Impact of Assimilating FORMOSAT-7/COSMIC-2 Radio Occultation Data on Typhoon Prediction Using a Regional Model

Abstract

As the successor of FORMOSAT-3/COSMIC (FS3/C1), FORMOSAT-7/COSMIC-2 (FS7/C2) was successfully launched on 25 June 2019. FS3 radio occultation (RO) data has contributed greatly to Taiwan’s meteorological progress, improving model representations of marine boundary layer heights, cyclogenesis, tropical cyclones/typhoons, and Mei-Yu front systems. The operational CWBWRF numerical weather prediction model with the 3DEnVar data assimilating system in the Taiwan Central Weather Bureau (CWB) was adopted to evaluate the impact of assimilating FS7 RO data. The following two experiments were conducted: one assimilated the in-situ observations as in the CWB operational task (nRO), and the other additionally assimilated FS7 RO refractivity profiles (wRO). Both experiments utilized 6-h assimilating window and full cycle data assimilation strategy and made 120-h forecasts after each assimilation. Within over 70 synoptic verification cases, the biases of geopotential height, temperature, and wind were reduced in the upper model levels in wRO results, and the typhoon track and intensity prediction error reductions were statistically significant. In addition, the wRO experiment improved the typhoon structure in the initial conditions and led to a better typhoon structure forecast. These results showed that the FS7 RO refractivity assimilation could improve model forecast performance, leading to its operational use in the CWB.

Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere

“…The R-squared (MSE) value increases (decreases) from 0.535 (37.044) with the y i and y i z i terms to 0.732 (26.610) with the y 2 i term. We further apply the minimum variance estimation (MVE;Clarizia et al, 2014) to combine the results from the LSW and TQ estimators. This approach has the advantage of having a smaller root mean square error (RMSE) than either the LSW estimation or the TQ estimation.…”

Assimilation and Evaluation of the COSMIC–2 and Sounding Data in Tropospheric Atmospheric Refractivity Forecasting across the Yellow Sea through an Ocean–Atmosphere–Wave Coupled Model

“…Based on the WRF model, Chen et al assimilated COSMIC-2 occultation data with the 3DEnVar assimilation algorithm and found that the bias of the temperature and wind in the upper atmosphere was reduced. Moreover, the prediction error of the typhoon path and intensity was also reduced [32]. Miller et al used the HWRF model to simulate six hurricane cases in 2020 and found that assimilating COSMIC-2 data significantly reduced the mean absolute prediction error of the minimum central sea level pressure by 8% to 12% [33].…”