields solved from the optimized tomographic voxels are evaluated using radiosonde data and a numerical weather prediction non-hydrostatic model (NHM) obtained for the Hong Kong station. The comparisons of tomographic integrated water vapor (IWV) with the radiosonde and NHM IWV show that RMS errors of their differences are 1.41 and 3.09 mm, respectively. Moreover, the tomographic water vapor density results are compared with those of radiosonde and NHM. The RMS error of the density differences between tomography and radiosonde data is 1.05  \(\mathrm{g/m}^{3}\) . For the comparison between tomography and NHM, an overall RMS error of \(1.43\,\mathrm{g/m^{3}}\) is achieved.     

顾及双差残差反演GPS信号方向的斜路径水汽含量

给出了顾及GPS双差残差反演斜路径水汽SWV的解算流程;然后详细给出了双差残差到非差残差的转化算法,并对算法进行了改进;最后利用并址的GPS和WVR实测数据对反演SWV算法进行了验证,结果证实改进的反演算法能以优于4 mm精度近实时估算SWV值,与目前国际研究精度在同一量级。     

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。     

顾及边界入射信号的多模水汽层析方法

利用GNSS三维水汽层析技术全天候地获取高时空采样率的水汽垂直分布信息,已成为GNSS气象学中一大研究热点。当前,基于单一导航系统的传统层析方法存在观测数据利用率低、观测分布不均等不足。本文设计和实现了一种顾及边界入射信号的多模水汽层析方法,采用香港CORS网观测数据和无线电探空产品进行精度验证,并详细分析边界入射信号和多模层顶信号的引入对层析水汽结果的改善程度。结果表明:相较于传统GPS层析方法,本文采用的融合两类多模层顶信号和边界入射信号的新水汽层析方法,兼备边界入射信号和多模层顶信号的优点,可得到更高精度和更可靠的三维水汽信息。     

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.     

基于BDS精密星历产品的水汽探测性能分析

研究北斗卫星导航系统（BDS）反演大气可降水量的性能有利于推动BDS在数值天气预报、气象学研究等方面的应用. 基于武汉大学发布的BDS最终精密星历产品(WUM)、快速精密星历产品(WHR)和超快速精密星历产品(WHU),利用MGEX站和单基站连续运行参考站（CORS）提供的全球卫星导航系统（GNSS）多模观测数据,在验证三种BDS精密星历产品解算对流层天顶延迟的精度达到要求后,将基于三种BDS精密星历产品解算的大气可降水量分别与GPS水汽探测结果、ERA-5再分析资料和探空站数据进行对比,分析基于三种精密星历产品的BDS水汽探测性能. 实验结果表明:基于BDS最终精密星历产品的大气水汽探测精度高于快速星历产品和超快速星历产品,三种BDS星历产品反演大气可降水量的相对精度和可靠性与GPS相当,满足中小尺度数值天气预报和气象学研究等要求.      

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.     

垂直不均匀分层的地基GPS层析水汽研究

依据四川省内GPS数据研究垂直分层方法对层析结果的影响及大气水汽随着高程变化的特点,提出一种垂直不均匀分层方法。与垂直均匀分层进行对比实验,不均匀分层的层析结果与探空水汽结果更吻合。由于水汽主要集中在对流层中低层,对流层低层的垂直分辨率相对较高,采用垂直不均匀分层方法得到的大气水汽的变化特征更加细致。考虑到水汽分布的不均匀特点,认为垂直不均匀分层更符合大气水汽的实际分布。四川地区的水汽层析实验研究结果表明文中提出的垂直不均匀分层方法可行且有效。     

基于超快速星历进行实时反演大气水汽总量的可行性研究

从GPS气象学实际应用的角度出发,能够实时获取高时空分辨率的大气水汽场是一个十分关键的问题。基于地基GPS遥感水汽的原理,利用香港地区CORS网的实际测量数据进行试验,根据IGS网站提供的不同精度的轨道信息设计了试验方案,并且比较了方案中最终精密星历、超快速星历以及气象探空站探测得到的大气可降水量序列。实验结果表明,利用超快速星历反演算出的大气水汽总量与最终精密星历一致,其精度可以满足气象预报等实时业务的需求。      

地基GPS网层析水汽三维分布数值积分新方法

针对传统层析方法的缺点,本文结合数值积分参数化方法,设计并实现了一种顾及地球曲率的水平与垂直方向分开插值的地基GPS网层析湿折射率三维分布方法,明显简化了垂直插值的运算,减少了层析实际观测方程中零系数参数的比例。利用美国Dallas地区CORS网实测GPS数据与气象数据,结合位于该区域的FWD探空站探空数据提供的湿折射率垂直轮廓线,验证分析了该方法用于实测数据的可行性及其精度。结果表明：相对于传统层析方法,新方法能够明显提高层析湿折射率垂直轮廓线的精度,与探空结果相比,新方法的RMS、误差分布均优于传统方法,而且垂直内插方法的精度也略高于复杂的三次样条垂直内插方法。     

基于气象要素内插的地基GPS/PWV 方法研究与精度分析

测站气压和温度的准确获取对GPS水汽反演的精度至关重要,但是我国各地在建立GPS连续运行观测站时的发展状态差别较大,有相当部分的GPS气象站网并未配备气压和温度传感器,无法有效准确采集测站气压及温度相关数据,对实时获取测站上方水汽有较大影响.本文基于一种增加高度改正的反距离加权法,和分布在全国的全球卫星导航系统(GNSS)气象站网数据,对该方法进行了实验验证．实验结果表明,通过此方法得到的气压和温度参数精度满足水汽解算需要．同时将本文方法与全球气温和气压经验模型(GPT2)进行对比,证明了本文得到的温压参数精度要优于GPT2模型.      

用GPS观测反演大气中水汽的含量

介绍用GPS测量提取水汽的原理和过程，讨论如何提高其精度和实时性，并提出构造三维水汽分布的方法。通过用GPS观测量反演大气的影响，从而提取大气中水汽的含量，这对气象研究和天气预报有很好的作用。     

利用星载GPS无线电掩星数据分析全球水汽分布

水汽是大气成分中重要的组成部分,了解全球水汽分布规律及其形成机制对于未来全球气候至关重要。并且,GPS无线电掩星技术用于GPS气象学,为研究者提供了高精度、全球性、连续性的数据资料,特别是海洋及无人区的数据。本研究主要利用GPS无线电掩星数据反演全球水汽所对应的绝对湿度值,从而得到较为精确和全面的全球水汽分布情况,为进一步提升气象预报、未来气候分析的准确性及未来的大气研究提供精确的参考数据。     

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。      

基于GPS-PWV的不同云系降水个例的综合分析

利用成都地基GPS观测网的观测数据,结合自动气象站资料计算出GPS遥感的大气可降水量(GPS-PWV)。按照降水性质,选取对流云降水和层状云降水个例,分析不同类型降水过程中GPS-PWV的变化特征。结果表明,对流云降水和层状云降水一般均发生在GPS-PWV的高值阶段。