Comparisons between the WRF data assimilation and the GNSS tomography technique in retrieving 3-D wet refractivity fields in Hong Kong

Abstract

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to accurately describe its three-dimensional (3-D) dynamical changes. The data assimilation technique and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting Data Assimilation (WRFDA) model (a representative of the data assimilation models) in retrieving wet refractivity (WR) in the Hong Kong area during a wet period and a dry period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delays. The WRFDA is used to assimilate the zenith tropospheric delay to improve the background data. The radiosonde data are used to validate the WR derived from the GNSS tomography, the WRFDA output, and the background data. The root mean square (rms) of the WR derived from the tomography results, the WRFDA output, and the background data are 6.50, 4.31, and 4.15 mm km−1 in the wet period. The rms becomes 7.02, 7.26, and 6.35 mm km−1 in the dry period. The lower accuracy in the dry period is mainly due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA only slightly improves the accuracy of the WR and that the WRFDA WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the WRFDA WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA, the retrieved WR is improved.