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The Performance of the Meteorological Of®ce Global Model in Predicting the Tracks of Atlantic Tropical Cyclones in 1995

J. T. HEMING AND A. M. RADFORD Meteorological Of®ce, Bracknell, Berkshire, United Kingdom (Manuscript received 3 September 1996, in ®nal form 6 May 1997)

ABSTRACT In 1994 the United Kingdom Meteorological Of®ce (UKMO) introduced a new method for intitializing tropical cyclones (TCs) in its global model by use of ``bogus'' data. This has resulted in a major reduction in TC forecast errors and has made the model far more competitive in the ®eld of TC forecasting. The unusually active Atlantic TC season of 1995 produced a stern test of the qualities of the model forecasts. A full assessment of UKMO forecasts shows that the mean forecast errors for TCs in the Atlantic in 1995 were lower than mean errors for the UKMO model in any previous year. Errors were also lower than those of the European Centre for Medium- Range Weather Forecasts model at all forecast ranges shorter than 120 h. In addition, assessment carried out at the National Hurricane Center (NHC), Miami, found that UKMO forecasts were better than all forms of guidance available to NHC, although they were not available to NHC in real time.

1. Introduction The tangential wind speed at each point on the mesh is derived from a combination of TC advisory message in- The current con®guration of the United Kingdom Me- formation and real observations. An asymmetry to the teorological Of®ce (UKMO) global numerical weather wind ¯ow is achieved by imposing a steering ¯ow (past prediction (NWP) model has a horizontal grid spacing 6-h movement vector) on the tangential wind values. This of 139 km ϫ 93 km at the equator and has 19 levels is the best approximation of asymmetry given the data in the vertical (Cullen 1993). This resolution is not ®ne available in real time. This formulation is shown diagram- enough to represent the detailed structure of a tropical matically in Fig. 1 and is described in more detail by cyclone (TC) vortex. However, the position of a TC and Heming et al. (1995). In tests, this new technique produced the interaction of the environmental ¯ow upon it can track forecast error reductions of between 25% and 46%. be modeled with suf®cient accuracy so as to produce a A diagnostic study by Chan and Kwok (1996) found that useful NWP forecast of the track of the TC. these improvements resulted from a combination of better Since most TCs form in data-sparse oceanic areas, re- initial positioning and representation of the radial structure liance cannot be placed on conventional observations to and asymmetry of the TC. de®ne the structure of the TC in the NWP model. Hence, Following implementation of the new intialization for some years the UKMO has used ``bogus'' observations technique in 1994, there were two more Atlantic TCs to de®ne the location and structure of the TC in the model. before the end of the season. UKMO forecasts for both These are derived from information found in TC advisory Hurricanes Florence and Gordon were very good with messages issued by TC warning centers. The earliest meth- mean skill scores against climatology and persistence od of bogussing used (Radford 1994) was relatively sim- (CLIPER) forecast methods for the unusual track of plistic and, despite producing an improvement in TC track Hurricane Gordon of between 51% and 67% (see section forecasts when compared with forecasts using no bogus 3 for a de®nition of skill score). observations (Heming 1993), also produced a systematic This paper will examine the performance of the UKMO bias in forecasts (Heming et al. 1995). In late 1994 a new, global model in predicting the tracks of all 19 tropical more sophisticated technique for initializing TCs in the storms of the 1995 Atlantic season (see Fig. 2) and will model was implemented. This involves creating a mesh compare the results with other NWP models and forecast of bogus wind data at the surface and three upper levels. guidance and with UKMO results from previous years.

2. Comparison with other models Corresponding author address: Julian T. Heming, Forecasting Sys- a. Models available to the National Hurricane Center tems Branch, Meteorological Of®ce, London Rd., Bracknell, Berk- shire RG12 2SZ, United Kingdom. UKMO forecasts were not available to the National E-mail: [email protected] Hurricane Center (NHC), Miami, in real time during the

᭧ 1998 American Meteorological Society

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UKMO TC veri®cation scheme Radford (1996) com- pared all TC forecasts in 1995 for the UKMO and ECMWF global models and found that UKMO forecast track errors were smaller at all forecast ranges shorter than 120 h. The results for the Atlantic basin alone are similar to those for all TC basins in 1995. These are shown graphically in Figs. 4 and 5 (see section 3 for de®nitions of forecast errors and skill scores). UKMO analyses were much better due to the use of the bo- gussing technique described above (ECMWF do not use an arti®cial TC initialization technique). UKMO T ϩ 24 forecasts showed 40% more skill over CLIPER than the corresponding ECMWF forecasts, but by T ϩ 120 the two models showed very similar results. This dif- ference in error growth rate can probably be attributed to the models' formulation rather than any difference in analysis systems.

3. Assessment of individual storm tracks The UKMO TC veri®cation method identi®es a TC center by locating a maximum in 850-hPa relative vor- ticity; this is in accordance with WMO recommenda- tions. A forecast is only veri®ed if the TC was classi®ed as a tropical storm (winds greater than 34 kt) both at the data time and validity time of the forecast. Full FIG. 1. Formulation of the new UKMO TC bogus scheme. details of the veri®cation technique can be found in Heming (1994). The forecast error (FE) is de®ned as the straight-line distance between the observed and fore- 1995 Atlantic season. However, following the end of cast positions of the TC. Forecast skill is a comparison the season, NHC performed an assessment of all the between the model FE and the FE as computed by CLI- guidance available to NHC and compared it with the PER (Neumann 1972). In this paper skill scores are of®cial NHC forecasts and UKMO forecasts (Gross de®ned as (CLIPER error Ϫ model error)/(CLIPER er- 1996, personal communication). Figure 3 shows mean ror) expressed as a percentage. A positive skill score forecast errors (in kilometers) for all 10 forms of guid- indicates the model was more skilful than CLIPER. Ta- ance for all storms during the season. The graph indi- ble 1 lists all 19 Atlantic TCs in 1995 in order of strength cates that at all forecast times beyond T ϩ 12, the as de®ned by the observed . UKMO track forecast errors were the smallest, beating Tables 2 and 3 show mean FEs and skill scores for each even the high-resolution Geophysical Fluid Dynamics of these TCs in strength order and the mean ®gures for Laboratory model (Kurihara et al. 1993; Bender et al. the period 1988±94. Nineteen eighty-eight was the ®rst 1993). Mean UKMO forecast errors for T ϩ 24, T ϩ year that TC tracks were veri®ed at the UKMO using 48, and T ϩ 72 were some 12% below the of®cial NHC the current method. The forecasts for each TC are dis- forecast. The storms where UKMO forecasts were par- cussed below in order of observed maximum wind ticularly good compared to other guidance were Mari- strength of the storm. lyn, Opal, and Roxanne (see individual track veri®cation was the strongest storm of the year in section 3). and was one of the three best forecast storms by the UKMO model when compared to other models available b. Comparison with the European Centre for to NHC (see section 2a). The FEs and skill scores were, Medium-Range Weather Forecasts (ECMWF) however, far from the best of all storms and early fore- model casts failed to predict the acceleration of the storm to the northeast as it raced toward the Gulf Coast. However, Comparisons made in recent years by the Japanese the timing of the sudden turn was well predicted as, Meteorological Agency (JMA) have con®rmed eventually, was the of this destructive hurricane. ECMWF forecasts of TCs in the western North Paci®c was one of the most noteworthy hur- as the most accurate when compared with UKMO and ricanes of the year as it devastated parts of the northeast JMA forecasts until 1994 when UKMO forecasts started Caribbean before turning north and northeastward and to show an improvement (Sato 1996, personal com- transforming into a very strong midlatitude depression. munication). In a separate assessment made using the UKMO FEs and skill scores for Hurricane Luis were

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FIG. 2. Observed tracks of tropical cyclones in the North Atlantic in 1995.

FIG. 3. Mean forecast track errors for models available to NHC for the 1995 North Atlantic season.

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FIG. 4. Mean tropical cyclone forecast track errors for UKMO and ECMWF for the 1995 North Atlantic season. among the best of all the season's hurricanes. The fore- Hurricane Luis was quickly followed by Hurricane casts were also the most consistent, indicating that the Marilyn, which, despite a couple of poor forecasts dur- hurricane would turn northward before reaching Puerto ing its early stage, was generally very well forecast with Rico and Hispaniola. Figure 6 shows the observed and FEs well below and skill scores well above the 1988± successive forecast tracks for Hurricane Luis. 94 mean. In the comparison with other models available Forecasts for were also very suc- to NHC, was one of the three best cessful with FEs well below the 1988±94 mean and skill forecast storms of the year by the UKMO model. scores between 38% and 48%. The most signi®cant fea- was another of the three best fore- ture of the UKMO forecasts was the correct prediction cast storms of the year by UKMO when compared with that following the storm's turn toward the United States other models available to NHC. FEs were well below after passing , it would stall short of making the 1988±94 mean values and skill scores in excess of landfall and turn back out to sea, whereas some other 30% at all forecast times. The model did particularly models were predicting landfall. well in predicting some of the unusual characteristics

FIG. 5. Mean tropical cyclone forecast skill scores for UKMO and ECMWF for the 1995 North Atlantic season.

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TABLE 1. Observed maximum sustained wind strengths of all At- TABLE 3. Skill scores for all Atlantic tropical cyclones in 1995. lantic tropical cyclones in 1995. MSW is maximum sustained wind Skill is skill score (%). Number in parentheses is number of forecasts (kt). veri®ed. MSW is maximum sustained wind.

Rank Name MSW T ϩ 24 1 Opal 130 MSW skill T ϩ 72 2 Luis 120 rank rank Name T ϩ 24 skill T ϩ 48 skill skill 3 Felix 115 4 Marilyn 100 1 5 Opal 21 (7) 40 (5) 39 (3) 5 Roxanne 95 2 6 Luis 18 (22) 48 (20) 58 (20) 5 Iris 95 3 2 Felix 38 (22) 48 (20) 45 (19) 7 Humberto 90 4 3 Marilyn 35 (15) 40 (13) 29 (9) 8 Tanya 75 5 4 Roxanne 32 (16) 43 (12) 36 (12) 8 Erin 75 5 9 Iris 8 (19) 43 (17) 54 (15) 10 Noel 65 7 12 Humberto Ϫ10 (13) 32 (11) 17 (9) 10 Allison 65 8 14 Tanya Ϫ12 (5) 15 (2) Ð 12 Chantal 60 8 1 Erin 62 (5) 75 (3) 83 (1) 13 Sebastien 50 10 8 Noel 10 (16) 40 (11) 17 (10) 13 Pablo 50 10 11 Allison 1 (1) Ð Ð 13 Barry 50 12 7 Chantal 15 (9) 18 (6) 24 (3) 16 Gabrielle 45 13 10 Sebastien 2 (2) Ð Ð 16 Karen 45 13 13 Pablo Ϫ11 (1) Ϫ62 (1) Ð 18 Dean 35 13 Ð Barry Ð Ð Ð 18 Jerry 35 16 Ð Gabrielle Ð Ð Ð 16 15 Karen Ϫ52 (3) 51 (1) Ð 18 Ð Dean Ð Ð Ð 18 Ð Jerry Ð Ð Ð of this storm; most notably its turn back on itself when 1988±94 mean 1 (279) 26 (194) 20 (136) in the southern Gulf of Mexico and its eventual dissi- pation without making landfall on the gulf's western coast. Hurricanes Humberto and Iris produced FEs that were were below the mean. The model also tended to dissipate about 30% below the 1988±94 mean in both cases. How- the storm too early in the forecast. This accounts for ever, while Hurricane Humberto's skill scores were near the lack of veri®cation statistics beyond T ϩ 48. to the 1988±94 mean values, 's scores was extremely well forecast by the were signi®cantly higher than the mean; 34% higher at UKMO model. All mean errors out to T ϩ 96 were T ϩ 72 despite early forecasts not predicting the extent below 200 km and skill scores were between 62% and of the northward turn of the storm. 83%. These high skill scores can be attributed to a suc- was not so well forecast by the mod- cessful forecast of the straight track of the storm whereas el. FEs were near to the 1988±94 mean and skill scores CLIPER forecasts expected the storm to recurve as it

TABLE 2. Forecast errors for all Atlantic tropical cyclones in 1995; FE is forecast error (km). Number in parentheses is number of forecasts veri®ed. MSW is maximum sustained wind.

T ϩ 24 MSW rank FE rank Name T ϩ 24 FE T ϩ 48 FE T ϩ 72 FE T ϩ 96 FE T ϩ 120 FE 1 11 Opal 165 (9) 300 (7) 447 (5) 684 (3) 1157 (1) 2 4 Luis 109 (24) 138 (22) 196 (20) 254 (18) 330 (15) 3 4 Felix 109 (24) 220 (22) 377 (21) 534 (16) 440 (7) 4 2 Marilyn 85 (16) 174 (14) 284 (10) 390 (5) 727 (5) 5 3 Roxanne 96 (18) 212 (14) 321 (14) 499 (12) 741 (11) 5 12 Iris 176 (21) 251 (19) 333 (17) 453 (11) 681 (8) 7 10 Humberto 163 (15) 216 (13) 286 (11) 433 (9) 592 (6) 8 15 Tanya 262 (7) 342 (4) Ð Ð Ð 8 7 Erin 141 (7) 157 (5) 167 (3) 184 (1) Ð 10 13 Noel 179 (18) 248 (12) 428 (11) 518 (9) 714 (6) 10 9 Allison 162 (3) 330 (1) Ð Ð Ð 12 8 Chantal 147 (11) 290 (8) 479 (5) 978 (1) 1320 (1) 13 17 Sebastien 315 (4) 328 (2) Ð Ð Ð 13 14 Pablo 258 (2) 541 (1) Ð Ð Ð 13 1 Barry 48 (1) Ð Ð Ð Ð 16 16 Gabrielle 269 (1) Ð Ð Ð Ð 16 6 Karen 124 (4) 86 (1) Ð Ð Ð 18 Ð Dean Ð Ð Ð Ð Ð 18 Ð Jerry Ð Ð Ð Ð Ð 1988±94 mean 247 (376) 393 (262) 517 (182) 737 (136) 883 (97)

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FIG. 6. Observed and successive UKMO forecast tracks of Hurricane Luis.

approached the Florida coast. Forecasts for the errati- FEs, the T ϩ 24 skill score of Ϫ52% was the lowest cally moving Hurricane Noel were not so good as for of all Atlantic storms in 1995. However, the T ϩ 48 Erin, but were still better than the 1988±94 mean. score was 51%. The model's major problem with Trop- FEs for , the ®rst and joint weakest ical Storm Karen was retaining its circulation long hurricane of the season, were below the 1988±94 mean enough in the forecast. although this was a relatively short-lived TC and the Tropical Storms Jerry and Dean only brie¯y reached number of forecasts in the sample were small. FEs for tropical storm status and hence produced no forecast Tropical Storm Chantal were smaller than the 1988±94 error statistics. mean up to T ϩ 72, but were larger at longer forecast ranges. The T ϩ 48 skill score was also lower than the 4. Discussion 1988±94 mean. The large 4- and 5-day forecast errors for this storm can be attributed to just one forecast early A more detailed comparison of the UKMO model's in the storm's life, which steered the storm on a more performance for individual storms suggests that the westerly track toward the Bahamas instead of recurving model may perform better for stronger storms than for it as actually occurred. the weaker storms. Tables 2 and 3 show the mean T ϩ Tropical Storms Sebastien, Pablo, Barry, Gabrielle, 24 FE and skill score rankings for each storm alongside and Karen were all relatively short-lived tropical storms. the rankings in order of maximum sustained wind. Low- FEs were near to the 1988±94 mean except for Tropical er FE and higher skill score produce a higher ranking. Storms Karen and Barry, which were well below the Four of the ®ve strongest storms of the year (Luis, Felix, mean. However, only one forecast was veri®ed for Trop- Marilyn, and Roxanne) appear in the top ®ve of the T ical Storm Barry. Tropical Storm Karen interacted with ϩ 24 FE rankings while three of the weakest storms the nearby stronger Hurricane Iris. Despite very low (Sebastien, Pablo, and Gabrielle) appear in the bottom

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FIG. 7. Observed and successive UKMO forecast tracks of Hurricane Marilyn.

FIG. 8. UKMO mean forecast track errors for all Atlantic tropical cyclones in 1995.

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FIG. 9. UKMO mean forecast skill scores for all Atlantic tropical cyclones in 1995.

four (Table 2). In addition, the ®ve strongest storms of 5. Summary the year (Opal, Luis, Felix, Marilyn, and Roxanne) ap- UKMO global model FEs for all Atlantic TCs in 1995 pear in the top six of the T ϩ 24 skill score rankings were 33%±50% lower than the 1988±94 mean value and (Table 3). To assess whether TC strength is directly skill scores were 16%±22% higher (see Figs. 8 and 9). related to FE, all T ϩ 24 FEs for every storm were UKMO FEs in 1995 were also lower than all forms of compared with the observed maximum sustained wind guidance available to NHC. UKMO FEs, averaged over at the data time of the forecast to see if there was any forecast times T ϩ 24, T ϩ 48, and T ϩ 72, were 12% correlation. In fact, the correlation coef®cient was just lower than the of®cial forecasts issued by NHC. In a Ϫ0.18 indicating a very small negative correlation be- comparison with ECMWF, UKMO Atlantic TC fore- tween FE and maximum sustained wind. The correlation casts were found to be better at all ranges shorter than coef®cient was similar for FEs at other forecast times 120 h. While these results indicate a substantial im- and also for skill scores (although the correlation was provement of UKMO forecasts over previous years and positive). Clearly maximum sustained wind strength is other models it must be emphasized that these results not the prime factor that determines the accuracy of each are for just one hurricane season. Hence they cannot be forecast of a storm. taken as an indication of a consistent improvement in Evaluation of individual storm forecasts also sug- the UKMO model. gested that sometimes the model will produce poor fore- Despite making signi®cant advances in TC forecast- casts during the ®rst day or two of the storm's life before ing over recent years that make UKMO forecasts com- starting to produce accurate forecasts. Examples of this parable with or better than most other forms of guidance, are Hurricane Iris, where early forecasts did not predict further improvement should be possible. A trial of an the storm's sharp turn to the north; Hurricane Roxanne, increased resolution global model took place during the where early forecasts predicted immediate recurvature lifetime of Hurricane Bertha in July 1996 and resulted and landfall on the northern Gulf Coast; Tropical Storm in large reductions in FE compared to operational fore- Chantal, where early forecasts took the storm toward casts as well as a much better representation of the TC the Bahamas; and most notably Hurricane Marilyn (see vortex both in the model analysis and forecast. Further Fig. 7), whose early forecasts predicted a much greater enhancements to the TC initialization scheme and an westward component to the forecast track. In all cases, increased resolution global model are planned for im- later forecasts were a vast improvement on earlier pre- plementation in 1998. dictions. It would appear that on occasions the model takes some time to develop an accurate representation of the TC vortex. When the TC is modeled accurately REFERENCES in terms of initial position, vortex structure, and asym- Bender, M. A., R. J. Ross, R. E. Tuleya, and Y. Kurihara, 1993: metry, a good forecast should result assuming an ac- Improvements in tropical cyclone track and intensity forecasts curate prediction of the large-scale environmental ¯ow using the GFDL initialization system. Mon. Wea. Rev., 121, (Chan and Kwok 1996). 2046±2061.

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