GPS-PWV estimation and validation with radiosonde data and numerical weather prediction model in Antarctica

Three permanent GPS tracking stations in the trans Antarctic mountain deformation (TAMDEF) network were used to estimate precipitable water vapor (PWV) using measurement series covering the period of 2002–2005. TAMDEF is a National Science Foundation funded joint project between The Ohio State University and the United States Geological Survey. The TAMDEF sites with the longest GPS data spans considered in this research are Franklin Island East (FIE0), the International GNSS Service site McMurdo (MCM4), and Cape Roberts (ROB1). For the experiment, PWV was extracted from the ionosphere-free double-difference carrier phase observations, processed using the adjustment of GPS ephemerides (PAGES) software. The GPS data were processed with a 30 s sampling rate, 15-degree cutoff angle, and precise GPS orbits disseminated by IGS. The time-varying part of the zenith wet delay is estimated using the Marini mapping function, while the constant part is evaluated using the corresponding Marini tropospheric model. Previous studies using TAMDEF data for PWV estimation show that the Marini mapping function performs the best among the models offered by PAGES. The data reduction to compute the zenith wet delay follows the step piecewise linear strategy, which is subsequently transformed to PWV. The resulting GPS-based PWV is compared to the radiosonde observations and to values obtained from the Antarctic mesoscale prediction system (AMPS). This comparison revealed a consistent bias of 1.7 mm between the GPS solution and the radiosonde and AMPS reference values.     

Using a regional numerical weather prediction model for GNSS positioning over Brazil

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.     

Real-time precise point positioning augmented with high-resolution numerical weather prediction model

GPS Solutions - The tropospheric delay is one of the major error sources in precise point positioning (PPP), affecting the accuracy and precision of estimated coordinates and convergence time,...     

Study of cloud liquid water path and total precipitable water from irs-p4/msmr and numerical weather prediction model output

A global weather analysis-forecast system is used to produce six hourly analysis of meteorological fields at roughly 150 km × 150 km resolution at the National Center for Medium Range Weather Forecast (NCMRWF). In this paper, we have studied the Total Precipitable Water Content (TPWC) and Cloud Liquid Water Path (CLWP) derived from the Indian Remote Sensing (IRS-P4) Satellite over the Indian Ocean region in relation to operational numerical weather prediction (NWP) model analysis and short-range forecasts. An objective analysis was carried out by introducing the observations of CLWP, TPWC and their values (six hour forecasts) from the T80 model as the first guess, for a 20 days period of August 1999 using the standard Cressman’s technique. The reanalysis could capture the signature of TPWC and CLWP data from IRS-P4 satellite. In general the observed values of TPWC and CLWP from IRS-P4 have a positive bias compared to NCMRWF analysis over the region where the satellite passed. The CLWP values have been compared with Special Sensor Microwave/Imager (SSM/I) products from the Defense Meteorological Satellite Program (DMSP) satellites. Results indicate that the model derived CLWP values were within acceptable limits, whereas the observations from the Multi-channel Scanning Microwave Radiometer (MSMR) showed slightly larger values.     

Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns

Continuous, very long baseline interferometry (VLBI) campaigns over 2 weeks have been carried out repeatedly, i.e., CONT02 in October 2002, CONT05 in September 2005, CONT08 in August 2008, and CONT11 in September 2011, to demonstrate the highest accuracy the current VLBI was capable at that time. In this study, we have compared zenith total delays (ZTD) and troposphere gradients as consistently estimated from the observations of VLBI, Global Navigation Satellite Systems (GNSS), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) at VLBI sites participating in the CONT campaigns. We analyzed the CONT campaigns using the state-of-the-art software following common processing strategies as closely as possible. In parallel, ZTD and gradients were derived from numerical weather models, i.e., from the global European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields, the High Resolution Limited Area Model (European sites), the Japan Meteorological Agency-Operational Meso-Analysis Field (MANAL, over Japan), and the Cloud Resolving Storm Simulator (Tsukuba, Japan). Finally, zenith wet delays were estimated from the observations of water vapor radiometers (WVR) at sites where the WVR observables are available during the CONT sessions. The best ZTD agreement, interpreted as the smallest standard deviation, was found between GNSS and VLBI techniques to be about 5–6 mm at most of the co-located sites and CONT campaigns. We did not detect any significant improvement in the ZTD agreement between various techniques over time, except for DORIS and MANAL. On the other hand, the agreement and thus the accuracy of the troposphere parameters mainly depend on the amount of humidity in the atmosphere.     

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。     

基于无线电探空的武汉大气加权平均温度模型研究

以武汉地区为例,本文推导无线电探空推导的大气加权平均温度模型并对其可靠性进行检验。采用武汉无线电探空数据推算武汉地区的大气加权平均温度计算模型,以此模型计算GPS可降水量,通过与无线电探空结果比较来检验该模型的精确度。在WHDH站GPS可降水量与无线电探空的比较中,两者差值的均方根为3.0mm,两者的相关性达到了0.952。利用中国地壳运动监测网络2002年武汉站GPS数据和武汉地区大气加权平均温度模型推算的可降水量与无线电探空比较,GPS可降水量与无线电探空可降水量在数值上和发展趋势上比较接近,说明了无线电探空的大气加权平均温度模型的可靠性。     

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。     

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.     

GNSS水汽层析的自适应非均匀指数分层方法

GNSS水汽层析技术在中小尺度灾害性天气的监测和预警中发挥着重要作用。常见的GNSS水汽层析技术在垂直分层时采用均匀分层,不符合大气水汽在垂直方向上的实际分布情况。本文以大气水汽密度为依据,提出一种自适应非均匀指数分层方法。该方法大大降低了各层之间的水汽密度差异,提高了水汽层析模型分层精度,且能够实现对任意给定层析区域的自适应分层建模。利用2019年8月香港CORS实测数据和探空数据对该方法进行试验与分析,与传统均匀分层相比,自适应非均匀指数分层的均方根误差和平均绝对误差分别降低了0.401 g/m³和0.223 g/m³,在低海拔处和恶劣天气下层析结果的精度和质量显著提高。     

GNSS/MODIS信号紧耦合水汽层析算法

GNSS水汽层析技术凭借高精度、高时空分辨率及全天候监测等优点,已成为探测大气水汽最具潜力的技术之一.目前,融合多源大气遥感数据逐步成为弥补传统层析模型GNSS信号几何缺陷的研究热点.本文利用Terra卫星上的中分辨率成像光谱仪(moderate resolution maging spectrorad ometer,...     

顾及边界信号及垂直约束的GNSS水汽层析方法

利用GNSS三维水汽层析技术获取大气水汽分布信息,具有全天候、高时空分辨率、高精度和经济实用的优势.但目前只考虑层顶信号的层析模型,存在观测数据利用率低、网格空格率大的问题,此外采用的垂直约束方程与实际水汽分布符合程度也较低.本文基于探空信息拟合的函数建立垂直约束,设计并实现了一种顾及边界信号的层析方法,利用香港CORS网数据和无线电探空产品进行精度验证,详细分析了边界信号对层析结果的改善程度,同时分析了垂直约束方程对层析结果的影响.研究结果表明:边界信号的加入使得观测量提高了51.9％,网格空格率大幅降低,解算结果的平均均方根误差降低了12.1％;相对于基于垂直方向上水汽分布呈指数递减特性建立的传统约束方程,本文采用的垂直约束解算结果的平均均方根误差降低了5.7％.     

太阳光度计反演大气水汽总量的方法与结果对比分析

详述了使用太阳光度计反演大气水汽柱总量的反演方法—单通道法和双通道法,其中双通道法又可采用不同 的非水汽通道来实现。考虑到气溶胶光学厚度及瑞利散射的影响,分析了不同方法反演所得水汽总量相对探空数据的 误差。结果表明,这些方法的反演结果非常接近。在实际应用中,可使用任一种方法来反演水汽。     

Improving BeiDou real-time precise point positioning with numerical weather models

Precise positioning with the current Chinese BeiDou Navigation Satellite System is proven to be of comparable accuracy to the Global Positioning System, which is at centimeter level for the horizontal components and sub-decimeter level for the vertical component. But the BeiDou precise point positioning (PPP) shows its limitation in requiring a relatively long convergence time. In this study, we develop a numerical weather model (NWM) augmented PPP processing algorithm to improve BeiDou precise positioning. Tropospheric delay parameters, i.e., zenith delays, mapping functions, and horizontal delay gradients, derived from short-range forecasts from the Global Forecast System of the National Centers for Environmental Prediction (NCEP) are applied into BeiDou real-time PPP. Observational data from stations that are capable of tracking the BeiDou constellation from the International GNSS Service (IGS) Multi-GNSS Experiments network are processed, with the introduced NWM-augmented PPP and the standard PPP processing. The accuracy of tropospheric delays derived from NCEP is assessed against with the IGS final tropospheric delay products. The positioning results show that an improvement in convergence time up to 60.0 and 66.7% for the east and vertical components, respectively, can be achieved with the NWM-augmented PPP solution compared to the standard PPP solutions, while only slight improvement in the solution convergence can be found for the north component. A positioning accuracy of 5.7 and 5.9 cm for the east component is achieved with the standard PPP that estimates gradients and the one that estimates no gradients, respectively, in comparison to 3.5 cm of the NWM-augmented PPP, showing an improvement of 38.6 and 40.1%. Compared to the accuracy of 3.7 and 4.1 cm for the north component derived from the two standard PPP solutions, the one of the NWM-augmented PPP solution is improved to 2.0 cm, by about 45.9 and 51.2%. The positioning accuracy for the up component improves from 11.4 and 13.2 cm with the two standard PPP solutions to 8.0 cm with the NWM-augmented PPP solution, an improvement of 29.8 and 39.4%, respectively.     

GPS遥感大气综合水汽含量局部区域模型与通用模型结果的比较分析

为进一步提高利用GPS遥感大气综合水汽含量的精度,部分学者提出了利用当地探空气象资料建立局部区域模型,以改善采用通用模型计算综合水汽含量结果的观点。为此本文就局部区域模型和通用模型反演的水汽结果进行了比较分析,得出了一些重要的结论。     

大气可降水量预测模型的自适应Kalmam滤波改进

针对现有可降水量预报模型存在预报精度不高等问题,该文提出采用方差分量估计自适应卡尔曼滤波对可降水量数据进行预处理,用以提高径向基神经网络预测模型的预测精度,从而形成高精度预报模型。通过比较不同基站不同时间的数据,分析使用方法的预报精度。实验结果表明:将预测模型应用于全国7个测站进行实验,预测相对精度的平均值可达95%以上,预报残差在10-5左右,残差值小于0.001的占90%以上。在影响因素方面,使用较短时间作为模型原始数据进行预测会得到较好的预测结果。实验证明本预测方法在预报大气可降水量值方面具有较高的精度。     

天顶静力延迟模型对GPS可降水量反演的影响分析及改进

利用地基GPS遥感大气可降水量(PWV,precipitable water vapor)过程中,天顶静力延迟(ZHD,zenith hydrostatic delay)模型精度直接影响PWV反演精度。文中将常用天顶静力延迟模型(Black模型、Hopfield模型和Saastamoinen模型)计算所得ZHD与基于湖南省2016-04-01—2017-03-31高空气象探测秒级数据计算所得探空ZHD进行对比,发现模型存在较明显系统偏差,其中Black模型ZHD平均偏低40mm以上。利用探空实测ZHD对天顶静力延迟模型进行回归建模,订正模型系数后可明显减小模型系统偏差和均方误差。改进后的ZHD模型可明显减小GPSPWV反演的系统偏差,并略微降低均方误差,其中采用改进后SA模型反演所得GPSPWV与探空PWV相比,平均偏低不超过0.230 7mm,反演准确性有较显著改善。     

利用CORS站研究多因子分季节可降水量转换模型

针对GNSS气象学中可降水量转换过程较为复杂的问题,利用2017年江苏CORS站及其并址探空数据,分析大气可降水量(PWV)与天顶对流层延迟(ZTD)、温度和气压之间的相关性,采用线性回归拟合法建立多因子分季节PWV模型,并用2017-2018年数据验证模型精度.结果表明PWV与ZTD有很强的线性相关性,相关系数为0.980 3,PWV与温度和气压有较强的相关性,相关系数分别为0.611 2和-0.613 6;全年PWV模型中,单、双、多因子模型的RMS分别为2.88、1.70和0.49 mm,精度依次提高;多因子PWV模型中,分季节PWV模型较全年PWV模型的RMS分别提高0.23、0.20、0.18和0.37 mm,精度明显优于全年模型.因此,多因子分季节PWV模型预测精度优于1 mm,满足GNSS监测水汽的气象应用精度要求.     

Assessment of time-series of troposphere zenith delays derived from the Global Data Assimilation System numerical weather model

Troposphere zenith path delays derived from the Global Data Assimilation System (GDAS) numerical weather model (NWM) are compared with those of the International GNSS Service (IGS) solutions over a 1.5-year period at 18 globally distributed IGS stations. Meteorological parameters can be interpolated from the NWM model at any location and at any time after December 2004. The meteorological parameters extracted from the NWM model agree with in situ direct measurements at some IGS stations within 1 mbar for pressure, 3° for temperature and 13% for relative humidity. The hydrostatic and wet components of the zenith path delay (ZPD) are computed using the meteorological parameters extracted from the NWM model. The total ZPDs derived from the GDAS NWM agree with the IGS ZPD solutions at 3.0 cm RMS level with biases of up to 4.5 cm, which can be attributed to the wet ZPDs estimates from the NWM model, considering the less accurate interpolated relative humidity parameter. Based on this study, it is suggested that the availability and the precision of the GDAS NWM ZPD should be sufficient for nearly all GPS navigation solutions.

基于GPS的MODIS近红外可降水量季节性模型建立

在考虑可降水量季节性变化的基础上,提出利用GPS数据建立MODIS近红外可降水量季节性模型。首先对比分析2014年北京房山(BJFS)站的GPS可降水量和相应时间的MODIS近红外可降水量数据,发现两者之间的变化趋势基本一致,存在显著线性相关性;然后以GPS可降水量为标准值,利用回归分析建立GPS和MODIS可降水量之间的季节和全年校正模型。经检验,GPS可降水量与四个季节模型校正的MODIS近红外可降水量的均方根误差均小于3mm,最大误差不超过6mm,季节校正模型的精度都要高于全年校正模型。