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In this paper, the impact of outer loop and partial cycling with the Weather Research and Forecasting Model’s (WRF) three-dimensional variational data assimilation system (3DVAR) is evaluated by analyzing 78 forecasts for three typhoons during 2008 for which Taiwan’s Central Weather Bureau (CWB) issued typhoon warnings, including Sinlaku, Hagupit, and Jangmi. The use of both the outer loop and the partial cycling approaches in WRF 3DVAR are found to reduce typhoon track forecast errors by more than 30%, averaged over a 72-h period. The improvement due to the outer loop approach, which can be more than 42%, was particularly significant in the early phase of the forecast. The use of the outer loop allows more observations to be assimilated and produces more accurate analyses. The assimilation of additional nonlinear GPS radio occultation (RO) observations over the western North Pacific Ocean, where traditional observational data are lacking, is particularly useful. With the lack of observations over the tropical and subtropical oceans, the error in the first-guess field (which is based on a 6-h forecast of the previous cycle) will continue to grow in a full-cycling limited-area data assimilation system. Even though the use of partial cycling only shows a slight improvement in typhoon track forecast after 12 h, it has the benefit of suppressing the growth of the systematic model error. A typhoon prediction model using the Advanced Research core of the WRF (WRF-ARW) and the WRF 3DVAR system with outer loop and partial cycling substantially improves the typhoon track forecast. This system, known as Typhoon WRF (TWRF), has been in use by CWB since 2010 for operational typhoon predictions.

Abstract. In this paper, we perform a systematic evaluation of the impact of Global Positioning System radio occultation (GPSRO) data on typhoon-track prediction over the northwestern Pacific. Specifically, we perform data assimilation and forecast experiments using the Typhoon Weather Research and Forecasting (TWRF) system at 45 km resolution on 11 typhoons (with a total of 327 cases) in the period of 2008-2010 over the northwestern Pacific, with or without the use of GPSRO refractivity observations. On average, about 100 GPSRO soundings are assimilated over a 12 h partially cycling assimilation period. The results indicate that the assimilation of GPSRO data reduces the 72 h track forecast errors by approximately 12 km (5 %). Although this is only a modest improvement, it is statistically significant. The assimilation of GPSRO data improves the analysis and the forecast of temperature, water vapor, and wind fields. Further analysis shows that the reduction in typhoon-track forecast errors can be attributed to the improved prediction of western Pacific subtropical high (WPSH) and its associated circulation, which leads to better forecasting of the environmental steering flow.

This paper introduces a relocation scheme for tropical cyclone (TC) initialization in the Advanced Research Weather Research and Forecasting (ARW-WRF) model and demonstrates its application to 70 forecasts of Typhoons Sinlaku (2008), Jangmi (2008, and Linfa (2009) for which Taiwan's Central Weather Bureau (CWB) issued typhoon warnings. An efficient and dynamically consistent TC vortex relocation scheme for the WRF terrainfollowing mass coordinate has been developed to improve the first guess of the TC analysis, and hence improves the tropical cyclone initialization. The vortex relocation scheme separates the first-guess atmospheric flow into a TC circulation and environmental flow, relocates the TC circulation to its observed location, and adds the relocated TC circulation back to the environmental flow to obtain the updated first guess with a correct TC position. Analysis of these typhoon cases indicates that the relocation procedure moves the typhoon circulation to the observed typhoon position without generating discontinuities or sharp gradients in the first guess.Numerical experiments with and without the vortex relocation procedure for Typhoons Sinlaku, Jangmi, and Linfa forecasts show that about 67% of the first-guess fields need a vortex relocation to correct typhoon position errors while eliminates the topographical effect. As the vortex relocation effectively removes the typhoon position errors in the analysis, the simulated typhoon tracks are considerably improved for all forecast times, especially in the early periods as large adjustments appeared without the vortex relocation. Comparison of the horizontal and vertical vortex structures shows that large errors in the first-guess fields due to an incorrect typhoon position are eliminated by the vortex relocation scheme and that the analyzed typhoon circulation is stronger and more symmetric without distortions, and better agrees with observations. The result suggests that the main difficulty of objective analysis methods [e.g., three-dimensional variational data assimilation (3DVAR)], in TC analysis comes from poor first-guess fields with incorrect TC positions rather than not enough model resolution or observations. In addition, by computing the eccentricity and correlation of the axes of the initial typhoon circulation, the distorted typhoon circulation caused by the position error without the vortex relocation scheme is demonstrated to be responsible for larger track errors. Therefore, by eliminating the typhoon position error in the first guess that avoids a distorted initial typhoon circulation, the vortex relocation scheme is able to improve the ARW-WRF typhoon initialization and forecasts particularly when using data assimilation update cycling.