Preprints
https://doi.org/10.5194/gmd-2023-202
https://doi.org/10.5194/gmd-2023-202
Submitted as: development and technical paper
 | 
15 Dec 2023
Submitted as: development and technical paper |  | 15 Dec 2023
Status: this preprint is currently under review for the journal GMD.

Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1

Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert

Abstract. In this study, we have incorporated tropospheric gradient observations from a Global Navigation Satellite Systems (GNSS) ground station network into the Weather Research and Forecasting (WRF) model through a newly developed observation operator. The experiments are aimed to test the functionality of the developed observation operator and to analyze the impact of tropospheric gradients in the sophisticated Data Assimilation (DA) system. The model was configured for a 0.1-degree mesh over Germany with 50 vertical levels up to 50 hPa. Our initial conditions were obtained from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data at 0.25-degree resolution, and conventional observations were obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF), restricted to surface stations and radiosondes. We selected approximately 100 GNSS stations with high data quality and availability covering Germany. We performed DA every 6 hours for June and July 2021. Three experiments were conducted: 1) The control run assimilating only conventional observations; 2) the impact run assimilating Zenith Total Delays (ZTDs) on top of the Control run; and 3) the Impact-Gradient run assimilating ZTDs and gradients on top of the Control run. The error for the Impact run was reduced by 32 % and 10 % for ZTDs and gradients, whereas the error for the Impact-Gradient run was reduced by 35 % and 18 %, respectively. Overall, the newly developed operator for the WRF DA system works as intended. In particular, the combined assimilation of gradients and the ZTDs led to a notable improvement in the humidity field at altitudes above 2.5 km. With the source codes developed and freely available to the WRF users, we aim to trigger further GNSS tropospheric gradient assimilation studies to refine the technique and improve its performance.

Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2023-202', Anonymous Referee #1, 23 Jan 2024
  • RC2: 'Comment on gmd-2023-202', Anonymous Referee #2, 20 Feb 2024
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert

Data sets

Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1 Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert https://doi.org/10.5281/zenodo.10276429

Model code and software

Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1 Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert https://doi.org/10.5281/zenodo.10276429

Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert

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Short summary
Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.