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 tomograph

GNSS troposphere tomography based on two-step reconstructions using GPS observations and COSMIC profiles

Traditionally, balloon-based radiosonde soundings are used to study the spatial distribution of atmospheric water vapour. However, this approach cannot be frequently employed due to its high cost. In contrast, GPS tomography technique can obtain water vapour in a high temporal resolution. In the tomography technique, an iterative or non-iterative reconstruction algorithm is usually utilised to overcome rank deficiency of observation equations for water vapour inversion. However, the single iterative or non-iterative reconstruction algorithm has their limitations. For instance, the iterative reconstruction algorithm requires accurate initial values of water vapour while the non-iterative reconstruction algorithm needs proper constraint conditions. To overcome these drawbacks, we present a combined iterative and non-iterative reconstruction approach for the three-dimensional (3-D) water vapour inversion using GPS observations and COSMIC profiles. In this approach, the non-iterative reconstruction algorithm is first used to estimate water vapour density based on a priori water vapour information derived from COSMIC radio occultation data. The estimates are then employed as initial values in the iterative reconstruction algorithm. The largest advantage of this approach is that precise initial values of water vapour density that are essential in the iterative reconstruction algorithm can be obtained. This combined reconstruction algorithm (CRA) is evaluated using 10-day GPS observations in Hong Kong and COSMIC profiles. The test results indicate that the water vapor accuracy from CRA is 16 and 14% higher than that of iterative and non-iterative reconstruction approaches, respectively. In addition, the tomography results obtained from the CRA are further validated using radiosonde data. Results indicate that water vapour densities derived from the CRA agree with radiosonde results very well at altitudes above 2.5 km. The average RMS value of their differences above 2.5 km is 0.44 g m⁻³

COMPARISON BETWEEN TWO SENSORS AND MULTIPLE SENSORS WITH TOA AND TDOA/FDOA FUSIONS AND NON-FUSIONS UNDER NOISE JITTER MITIGATION

The prominence of geolocation technology and its demand has risen in recent years. Stringent and precise positioning is at the forefront of both civilian and military applications. The importance of precision leads to a rise in processing and algorithm run times. In addition, space, time and atmospheric conditions contribute to the complexity of geolocation operations. Past research measured time-of-arrival, time-difference-of-arrival, and frequency-difference-of arrival under stringent conditions using a synthetic aperture approach of two airborne sensors. While four sensors have been proven to be ideal in the geolocation of an emitter, we aim to decrease the requirement to three sensors and retain the purity of the original two sensor algorithm. Three-sensor fusion from multiple time-samples enhances the precision of the estimate and provides the end-user a better positioning solution. We propose the utilization of three airborne sensors collecting measurements from the synthetic aperture model. Sensor angular separation and aperture size are addressed. A thorough investigation into ionosphere mitigation is provided. Finally, an overall summary and comparison between two- and three-sensor approaches are documented.Lieutenant, United States NavyApproved for public release; distribution is unlimited

Applications in GNSS water vapor tomography

Algebraic reconstruction algorithms are iterative algorithms that are used in many area including medicine, seismology or meteorology. These algorithms are known to be highly computational intensive. This may be especially troublesome for real-time applications or when processed by conventional low-cost personnel computers. One of these real time applications is the reconstruction of water vapor images from Global Navigation Satellite System (GNSS) observations. The parallelization of algebraic reconstruction algorithms has the potential to diminish signi cantly the required resources permitting to obtain valid solutions in time to be used for nowcasting and forecasting weather models. The main objective of this dissertation was to present and analyse diverse shared memory libraries and techniques in CPU and GPU for algebraic reconstruction algorithms. It was concluded that the parallelization compensates over sequential implementations. Overall the GPU implementations were found to be only slightly faster than the CPU implementations, depending on the size of the problem being studied. A secondary objective was to develop a software to perform the GNSS water vapor reconstruction using the implemented parallel algorithms. This software has been developed with success and diverse tests were made namely with synthetic and real data, the preliminary results shown to be satisfactory. This dissertation was written in the Space & Earth Geodetic Analysis Laboratory (SEGAL) and was carried out in the framework of the Structure of Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC/CTE-ATM/119922/2010) project funded by FCT.Algoritmos de reconstrução algébrica são algoritmos iterativos que são usados em muitas áreas incluindo medicina, sismologia ou meteorologia. Estes algoritmos são conhecidos por serem bastante exigentes computacionalmente. Isto pode ser especialmente complicado para aplicações de tempo real ou quando processados por computadores pessoais de baixo custo. Uma destas aplicações de tempo real é a reconstrução de imagens de vapor de água a partir de observações de sistemas globais de navegação por satélite. A paralelização dos algoritmos de reconstrução algébrica permite que se reduza significativamente os requisitos computacionais permitindo obter soluções válidas para previsão meteorológica num curto espaço de tempo. O principal objectivo desta dissertação é apresentar e analisar diversas bibliotecas e técnicas multithreading para a reconstrução algébrica em CPU e GPU. Foi concluído que a paralelização compensa sobre a implementações sequenciais. De um modo geral as implementações GPU obtiveram resultados relativamente melhores que implementações em CPU, isto dependendo do tamanho do problema a ser estudado. Um objectivo secundário era desenvolver uma aplicação que realizasse a reconstrução de imagem de vapor de água através de sistemas globais de navegação por satélite de uma forma paralela. Este software tem sido desenvolvido com sucesso e diversos testes foram realizados com dados sintéticos e dados reais, os resultados preliminares foram satisfatórios. Esta dissertação foi escrita no Space & Earth Geodetic Analysis Laboratory (SEGAL) e foi realizada de acordo com o projecto Structure 01' Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC / CTE-ATM/ 11992212010) financiado pelo FCT.Fundação para a Ciência e a Tecnologia (FCT

Validation of GPS atmospheric water vapor with WVR data in satellite tracking mode

Slant-integrated water vapor (SIWV) data derived from GPS STDs (slant total delays), which provide the spatial information on tropospheric water vapor, have a high potential for assimilation to weather models or for nowcasting or reconstruction of the 3-D humidity field with tomographic techniques. Therefore, the accuracy of GPS STD is important, and independent observations are needed to estimate the quality of GPS STD. In 2012 the GFZ (German Research Centre for Geosciences) started to operate a microwave radiometer in the vicinity of the Potsdam GPS station. The water vapor content along the line of sight between a ground station and a GPS satellite can be derived from GPS data and directly measured by a water vapor radiometer (WVR) at the same time. In this study we present the validation results of SIWV observed by a ground-based GPS receiver and a WVR. The validation covers 184 days of data with dry and wet humidity conditions. SIWV data from GPS and WVR generally show good agreement with a mean bias of −0.4 kg m−2 and an rms (root mean square) of 3.15 kg m−2. The differences in SIWV show an elevation dependent on an rms of 7.13 kg m−2 below 15° but of 1.76 kg m−2 above 15°. Nevertheless, this elevation dependence is not observed regarding relative deviations. The relation between the differences and possible influencing factors (elevation angles, pressure, temperature and relative humidity) are analyzed in this study. Besides the elevation, dependencies between the atmospheric humidity conditions, temperature and the differences in SIWV are found

Seasonal heavy precipitation sensitivity to moisture corrections in the western Mediterranean across resolutions

The controlling role of atmospheric water vapour for heavy precipitation leading to extreme events has been widely demonstrated, along with the existing gap of adequate moisture observations and the frequent biases present in model simulations concerning this fundamental variable. In this study, we profit from a state-of-the-art dense network of GPS measurements over Europe retrieving a homogenized GPS-derived Zenith Total Delay (GPS-ZTD) data set up to 10 min of temporal resolution, to assess the seasonal sensitivity of convection-related processes and heavy precipitation modelling to atmospheric humidity corrections. For this purpose, we perform nudging experiments with the COSMO-CLM model at two spatial resolutions, 7 km (parameterized convection) and 2.8 km (explicitly resolved convection) covering the autumn period of 2012, when the Special Observation Period (SOP) 1 of the Hydrological Cycle in the Mediterranean Experiment (HyMeX) program took place in the Western Mediterranean, which is our area of interest. The benefits and disadvantages of GPS-ZTD nudging and resulting moisture corrections are disentangled. The impact on high-resolution parameterized versus convection-permitting simulations is compared. A process-understanding methodology and a local-to-regional approach are used. Our results show a beneficial impact on the seasonal scale at both model grid spacings improving the representation of the chain of processes leading to heavy precipitation, contrary to the non-systematic improvement at the event and sub-event scales. The correction of atmospheric moisture entails a reduction of about 10% in the total column water vapour and corrections on single locations up to 10 mm counteracting the model wet bias across scales. The location, structure, and amount of total precipitation are positively affected. Particularly, the combination of high-resolution atmospheric humidity observations and fine convection-permitting simulations shows great potential for correction of the precipitation daily cycle, key for accurate precipitation modelling. The difference in the density of local and upstream observational networks and the lack of information on the vertical stratification of moisture are identified weaknesses, which could be determinants in obtaining more accurate corrections on seasonal to sub-seasonal scales after assimilation strategies

A GPS network for tropospheric tomography in the framework of the Mediterranean hydrometeorological observatory Cévennes-Vivarais (south-eastern France)

International audienceThe Mediterranean hydrometeorological observatory Cévennes-Vivarais (OHM-CV) coordinates hydrometeorological observations (radars, rain gauges, water level stations) on a regional scale in southeastern France. In the framework of OHM-CV, temporary GPS measurements have been carried out for 2 months in autumn 2002, when the heaviest rainfall are expected. These measurements increase the spatial density of the existing permanent GPS network, by adding three more receivers between the Mediterranean coast and the Cévennes-Vivarais range to monitor maritime source of water vapour flow feeding the precipitating systems over the Cévennes-Vivarais region. In addition, a local network of 18 receivers covered an area of 30 by 30 km within the field of view of the meteorological radar. These regional and local networks of permanent and temporary stations are used to monitor the precipitable water vapour (PWV) with high temporal resolution (15 min). Also, the dense local network provided data which have been inverted using tomographic techniques to obtain the 3-D field of tropospheric water vapour content. This study presents methodological tests for retrieving GPS tropospheric observations from dense networks, with the aim of assessing the uncertainties of GPS retrievals. Using optimal tropospheric GPS retrieval methods, high resolution measurements of PWV on a local scale (a few kilometres) are discussed for rain events. Finally, the results of 3-D fields of water vapour densities from GPS tomography are analysed with respect to precipitation fields derived from a meteorological radar, showing a good correlation between precipitation and water vapour depletion areas