Galina Dick

Real‐time GPS sensing of atmospheric water vapor: Precise point positioning with orbit, clock, and phase delay corrections

The recent development of the International Global Navigation Satellite Systems Service Real-Time Pilot Project and the enormous progress in precise point positioning (PPP) techniques provide a promising opportunity for real-time determination of Integrated Water Vapor (IWV) using GPS ground networks for various geodetic and meteorological applications. In this study, we develop a new real-time GPS water vapor processing system based on the PPP ambiguity fixing technique with real-time satellite orbit, clock, and phase delay corrections. We demonstrate the performance of the new real-time water vapor estimates using the currently operationally used near-real-time GPS atmospheric data and collocated microwave radiometer measurements as an independent reference. The results show that an accuracy of 1.0 ~ 2.0 mm is achievable for the new real-time GPS based IWV value. Data of such accuracy might be highly valuable for time-critical geodetic (positioning) and meteorological applications.

First experience with near real-time water vapor estimation in a German GPS network

Abstract The GeoForschungsZentrum (GFZ) has started together with three other research centers of the German Helmholtz Association the “GPS Atmosphere Sounding” Project (GASP) on using ground-based (Subproject 1) and space-based (Subproject 2) GPS observations for applications in the numerical weather predictions, climate research and space weather monitoring, which this paper focusses on. The Subproject 1 comprises all necessary components – data links and handling, path delay estimation, conversion to water vapor. The GPS and meteorological data are transmitted in hourly batches to the GFZ since December 1998 and processed with GFZ EPOS software. First experiences with near real-time analysis have been obtained and the operational precision determination of water vapor within local GPS networks has been demonstrated with an accuracy of better than 2 mm with a standard deviation at the level of better than ±1 mm . Densification of the test network is progressing from 10 to 100 sites, requiring new analysis strategies.

Retrieving of atmospheric parameters from multi‐GNSS in real time: Validation with water vapor radiometer and numerical weather model

The multiconstellation Global Navigation Satellite Systems (GNSS) (e.g., GPS, GLObal NAvigation Satellite System (GLONASS), Galileo, and BeiDou) offers great opportunities for real-time retrieval of atmospheric parameters for supporting numerical weather prediction nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined to retrieve atmospheric parameters based on the real-time precise point positioning technique. The atmospheric parameters, retrieved from multi-GNSS observations of a 180 day period from about 100 globally distributed stations, including zenith total delay, integrated water vapor, horizontal gradient, and slant total delay (STD), are analyzed and evaluated. The water vapor radiometer data and a numerical weather model, the operational analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF), are used to independently validate the performance of individual GNSS and also demonstrate the benefits of multiconstellation GNSS for real-time atmospheric monitoring. Our results show that the GLONASS and BeiDou have the potential capability for real-time atmospheric parameter retrieval for time-critical meteorological applications as GPS does, and the combination of multi-GNSS observations can improve the performance of a single-system solution in meteorological applications with higher accuracy and robustness. The multi-GNSS processing greatly increases the number of STDs. The mean and standard deviation of STDs between each GNSS and ECMWF exhibit a good stability as function of the elevation angle, the azimuth angle, and time, in general. An obvious latitude dependence is confirmed by a map of station specific mean and standard deviations. Such real-time atmospheric products, provided by multi-GNSS processing with higher accuracy, stronger reliability, and better distribution, might be highly valuable for atmospheric sounding systems, especially for nowcasting of extreme weather.

The rapid and precise computation of GPS slant total delays and mapping factors utilizing a numerical weather model

In a previous study we developed an elegant technique to compute the signal travel time delay due to the neutral atmosphere, also known as slant total delay (STD), between a Global Positioning System (GPS) satellite and a ground-based receiver utilizing data from a numerical weather model (NWM). Currently, we make use of NWM data from the Global Forecast System (GFS) because short-range forecasts are easily accessible. In this study we introduce some modifications which double the speed of our algorithm without altering its precision; on an ordinary PC (using a single core) we compute about 2000 STDs per second with a precision of about 1 mm. The data throughput and precision are independent of the vacuum elevation (azimuth) angle of the receiver satellite link. Hence, the algorithm allows the computation of STDs in a mesobeta-scale NWM with an unprecedented speed and precision. A practical by-product of the algorithm is introduced as well; the Potsdam Mapping Factors (PMFs), which are generated by fast direct mapping utilizing short-range GFS forecasts. In fact, it appears that the PMFs make the application of parameterized mapping in GPS processing obsolete.

Multi-GNSS Meteorology: Real-Time Retrieving of Atmospheric Water Vapor From BeiDou, Galileo, GLONASS, and GPS Observations

The rapid development of multi-Global Navigation Satellite Systems (GNSSs, e.g., BeiDou, Galileo, GLONASS, and GPS) and the International GNSS Service (IGS) Multi-GNSS Experiment (MGEX) brings great opportunities and challenges for real-time determination of tropospheric zenith total delays (ZTDs) and integrated water vapor (IWV) to improve numerical weather prediction, particularly for nowcasting or severe weather event monitoring. In this paper, we develop a multi-GNSS model to fully exploit the potential of observations from all currently available GNSSs for enhancing real-time ZTD/IWV processing. A prototype multi-GNSS real-time ZTD/IWV monitoring system is also designed and realized at the Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences (GFZ) based on the precise point positioning technique. The ZTD and IWV derived from multi-GNSS stations are carefully analyzed and compared with those from collocated Very Long Baseline Interferometry and radiosonde stations. The performance of individual GNSS is assessed, and the significant benefit of multi-GNSS for real-time water vapor retrieval is also evaluated. The statistical results show that accuracy of several millimeters with high reliability is achievable for the multi-GNSS-based real-time ZTD estimates, which corresponds to about 1- to 1.5-mm accuracy for the IWV. The ZTD/IWV with improved accuracy and reliability would be beneficial for atmospheric sounding systems, particularly for time-critical geodetic and meteorological applications.

Validation of GPS slant delays using water vapour radiometers and weather models

Slant delay data obtained from global positioning system (GPS) observations carry valuable meteorological information. The spatial distribution of the water vapour can be reconstructed from such slant delays. To estimate the quality of the GPS slant delays two validation studies were carried out. One study was based on the observations of a water vapour radiometer, a second on the analysis fields of a numerical weather model which were used to compute the corresponding GPS delays. Both studies yielded a high correlation between the available slant delays at higher elevation angles but showed deficiencies at low elevations. The mean bias between the GPS zenith delays and the radiometer data is 1.18 mm with a RMS of 6.0 mm. The corresponding bias and RMS of the GPS vs. model comparison are 3.3 mm and 2.9 mm.

Estimates of the information provided by GPS slant data observed in Germany regarding tomographic applications

[1] The observation of GPS slant delays from ground GPS networks can be used to reconstruct spatially resolved humidity fields in the troposphere by means of tomographic techniques. Tomography is always related to the solution of inverse problems which are very sensitive to the quality of the input data. Prior to a tomographic reconstruction, it is therefore necessary to quantify the information provided by a given set of GPS slant delay data. This work describes the properties and the information content of more than two million GPS slant delays taken in March 2006 by a continuously operating German GPS network. The temporal and spatial distribution of the slant paths in the atmosphere and their angular distribution in the local system of the GPS station is given. These distributions depend on the satellite orbits and show some characteristic pattern. The available information is estimated by investigating the distribution of intersection points between the slant paths. From these data it is possible to identify regions that are well covered by GPS slant paths and to evaluate the applicability of the existing German GPS stations for continuous atmosphere sounding.

KITcube - a mobile observation platform for convection studies deployed during HyMeX

With the increase of spatial resolution of weather forecast models to order O(1 km), the need for adequate observations for model validation becomes evident. Therefore, we designed and constructed the ‘‘KITcube’’, a mobile observation platform for convection studies of processes on the meso-c scale. The KITcube consists of in-situ and remote sensing systems which allow measuring the energy balance components of the Earth’s surface at different sites; the mean atmospheric conditions by radiosondes, GPS station, and a microwave radiometer; the turbulent characteristics by a sodar and wind lidars; and cloud and precipitation properties by use of a cloud radar, a micro rain radar, disdrometers, rain gauges, and an X-band rain radar. The KITcube was deployed fully for the first time on the French island of Corsica during the HyMeX (Hydrological cycle in the Mediterranean eXperiment) field campaign in 2012. In this article, the components of KITcube and its implementation on the island are described. Moreover, results from one of the HyMeX intensive observation periods are presented to show the capabilities of KITcube.

Retrieving high‐resolution tropospheric gradients from multiconstellation GNSS observations

The developing multi-Global Navigation Satellite Systems (GNSS) constellations have the potential to provide accurate high-resolution tropospheric gradients. Such data, closely linked to strong humidity gradients accompanying severe weather phenomena, are considered a new important data source for meteorological studies, e.g., nowcasting of severe rainfall events. Here we describe the development of a multi-GNSS processing system for the precise retrieval of high-resolution tropospheric gradients. The retrieved products were validated by using independent water vapor radiometer (WVR) observations and numerical weather model (NWM) data. The multi-GNSS high-resolution gradients agree well with those, derived from NWM and WVR, especially for the fast-changing peaks which were mostly associated with synoptic fronts. Compared to GPS-only gradients, the correlations with the validation data are significantly improved up to 20–35%. The new data product has significant potential to improve numerical weather prediction and to advance meteorological studies.

Systematic errors of mapping functions which are based on the VMF1 concept

Abstract Precise global navigation satellite system (GNSS) positioning requires an accurate mapping function (MF) to model the tropospheric delay. To date, the most accurate MF is the Vienna mapping function 1 (VMF1). It utilizes data from a numerical weather model and therefore captures the short-term variability of the atmosphere. Still, the VMF1, or any other MF that is based on the VMF1 concept, is a parameterized mapping approach, and this means that it is tuned for specific elevation angles, station heights, and orbital altitudes. In this study, we analyze the systematic errors caused by such tuning on a global scale. We find that, in particular, the parameterization of the station height dependency is a major concern regarding the application in complex terrain or airborne applications. At this time, we do not provide an improved parameterized mapping approach to mitigate the systematic errors but instead we propose a (ultra-) rapid direct mapping approach, the so-called Potsdam mapping factors (PMFs). Since for any station–satellite link the ratio of the tropospheric delay in the slant and zenith direction is computed directly, the PMFs effectively eliminate the systematic errors.