3D-Var Assimilation of GNSS Single Frequency Receiver data in RAMS NWP model: Impact Studies over Italy

The purpose of the data assimilation is to optimally use all the available information, to determine as accurately as possible the state of the atmosphere. We show the assimilation of the GPS-ZTD (Global Positioning System - Zenith Total Delay) by a 3D-Var data assimilation system that can be used in cycling mode with the Regional Atmospheric Modeling System (RAMS; Federico, 2013). The water vapour mixing ratio (q) and temperature (T) given by the RAMS model (background) are modified according to the assimilation of the GPS-ZTD with the purpose of improving the representation of the humidity and temperature fields and eventually decrease the model spin-up time. To verify the impact of the GPS-ZTD data assimilation on the representation of the atmospheric humidity field, especially at the local scale, a numerical experiment is performed over an italian region. Processing was carried out in PPP (Precise Point Positioning) using RTKLIB, an Open Source Program Package for GNSS Positioning (http://www.rtklib.com/). As regards GNSS single frequency receivers, they have turned up more and more in marketing for their very low cost with respect to high level of performances. Nevertheless, a still open problem concerns their use for PPP applications, since standard algorithms are based on dual frequency observations to remove ionospheric delay through ionosphere-free combination. The aim of this work is to introduce a new ground based augmentation strategy to obtain PPP at centimetric accuracy level working with single frequency low-cost receivers. The developed algorithm, starting from the observations of a unique dual frequency "reference" receiver, is able to reconstruct L2 synthetic observations for any single frequency receiver located in its surroundings. For the verification of 3D-Var system, the whole dataset is divided in two parts: a set of receivers is used for the data assimilation, while the remaining stations are used for verification. Results show a substantial decrease of the RMSE of the GPS-ZTD and IWV for the stations used for the verification of the methodology; also and the absolute value of the bias is decreased, showing the potential of the assimilation of the GPS-ZTD. For the quantification of the improvement of the IWV forecast, short range (< 3h) prediction of the RAMS model were taken at 4 km horizontal resolution, starting from the 3D-Var analyses. The results of this study are promising and will be further developed in future work with the aim to evaluate the impact of the GPS-ZTD data assimilation on the precipitation forecast. References Bock, O., Bosser, P., Pacione, R., Nuret, M., Fourrie?, N., and Parracho, A.: A high-quality reprocessed ground-based GPS dataset for atmospheric process studies, radiosonde and model evaluation, and reanalysis of HyMeX Special Observing Period, Q. J. Roy. Meteor. Soc., 142, 56-71, https://doi.org/10.1002/qj.2701, 2016. Federico, S.: Implementation of a 3D-Var system for atmospheric profiling data assimilation into the RAMS model: initial results, Atmos. Meas. Tech., 6, 3563-3576, doi:10.5194/amt-6-3563-2013, 2013. Parrish, D. F. and Derber, J. C.: The National Meteorological Center's Spectral Statistical Interpolation analysis system, Mon. Weather Rev., 120, 1747-1763, 1992.