Estimation of 3D wet refractivity by tomography, combining GNSS and NWP data: First results from assimilation of wet refractivity into NWP. (4th March 2019)

• Record Type: Journal Article
• Authors: Trzcina, Estera; Rohm, Witold
• Is Part Of: Quarterly journal of the Royal Meteorological Society. Volume 145:Number 720(2019)
• Page Start: 1034
• Page End: 1051
• Publication Date: 2019-03-04
• Subjects: data assimilation -- GNSS meteorology -- GNSS troposphere tomography -- numerical weather prediction models; Meteorology -- Periodicals; 551.5
• DOI: 10.1002/qj.3475
• Languages: English
• ISSNs: 0035-9009

Abstract

Abstract : The magnitude of water‐vapour content and its temporal variability are factors that influence the thermodynamics of the atmosphere significantly and result in different meteorological phenomena or hazards. High‐quality observations of water‐vapour spatial and temporal distribution enable precise weather forecasts to be made. Global Navigation Satellite System (GNSS) troposphere tomography is a technique that enables derivation of a three‐dimensional (3D) distribution of the wet refractivity with low cost in all weather conditions, based on GNSS slant observations of tropospheric delay. The tomographic estimations of the wet refractivity distribution have the potential to improve numerical weather prediction (NWP) models. In this study, we established a near‐real‐time (NRT) tomographic solution in the area of Poland using the TOMO2 model in order to verify whether tomographic products can attain the required accuracy and be assimilated into operational NWP models. The assimilation of the TOMO2 output into a weather research and forecasting (WRF) model was performed, using the WRF Data Assimilation (WRFDA) system and a GPSREF observation operator dedicated to radio occultation (RO) total refractivity assimilation. Two selected analysis periods covered summer storms and autumn rainfalls. The validation of the WRF model analysis with GNSS integrated water vapour (IWV) data, synoptic observations, radiosonde profiles, and ERA‐Interim reanalysis indicated an improvement in the relative humidity in the top tropospheric layers (the bias decreased by 1.4–4.6% and the standard deviation by 0.8–2.8%). In the middle troposphere, a positive impact was noticed in the summer (the standard deviation of the relative humidity decreased by 0.15%) but not in the autumn. The forecast at lead times of 6–18 hr was visibly improved in the autumn (reduction of root‐mean‐square error (RMSE) by 0.5% in relative humidity and 0.25 °C in temperature, reduction in standard deviation of surface pressure by 0.5 hPa), while in the summer the results were neutral or negative (RMSE of relative humidity increased by 1.0%). Abstract : In this study we present the near‐real time Global Navigation Satellite System (GNSS) troposphere tomography model TOMO2 used for estimation of the 3D wet refractivity field in the troposphere, with root‐mean‐square error lower than 10 parts per million (ppm) in summer and 5 ppm in autumn. We assimilated the TOMO2 output into the Weather Research and Forecasting model using a GPSREF observation operator dedicated for radio occultation data. We observe the assimilation results in improvement of surface pressure, temperature, and relative humidity forecasts, especially in autumn up to 18 hr lead time.