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Munehiko Yamaguchi and Naohisa Koide

Abstract

TC genesis guidance using the early stage Dvorak analysis technique (EDA) and global ensembles is investigated as one of the statistical–dynamical TC genesis guidance schemes. The EDA is a scheme that enables the analysis of tropical disturbances at earlier stages by adding T numbers of 0.0 and 0.5 to the conventional Dvorak technique. This unique analysis method has been in operation at JMA since 2001. The global ensembles used in this study are the ECMWF, JMA, NCEP, and UKMO ensembles covering from 2010 to 2013. First, probabilities that tropical disturbances analyzed with the EDA reach tropical storm intensity within a certain lead time up to 5 days are statistically investigated. For example, the probabilities that a tropical disturbance analyzed with T numbers of 0.0, 0.5, and 1.0 reaches tropical storm intensity within 2 days are 15%, 23%, and 57%, respectively. While the false alarm ratio (FAR) is found to decrease if the global ensembles simulate the tropical disturbance analyzed with the EDA in the models, it tends to decrease with the increasing number of such ensemble members. Also, it should be noted that the probability of detection (POD) decreases with the increasing number of such ensemble members. One of the potential uses of these verification results is that forecasters could issue TC genesis forecasts by counting ensemble members that successfully simulate a targeted tropical disturbance and then refer to the FAR and POD corresponding to the number of the ensemble members. These would provide some confidence information of the forecasts.

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Munehiko Yamaguchi, Frédéric Vitart, Simon T. K. Lang, Linus Magnusson, Russell L. Elsberry, Grant Elliott, Masayuki Kyouda, and Tetsuo Nakazawa

Abstract

Operational global medium-range ensemble forecasts of tropical cyclone (TC) activity (genesis plus the subsequent track) are systematically evaluated to understand the skill of the state-of-the-art ensembles in forecasting TC activity as well as the relative benefits of a multicenter grand ensemble with respect to a single-model ensemble. The global ECMWF, JMA, NCEP, and UKMO ensembles are evaluated from 2010 to 2013 in seven TC basins around the world. The verification metric is the Brier skill score (BSS), which is calculated within a 3-day time window over a forecast length of 2 weeks to examine the skill from short- to medium-range time scales (0–14 days). These operational global medium-range ensembles are capable of providing guidance on TC activity forecasts that extends into week 2. Multicenter grand ensembles (MCGEs) tend to have better forecast skill (larger BSSs) than does the best single-model ensemble, which is the ECMWF ensemble in most verification time windows and most TC basins. The relative benefit of the MCGEs is relatively large in the north Indian Ocean and TC basins in the Southern Hemisphere where the BSS of the single-model ensemble is relatively small. The BSS metric and the reliability are found to be sensitive to the choice of threshold wind values that are used to define the model TCs.

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Udai Shimada, Hiromi Owada, Munehiko Yamaguchi, Takeshi Iriguchi, Masahiro Sawada, Kazumasa Aonashi, Mark DeMaria, and Kate D. Musgrave

Abstract

The Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind speed (Vmax)]. To further improve the accuracy of the Japan Meteorological Agency version of SHIPS, five new predictors associated with TC rainfall and structural features were incorporated into the scheme. Four of the five predictors were primarily derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetry of rainfall distribution around a TC multiplied by ocean heat content (OHC), rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain multiplied by OHC. The fifth predictor is the Rossby number. Among these predictors, the axisymmetry multiplied by OHC had the greatest impact on intensity change, particularly, at forecast times up to 42 h. The forecast results up to 5 days showed that the mean absolute error (MAE) of the Pmin forecast in SHIPS with the new predictors was improved by over 6% in the first half of the forecast period. The MAE of the Vmax forecast was also improved by nearly 4%. Regarding the Pmin forecast, the improvement was greatest (up to 13%) for steady-state TCs, including those initialized as tropical depressions, with slight improvement (2%–5%) for intensifying TCs. Finally, a real-time forecast experiment utilizing the hourly near-real-time GSMaP product demonstrated the improvement of the SHIPS forecasts, confirming feasibility for operational use.

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