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Typhoon Ensemble Prediction System Developed at the Japan Meteorological Agency

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Typhoon Ensemble Prediction System Developed at the Japan Meteorological Agency 2592 MONTHLY WEATHER REVIEW VOLUME 137 Typhoon Ensemble Prediction System Developed at the Japan Meteorological Agency MUNEHIKO YAMAGUCHI,RYOTA SAKAI,MASAYUKI KYODA,TAKUYA KOMORI, AND TAKASHI KADOWAKI Japan Meteorological Agency, Tokyo, Japan (Manuscript received 24 June 2008, in final form 6 February 2009) ABSTRACT The Japan Meteorological Agency (JMA) Typhoon Ensemble Prediction System (TEPS) and its perfor- mance are described. In February 2008, JMA started an operation of TEPS that was designed for providing skillful tropical cyclone (TC) track predictions in both deterministic and probabilistic ways. TEPS consists of 1 nonperturbed prediction and 10 perturbed predictions based on the lower-resolution version (TL319L60) of the JMA Global Spectral Model (GSM; TL959L60) and a global analysis for JMA/GSM. A singular vector method is employed to create initial perturbations. Focusing on TCs in the western North Pacific Ocean and the South China Sea (08–608N, 1008E–1808), TEPS runs 4 times a day, initiated at 0000, 0600, 1200, and 1800 UTC with a prediction range of 132 h. The verifications of TEPS during the quasi-operational period from May to December 2007 indicate that the ensemble mean track predictions statistically have better perfor- mance as compared with the control (nonperturbed) predictions: the error reduction in the 5-day predictions is 40 km on average. Moreover, it is found that the ensemble spread of tracks is an indicator of position error, indicating that TEPS will be useful in presenting confidence information on TC track predictions. For 2008 when TEPS was in operational use, however, it was also found that the ensemble mean was significantly worse than the deterministic model (JMA/GSM) out to 84 h. 1. Introduction While the accuracy of TC track forecasts has im- proved significantly, ensemble techniques have been In 1997, the Japan Meteorological Agency (JMA) attracting much attention because they are expected to started to provide public users with 3-day track forecasts improve deterministic TC track forecasts and also provide of tropical cyclones (TCs) in the western North Pacific the uncertainty information (WMO 2008a), based on Ocean and South China Sea based on numerical weather ensemble mean and ensemble spread, respectively (e.g., prediction [NWP; the (Regional Specialized Meteoro- Jeffries and Fukada 2002; Vijaya Kumar and Krishna- logical Center) RSMC Tokyo-Typhoon Center 1997]. murti 2003; Sampson et al. 2006; Goerss 2007). For the Since then, the remarkable progress of the JMA NWP western North Pacific basin, Goerss et al. (2004) have system has brought considerable improvement of the shown that the consensus of three models, the Navy track forecasts. According to the verification of the JMA Operational Global Atmospheric Prediction System global NWP system, the 3-yr running mean of position (NOGAPS; Hogan and Rosmond 1991; Goerss and errors of 5-day predictions in 2007 (451 km, the average Jeffries 1994), the Met Office (UKMO) global model of 2005, 2006, and 2007) is smaller than that of 3-day (Cullen 1993; Heming et al. 1995), and the JMA ty- predictions in 1997 (472 km, the average of 1995, 1996, phoon model (TYM; Kuma 1996), has reduced forecast and 1997), indicating that we have succeeded in ob- errors with respect to the best of the individual models. taining a 2-day lead time of deterministic TC track For 2002, for example, the improvement rate of the predictions over the past 11 yr (see Fig. 1). consensus with respect to the best of the individual models is 17%, 14%, and 11% at 24, 48, and 72 h, re- spectively. Goerss (2000) has also shown the effective- Corresponding author address: Munehiko Yamaguchi, 1-3-4 Ote- ness of consensus forecasts for both the western North machi, Chiyoda-ku, Tokyo, 100-8122 Japan. Pacific and the Atlantic basin: using the JMA global E-mail: [email protected] model (GSM; Kuma 1996), NOGAPS, and UKMO for DOI: 10.1175/2009MWR2697.1 Ó 2009 American Meteorological Society Unauthenticated | Downloaded 10/04/21 05:12 PM UTC AUGUST 2009 Y A M AGUCHI ET AL. 2593 TEPS during the quasi-operational period as well as its specifications: first, the skill of ensemble mean track predictions is verified; and second, the effectiveness of confidence information on track predictions using the ensemble spread is verified. Moreover, the verification of confidence information is performed by dividing the ensemble spread into along-track and cross-track di- rections since the prediction of uncertainty in timing and location of TC impacts is essential (Aberson 2001). Section 2 describes the specifications of TEPS: the NWP system and the method to create initial perturbations. Section 3 describes the performance of TEPS, and sec- tion 4 discusses the performance. The summary and conclusions are presented in section 5. FIG. 1. Time series of 3-yr running mean of position errors by JMA/GSM from 1997 to 2007 (e.g., the verification value of 2007 is 2. Specifications of TEPS the average of that of 2005, 2006, and 2007). Each line represents the errors of 24-, 48-, 72-, 96-, and 120-h predictions from the bottom up. a. Overview of TEPS In February 2008, JMA started an operation of TEPS the western North Pacific basin; and the Geophysical (Fig. 2). TEPS uses a lower-resolution version of the Fluid Dynamics Laboratory Hurricane Prediction System JMA/GSM. The model resolution of TEPS is TL319L60, (GFDL; Kurihara et al. 1993, 1995, 1998), NOGAPS, the spectral triangular truncation TL319 (the ‘‘L’’ indi- and UKMO for the Atlantic basin. For the western cating the linear grid option) and 60 vertical levels, while North Pacific during 1997, the improvement rate with that of JMA/GSM is TL959L60 (Iwamura and Kitagawa respect to the best of the individual models is 16%, 13%, 2008). As TEPS does not have its own data assimilation and 12% at 24, 48, and 72 h, and for the 1995–96 Atlantic system, a global analysis for JMA/GSM, which is based hurricane seasons, the improvement rate is 16%, 20%, on a four-dimensional variational data system (4DVAR; and 23% at 24, 48, and 72 h, respectively. Furthermore, Kadowaki 2005; JMA 2007), is used for an initial condi- Komori et al. (2007) have verified the ensemble mean tion of the nonperturbed run of TEPS after interpolating track of three global models from operational NWP cen- it from TL959L60 to TL319L60. ters, the European Centre for Medium-Range Weather Forecasters on duty at JMA initiate the operation of Forecasts (ECMWF), JMA, and UKMO. In the verifi- TEPS when the following two conditions are satisfied: cation of 48- and 96-h predictions for the western North 1) TCs are located in the RSMC Tokyo-Typhoon Pacific basin from 1991 to 2005, and for the Atlantic basin Center’s responsibility area of 08–608N, 1008E–1808, from 1999 to 2005, the ensemble mean has the best per- or are expected to move into the area within 24 h. formance with respect to the best of the individual models 2) The TC’s maximum sustained wind speed exceeds with few exceptional years. For a study on evaluating the 34 kt or is expected to reach the threshold within 24 h ensemble spread of TC track predictions, Goerss (2000) (in that sense, the name of TEPS might not be ap- and Elsberry and Carr (2000) have demonstrated the propriate because we call TCs with a maximum benefit of the ensemble spread as a measure of confidence sustained wind of 64 kt or more ‘‘typhoon’’). in ensemble TC predictions: a small spread of tracks is often an indication of a small error of ensemble mean track TEPS runs 4 times a day, initiated at 0000, 0600, 1200, prediction. These arguments form the rationale for the and 1800 UTC with a prediction range of 132 h. The development of the ensemble prediction system (EPS). ensemble size is 11. A singular vector (SV) method Recently, JMA has developed a new Typhoon EPS (Buizza 1994; Molteni et al. 1996; Puri et al. 2001) is (TEPS). Different from the multimodel EPS mentioned employed to create initial perturbations (see section 2b above, TEPS is based on a sole NWP model with per- for more details). A method dealing with the uncertainty turbed initial conditions. To evaluate whether the en- of an NWP model itself such as a stochastic physics semble mean and ensemble spread of TEPS have sim- method (Buizza et al. 1999) is yet to be considered. ilar characteristics as compared with the multimodel b. Singular vector method EPS used in previous studies, we conducted a series of quasi-operational runs of TEPS from May to December Under the assumption that a perturbation grows 2007. This paper describes the verification results of linearly, a SV with a large singular value represents a Unauthenticated | Downloaded 10/04/21 05:12 PM UTC 2594 MONTHLY WEATHER REVIEW VOLUME 137 FIG. 2. Time line of the upgrade of JMA NWP systems: JMA/GSM, TYM, WEPS, and TEPS. sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi fast-growing perturbation (Lorenz 1965). Consider a 1/2 À1/2 1/2 À1/2 kx(t 5 t )k (x^,(Ef TMEi )*Ef TMEi x^) growth rate of a perturbation x as shown in Eq. (1): a 5 , (3) kx(t 5 t0)k (x^, x^) kx(t 5 t )k sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi a x 2 Rn, (1) 5 (x^, A*Ax^) kx(t t0)k 5 . (4) (x^, x^) where x(t 5 t0) is a perturbation at a base time t0, x(t 5 ta) is one at an optimization time ta (ta . t0), and kk de- Equation (4) represents that SVs, or forward SVs of notes the norm associated with the Euclidean inner matrix A, grow linearly about a given trajectory with product.
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