GNSS-based water vapor estimation and validation during the MOSAiC expedition

Within the transpolar drifting expedition MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), the Global Navigation Satellite System (GNSS) was used among other techniques to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked GNSS data including GPS, GLONASS and Galileo, epoch-wise coordinates and hourly zenith total delays (ZTDs) were determined using a kinematic precise point positioning (PPP) approach. The derived ZTD values agree to 1.1 ± 0.2 mm (root mean square (rms) of the differences 10.2 mm) with the numerical weather data of ECMWF's latest reanalysis, ERA5, computed for the derived ship's locations. This level of agreement is also confirmed by comparing the on-board estimates with ZTDs derived for terrestrial GNSS stations in Bremerhaven and Ny-Ålesund and for the radio telescopes observing very long baseline interferometry in Ny-Ålesund. Preliminary estimates of integrated water vapor derived from frequently launched radiosondes are used to assess the GNSS-derived integrated water vapor estimates. The overall difference of 0.08 ± 0.04 kg m−2 (rms of the differences 1.47 kg m−2) demonstrates a good agreement between GNSS and radiosonde data. Finally, the water vapor variations associated with two warm-air intrusion events in April 2020 are assessed

Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data

Tropospheric delay comprises one of the most important error sources in satellite navigation and is caused when radio signals broadcasted by GPS satellites propagate into the atmosphere. It is usually projected onto zenith direction by using mapping functions named as Zenith Tropospheric Delay (ZTD). ZTD is described as the sum of the Zenith Hydrostatic Delay (ZHD) and the Zenith Wet Delay (ZWD) and with the aid of surface pressure and temperature the integrated water vapor can be estimated. The main objective of this study is to evaluate the tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS (ECMWF stands for the European Centre for Medium-Range Weather Forecasts) reanalysis model and ground meteorological data from two stations of the permanent network of Cyprus and Greece. The period from 27 May to 3 June 2018 is characterized by two different synoptic conditions: high pressure with fair weather in central Mediterranean (Greece), on the one hand, and high instability over the upper levels of the atmosphere that resulted in thunderstorms inland and mountainous areas during midday over the Eastern Mediterranean (Cyprus), on the other hand. In general, the results show that both the empirical blind model GPT2w and the ECMWF (IFS) operational model perform well in particular over Nicosia when used for the retrieval of Integrated Water Vapor (IWV) from GNSS measurements, although appreciable deviations were observed between ECMWF (IFS)-retrieved IWV and the one retrieved from GNSS observations by using meteorological measurements. A sharp increase of IWV prior to the abrupt rainfall events during noon on 30 and 31 May over Nicosia was also found.</p

Estimating trends in atmospheric water vapor and temperature time series over Germany

Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: (1) estimated from ground-based GNSS observations using the method of precise point positioning, (2) inferred from ERA-Interim reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil–Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between −1.5 and 2.3 mm decade−1 with standard deviations below 0.25 mm decade−1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33 ± 0.06 mm decade−1 with standard errors below 0.03 mm decade−1. The increment in PWV varies between 4.5 and 6.5 % per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius–Clapeyron equation

The Potsdam open source radio interferometry tool (Port)

Funding Information: Research development for PORT was funded partially by the German Research Foundation (ECORAS-2, SCHU 1103/7-2 and HE5937/2-2). K.B. was funded by the Deutsche For-schungsgemeinschaft (DFG, German Research Foundation)— Project-ID 434617780—SFB 1464 (TerraQ). M.H.X. was supported by the Academy of Finland project No. 315721. S.B. was supported by Generalitat Valenciana SEJIGENT program (SEJIGENT/2021/001). The PORT source code is based on VieVS@GFZ which itself is a fork branched off from VieVS in 2012. In addition, the code contains MATLAB® adaptions of a significant number of IERS library functions (Petit & Luzum 2010) and modified GNU Octave (Eaton et al. 2008; Hansen 2011) routines. Software routines from the International Astronomical Union (IAU) SOFA Collection were used. Copyright ©International Astronomical Union Standards of Fundamental Astronomy (https://www.iausofa.org) (IAU SOFA Board 2021). Source code written by or adapted from D. Agnew, Julien Bect, Johannes Böhm, Sigrid Böhm (née Englich), Maximilien Chaumon, John R. D’Errico, Daniel Gambis, Kurt Hornik, Paul Kienzle, Hana Krásná (née Spicakova), Klemens Lagler, Daniel Landskron, Lucia MacCallum (née Plank), Matthias Madzak, Oliver Montenbruck, Vahab Nafisi, Andrea Pany, Sean Reilly, Beth E. Stetzler, Jing Sun, Kamil Teke, Volker Tesmer, Claudia Tierno Ros, Oleg Titov, Rik Wehbring, Nestor Zarraoa and Nataliya Zubko are acknowledged. We thank the anonymous reviewer for his/her comments and corrections. Publisher Copyright: © 2021. The Astronomical Society of the Pacific.The Potsdam Open Source Radio Interferometry Tool (PORT) is the very long baseline interferometry (VLBI) analysis software developed and maintained at the GFZ German Research Centre for Geosciences. Chiefly, PORT is tasked with the timely processing of VLBI sessions and post-processing activities supporting the generation of celestial and terrestrial reference frames. In addition, it serves as a framework for research and development within the GFZ's VLBI working group and is part of the tool set employed in educating young researchers. Starting out from VLBI group delays, PORT estimates station and radio sources positions, as well as Earth orientation parameters, tropospheric parameters, and station clock offsets and drifts. The estimation procedures take into account all the necessary data analysis models that were agreed on for contributing to the ITRF2020 processing activities. The PORT code base is implemented in the MATLAB (R) and Python programming languages. It is licensed under the terms of the GNU General Public License and available for download at GFZ's Git server .Peer reviewe

Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3)

International audienceThere has been growing interest in recent years in the use of homogeneously reprocessed ground-based GNSS, VLBI, and DORIS measurements for climate applications. Existing datasets are reviewed and the sensitivity of tropospheric estimates to the processing details is discussed. The uncertainty in the derived IWV estimates and linear trends is around 1 kg m−2 RMS and ± 0.3 kg m−2 per decade, respectively. Standardized methods for ZTD outlier detection and IWV conversion are proposed. The homogeneity of final time series is limited however by changes in the stations equipment and environment. Various homogenization algorithms have been evaluated based on a synthetic benchmark dataset. The uncertainty of trends estimated from the homogenized times series is estimated to ±0.5 kg m−2 per decade. Reprocessed GNSS IWV data are analysed along with satellites data, reanalyses and global and regional climate model simulations. A selection of global and regional reprocessed GNSS datasets and ERA-interim reanalysis are made available through the GOP-TropDB tropospheric database and online service. A new tropo SINEX format, providing new features and simplifications, was developed and it is going to be adopted by all the IAG services