520 AND FORECASTING VOLUME 22

Dynamical Tropical 96- and 120-h Track Forecast Errors in the Western North Pacific

RYAN M. KEHOE,MARK A. BOOTHE, AND RUSSELL L. ELSBERRY Graduate School of Engineering and Applied Sciences, Naval Postgraduate School, Monterey, California

(Manuscript received 15 February 2006, in final form 29 September 2006)

ABSTRACT

The Joint Warning Center has been issuing 96- and 120-h track forecasts since May 2003. It uses four dynamical models that provide guidance at these forecast intervals and relies heavily on a consensus of these four models in producing the official forecast. Whereas each of the models has skill, each occa- sionally has large errors. The objective of this study is to provide a characterization of these errors in the western North Pacific during 2004 for two of the four models: the Navy Operational Global Atmospheric Prediction System (NOGAPS) and the U.S. Navy’s version of the Geophysical Fluid Dynamics Laboratory model (GFDN). All 96- and 120-h track errors greater than 400 and 500 n mi, respectively, are examined following the approach developed recently by Carr and Elsberry. All of these large-error cases can be attributed to the models not properly representing the physical processes known to control motion, which were classified in a series of conceptual models by Carr and Elsberry for either tropical- related or midlatitude-related mechanisms. For those large-error cases where an error mechanism could be established, midlatitude influences caused 83% (85%) of the NOGAPS (GFDN) errors. The most common tropical influence is an excessive direct cyclone interaction in which the tropical cyclone track is erroneously affected by an adjacent cyclone. The most common midlatitude-related errors in the NOGAPS tracks arise from an erroneous prediction of the environmental flow dominated by a ridge in the midlatitudes. Errors in the GFDN tracks are caused by both ridge-dominated and trough-dominated environmental flows in the midlatitudes. Case studies illustrating the key error mechanisms are provided. An ability to confidently identify these error mechanisms and thereby eliminate likely erroneous tracks from the consensus would improve the accuracy of 96- and 120-h track forecasts.

1. Introduction ance is likely to be erroneous and thus should be re- jected during preparation of the warning. Carr and Elsberry (2000a,b) examined all of the A change in paradigm to consensus tropical cyclone highly erroneous (Ͼ300 n mi or 555 km at 72 h) Navy track forecasting was occurring at the same time. Operational Global Atmospheric Prediction System Goerss (2000) had developed a three-global-model or (NOGAPS) and U.S. Navy version of the Geophysical two-regional-model consensus technique at the synop- Fluid Dynamics Laboratory model (GFDN) tropical tic and off-synoptic times, respectively. As part of the cyclone track forecast errors in the western North Pa- Systematic Approach Forecasting Aid (SAFA; Carr et cific during 1997. They described the responsible error al. 2001), the above models and the Global Spec- mechanisms in terms of conceptual models that are re- tral Model (JGSM), the Typhoon Model (JTYM), and lated to known tropical cyclone motion processes that the Met Office (UKMO) global model were interpo- are being misrepresented in the dynamical models. The lated in time so that five tracks would be available each motivation for the Carr and Elsberry study was to help 6 h (Carr et al. 2001). Elsberry and Carr (2000) docu- the forecaster detect when the dynamical model guid- mented that a small spread (Ͻ300 n mi) among these five model 72-h tracks often implied a small consensus error, but that a large spread did not necessarily imply a large consensus track error because the errors of two Corresponding author address: R. L. Elsberry, Dept. of Meteo- rology, MR/Es, Rm. 254, 589 Dyer Rd., Monterey, CA 93943- (or more) of the models may be compensating. One of 5114. the objectives in SAFA is to examine the model guid- E-mail: [email protected] ance and eliminate the model tracks that are likely to

DOI: 10.1175/WAF1002.1

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WAF1002 JUNE 2007 KEHOE ET AL. 521 have large errors to form a selective consensus of the cause the consensus to be seriously degraded. Never- remaining model tracks that should be more accurate theless, the hypothesis is that elimination of the erro- than a nonselective consensus of all five dynamical neous model track and reduction of the consensus to models. only three model tracks would still lead to a more ac- The Joint Typhoon Warning Center (JTWC), with curate forecast. Since this is a retrospective study of the assistance of the Naval Research Laboratory, in cases in which it is known that the dynamical model had Monterey, California, has expanded the consensus fore- a large error, it is a separate issue whether these errors casting concept so that during the 2004 typhoon can be detected in real time. its consensus forecast (CONW) included 10 global and regional model tracks. In addition to the five models 2. Methodology mentioned above, the CONW also includes the Na- tional Centers for Environmental Prediction Global The approach has been to analyze all cases in which Forecast System (GFS), the Australian Bureau of Me- large 120-h track errors occurred in the NOGAPS and teorology’s Tropical Cyclone Local Area Prediction GFDN forecasts of western North Pacific tropical cy- System, the Weber Barotropic Model, the U.S. Air clones during 2004. Only these two models are exam- Force’s version of the fifth-generation Pennsylvania ined because a complete archive of analyses and fore- State University–National Center for Atmospheric cast fields, which is necessary for error mechanism de- Research Mesoscale Model (MM5), and the Navy termination, was not available for the GFS and UKMO Coupled Ocean/Atmospheric Mesoscale Prediction models. System (COAMPS). Each of these models has been The definition of “large” 96- and 120-h track errors improved over the years, and with the application of the as being equal to 400 and 500 n mi was based on the consensus forecasting paradigm, the JTWC has been histogram of errors during 2003 and 2004 (Kehoe 2005, able to markedly improve its 72-h forecast accuracy his Figs. 3 and 4). Whereas this definition is somewhat (Jeffries and Fukada 2002). arbitrary, it is consistent with the approach of Carr and Based on these improvements and internal tests of Elsberry (2000a,b) in selecting a value that is twice as 96- and 120-h track forecasts during the 2001 and 2002 large as a reasonable goal for the 96- and 120-h track , the JTWC implemented official 96- and 120-h forecast accuracies. The error needs to be large enough forecasts beginning in May 2003. Only four models pro- that an error mechanism can be confidently established, vide guidance for these longer forecast intervals: and the elimination of Ͼ500 n mi errors at 120 h would NOGAPS, GFS, GFDN, and UKMO. During the 2004 greatly improve the seasonal error statistics and the season, the first two models provided guidance each 6 confidence of the customer in the warning system. h, but the GFDN (UKMO) tracks were only available To maximize the number of 120-h forecast verifica- for 0600 (0000) UTC and 1800 (1200) UTC. Because tions for both NOGAPS and GFDN, the best-track po- the dynamical model forecasts are not available until sitions were manually extended beyond the point that 4–5 h after the synoptic time, the track forecasts are JTWC declares the tropical cyclone to be extratropical. interpolated from the prior 6-h integration (or 12 h for Continuing the positions using mean sea level pressure the GFDN and UKMO models) to the position at the (MSLP) analyses is considered valid since the hazards warning time. As demonstrated by Kehoe (2005, his associated with the wind, , and waves ac- Fig. 2), the JTWC relies heavily on the consensus of companying an do not suddenly these four models for its 120-h forecasts since the cor- diminish at the time a is declared extratropical. relation coefficient between the JTWC and consensus When the MSLP center was predicted by the GFDN errors was 0.943 during 2004. model to have left the model domain, the last location The approach in this study follows that of Carr and inside the domain was used as the predicted position for Elsberry (2000a,b) with the objective being to deter- calculating the errors. This is a conservative estimate mine the 96- and 120-h track error characteristics and because the actual error would be larger than this cal- thus provide guidance to the forecaster as to likely er- culated error. Consequently, the error summaries in roneous forecasts. Jeffries and Fukada (2002) had dem- this study will not match the JTWC summaries and will onstrated that more than three track forecasts were in fact be larger. By following these procedures to maxi- highly desirable for 72-h consensus forecasting to mize verifications of 120-h forecasts, the number of achieve the canceling of random errors, which would cases with large errors increased nearly 28% (24%) for suggest that all four of the 120-h track forecasts are NOGAPS (GFDN) (Table 1). One reason that the needed. A dilemma then exists when one of the four GFDN increase was lower than for NOGAPS was be- models has a highly erroneous 120-h track that may cause 26 of the 134 large-error cases in GFDN (de-

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TABLE 1. Number of cases at 96 and 120 h for 2004. First total In 2004, a total of 354 NOGAPS forecasts to 120 h indicates the number of verifying forecast positions from best- were made for the western North Pacific tropical cy- track data. Second total, in parentheses, includes verifying posi- clones. For GFDN in the same year, 262 forecasts to tions extended beyond declared extratropical to maximize 96- and 120-h model verifications. 120 h were available for the same basin (Table 1). Of those forecasts, 162 (134) cases for NOGAPS (GFDN) No. of No. of 96-h No. of 120-h had a large forecast error at 96 and/or 120 h (to be Model forecasts forecasts described in Table 2). To identify the causes of these NOGAPS 32 367 (422) 277 (354) large errors, both the predicted and verifying analysis GFDN 32 283 (318) 211 (262) fields of the winds and geopotential heights at 200, 500, 700, and 850 mb and the mean sea level pressures were scribed later in Table 2) did not have forecast fields utilized. The geopotential heights from 850 through 500 archived to 120 h, which is a necessity for extending the mb were found to be most beneficial in diagnosing the tracks. cause of the large track forecast errors when midlati- In the identification of these large errors, the GFDN tude synoptic features were affecting the steering cur- had track errors at 0600 and 1800 UTC for which no rent for the tropical cyclone. If vertical ef- archived fields were available from the U.S. Navy Mas- fects were suspected of causing the error, the vector ter Environmental Laboratory. To still incorporate difference in winds between 850 and 500 mb, as well as these forecasts in the summary, if the 0600 UTC (1800 at the 200-mb level, was vital. When the large size of a UTC) error was between 0000 and 1200 UTC (1200 and tropical cyclone was contributing to a beta-effect 0000 UTC) forecasts that also had large errors, and propagation error, the mean sea level pressure fields both of these adjacent forecasts had the same error were found to be most effective in detecting the cause mechanism, then the 0600 or 1800 UTC error was as- of the error. signed the same error mechanism. If the 0600 or 1800 As noted above, the dynamical model 72-h track UTC error had a large error only on one side, and the guidance has been improved since the 1997 season that error values and the track forecasts of the two times was studied by Carr and Elsberry (2000a,b). However, were similar, it too was assigned the same error mecha- Kehoe (2005) documented that an excellent (Ͻ150 n nism. By applying this procedure, the GFDN sample mi), good (Ͻ200 n mi), or fair (Ͻ300 n mi) forecast at included 65 of 72 of the 0600 or 1800 UTC large fore- 72 h does not guarantee even a fair (Ͻ500 n mi) fore- cast errors. A similar procedure for evaluating the off- cast at 120 h. Of the 162 NOGAPS large 96- or 120-h time GFDN error mechanisms also retained 65 of the errors during 2004, 13% occurred when the 72-h error 72 large forecast errors at 0000 and 1200 UTC. If a large was excellent, 25% when the 72-h error was good, and 0600 or 1800 UTC error did not have a large error at 39% occurred when the 72-h error was fair. For the 134 either adjacent time, it was listed as “no fields avail- GFDN large 120-h errors, the corresponding percent- able” but it was included in the error summary. ages of excellent, good, and fair 72-h errors were 5%,

TABLE 2. List of the 96- and 120-h error mechanisms for NOGAPS and GFDN occurring in 2004. The first (second) number listed is the number of times the phenomenon occurred excessively (insufficiently).

Phenomenon name Acronym No. of NOGAPS forecasts No. of GFDN forecasts Large errors due to tropical influences Direct cyclone interaction (tropical) DCI-t 20 (0) 11 (0) Reverse trough formation RTF 0 (0) 3 (0) Beta effect propagation BEP 0 (5) 0 (0) Large errors due to midlatitude influences Direct cyclone interaction (midlatitude) DCI-m 6 (0) 5 (0) Response to vertical wind shear RVS 26 (0) 0 (0) Baroclinic cyclone interaction BCI 6 (0) 0 (0) Midlatitude MCG 6 (53) 28 (46) Midlatitude MCL 12 (0) 2 (0) Midlatitude anticyclogenesis MAG 6 (0) 9 (6) Midlatitude anticyclolysis MAL 2 (4) 0 (0) False alarm 6 4 Tracker error 8 4 Fields not available 2 16 Total of all large-error forecasts 162 134

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21%, and 45%. However, it will be shown in the next verifying analysis fields but the model still predicted a section that the error mechanisms causing large 120-h circulation (false alarm). Since the best track stops errors are similar to those at 72 h, and that these mecha- when no circulation is present, there was no way to nisms just come into play later in the forecasts now with calculate a 120-h error. The last group that could not be these improved models. assigned an error mechanism was 2 (16) cases when no fields were available for NOGAPS (GFDN) (Table 2). 3. Summary of large track error cases For convenience, error mechanisms will henceforth be referred to by their three-letter acronym given in Following Carr and Elsberry (2000a,b), the hypoth- Table 2 with a prefix of E (excessively) or I (insuffi- esis in this analysis is that the large track error is due to ciently), for example, excessive-direct cyclone interac- an improper representation by the model of the tropical tion is abbreviated E-DCI. Each of these large-error cyclone interaction with the environmental flow. The conceptual models in Table 2 is defined and discussed intent of the analysis was therefore to diagnose when in Carr and Elsberry (2000a,b) or Carr and Elsberry and where the model was not properly predicting the (1999). It is emphasized that except for a slight modi- correct interaction that ultimately would steer the fication of one error mechanism, the same error mecha- tropical cyclone. If the intensity or horizontal scale of a nisms as in Carr and Elsberry (2000a,b) lead to large synoptic feature was found to be incorrectly forecast, or track errors at 96 and 120 h. That is, no error mecha- if the timing of a transition between synoptic features nisms were discovered or required. What has changed was found to be incorrect, the track errors were directly is the decrease in the number of tropical-related mecha- related to that incorrect prediction and assigned a spe- nisms and a proportional increase in midlatitude- cific error mechanism. influenced errors at the longer forecast intervals. When For the 146 (110) large-error cases in which an error the numerical models are upgraded, the relative fre- mechanism can be defined for the NOGAPS (GFDN) quency of occurrence of these error mechanisms may model, tropical influences caused 25 or 17% (14 or change. Thus, a detailed examination of the sources of 13%) of the large errors, and midlatitude influences track errors needs to be conducted, preferably with the caused 121 or 83% (96 or 87%) (Table 2). The pre- beta-test sample, or as a minimum after each season. dominance of midlatitude influences for 96- and 120-h In the following sections, conceptual models of the track errors during the 2004 season is a marked devia- most important error mechanisms leading to the large tion from the Carr and Elsberry (2000a,b) studies based track errors will be presented and described along with on the 1997 season. Carr and Elsberry found about the frequency of their occurrence based on the 2004 one-half of the large 72-h errors were associated with typhoon season. tropical influences. Part of the explanation is the im- provement in horizontal resolution and physical pro- cesses in the numerical models since 1997, and perhaps 4. Key tropical-related error mechanism a better representation of the tropical cyclone environ- ment from the assimilation of the satellite observations. Each of the tropical interactions generally occurred A second reason for the predominance of midlati- when the tropical cyclone was south of the subtropical tude influences is that the 4- and 5-day forecasts are ridge axis and the environmental flow had either an more likely to involve an interaction with the midlati- easterly or southerly component or a combination of tude circulations, especially because the forecasts in the two. Because the tropical cyclone is south of the this study (but not in the Carr and Elsberry studies) subtropical ridge axis, its motion is not directly affected were verified against extended best tracks. Thus, the by midlatitude synoptic features. Therefore, the poorly percentages in Table 2 indicate that the proper predic- predicted interaction of the tropical cyclone was typi- tion of amplitude, scales, and translation of midlatitude cally with another warm-core circulation (e.g., mon- synoptic features is a critical component to 96- and soon depression), or with the subtropical ridge. Of the 120-h tropical cyclone track forecasting. tropical-related errors in Table 2, only the direct cy- Not all large track errors could be assigned a concep- clone interaction-tropical (DCI-t) had a large number tual error mechanism. In eight (four) cases for of cases and, thus, will be discussed here. Discussion of NOGAPS (GFDN), the model field accuracy was ac- the reverse trough formation and beta-effect propaga- ceptable, but an undiagnosed problem with the tracking tion error mechanisms in Table 2 is given in Kehoe algorithm caused the large error. In six (four) cases for (2005). NOGAPS (GFDN), the tropical cyclone had decayed The conceptual model of DCI (Carr and Elsberry to the point where it was no longer discernable in the 2000a, their Fig. 2) involves the mutual cyclonic -

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TABLE 3. Cases of model-predicted E-DCI-t in the western North Pacific in 2004. A total of 31 cases of E-DCI-t occurred in five tropical during 2004. Intensity is measured in kt. A probable tropical circulation is indicated by PTC.

No. of cases Synoptic Location Time and date of affected for NOGAPS environment Intensity during Nature of of second TC No. model runs (GFDN) of affected TC interaction (kt) second cyclone cyclone 08W 1800 UTC 8 Jun–0600 UTC 9 Jun 2 S/TE 35–40 07W NNW 10W 1800 UTC 23 Jun–0000 UTC 24 Jun 2 S/TE 35–45 Pre-11W E 19W 1200 UTC 19 Aug–1200 UTC 21 Aug 7 (9) S/TE 45–90 Pre-20W → 20W W 20W 1800 UTC 19 Aug–1200 UTC 21 Aug 8 (2) S/TE 30–65 19W E 31W 0000 UTC 9 Dec 1 S/TE 30 PTC E

tion of two cyclones and a potential merger into one flow of the smaller tropical cyclone as they came in circulation that is usually larger in size than the ana- close proximity. lyzed tropical cyclone. In the analysis of the 2004 fore- a. Frequency and characteristics casts, the track of the larger circulation was found to be less affected than the track of the smaller circulation in In the 2004 sample, 20 NOGAPS and 11 GFDN track E-DCI-t. The smaller circulation usually accelerated forecasts with large errors involved E-DCI-t (Table 3). rapidly as it rotated counterclockwise (CCW) around The range of consecutive integrations affected ranged the larger circulation. Such differences from the 1997 from as few as one by NOGAPS in Tropical Storm cases studied by Carr and Elsberry are likely due to Talas (previously tropical depression 31W) to as many numerical model and observation improvements. as nine by GFDN in (19W). In Direct cyclone interactions in the Tropics during the NOGAPS, other periods of consecutive model- 2004 season were found to always be excessively pre- predicted E-DCI in the Tropics included two occur- dicted by both NOGAPS or GFDN; that is, no insuffi- rences in Typhoon Chanthu (08W), two in Typhoon cient cases are shown in Table 2. As Carr and Elsberry Mindulle (10W), seven in Chaba (19W), and eight in (2000a) summarized, E-DCI errors (tropical or midlati- (20W). Consecutive E-DCI predictions tude) occurred when the tropical cyclone circulation by GFDN in addition to Chaba included two consecu- was forecast to directly interact with an adjacent cy- tive occurrences in Aere. Especially for the longer se- clonic circulation such that the predicted interaction is quences of consecutive erroneous forecasts, the fore- either false or is significantly more vigorous than in caster will have a better opportunity to detect the error. reality. The adjacent cyclonic circulation in the E-DCI-t Although the environmental structure of all tropical would often then become aligned in such a manner that cyclones during the period of E-DCI-t in the Tropics their peripheral formed a reverse-oriented was classified as being in the synoptic pattern/region trough (Kehoe 2005, chapter IIIB.2). The called standard/tropical easterlies (S/TE), the incidence flow in the reverse-oriented would of E-DCI-t then resulted in a shift from S/TE to stan- then become dominant and overpower the influence dard/poleward flow (S/PF). In 17 (55%) of the 31 cases, the two cyclones had on each other during DCI. Thus, the tropical cyclone was less than typhoon strength (64 both cyclones would then track to the northeast. Since kt) during the period of E-DCI-t. it was the E-DCI that lead to the reverse-oriented mon- As in the Carr and Elsberry (2000a) study of the 1997 soon trough error mechanism, E-DCI was the concep- typhoon season in the western North Pacific, every case tual error mechanism assigned. of E-DCI-t in the Tropics was deemed to have falsely The reasons for E-DCI with another real cyclonic occurred. That is, there were no occurrences of a model circulation in the Tropics include (i) too large a hori- exaggeration of an actual DCI in the Tropics. If the zontal extent and associated outer wind strength of the analyses of the 2004 and 1997 seasons are taken to be tropical cyclone and/or another cyclone in the initial representative, the models are biased toward E-DCI-t analysis or forecast; (ii) misplaced tropical cyclone and/ rather than real DCI. The 2004 analysis reinforces the or another cyclone in the initial analysis or forecast, assertion made by Carr and Elsberry (2000a) that if the such that the separation of the two cyclones is smaller forecaster in real time can discern the occurrence of than in reality; and (iii) the 2004 analysis of NOGAPS DCI in a dynamic model, the probability is high that the and GFDN forecasts indicated that an improper inten- event is excessive. The forecaster would therefore be sification of a tropical cyclone (weaker than reality) justified in removing the model track from the consen- caused the larger circulation to dominate the steering sus and forming a selective consensus forecast track

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(the westernmost tropical cyclone) as a much broader and less organized circulation. Despite the similar in- tensity forecasts for Chaba by GFDN, the falsely fore- cast large horizontal scale of Aere leads to the direct interaction between the two. The corresponding NOGAPS forecast (Fig. 2, row 2, column 2) has the eastern tropical cyclone (Chaba) much weaker and it is predicted to rotate CCW around the western tropical cyclone (Aere). The verifying analysis fields (Fig. 2, row 3, column 2) illustrate that Chaba has instead in- tensified and both Chaba and Aere have remained on a west-northwest track. The slowing and southward de- flection in the forecast track for Aere combined with the CCW rotation of Chaba around Aere are evidence that both GFDN and NOGAPS are predicting a mutual interaction of Tropical Cyclones Chaba and Aere. FIG. 1. Interpolated forecast tracks for 19W (Typhoon Chaba) by NOGAPS, GFDN, UKMO, and GFS for the 5-day forecast While the track forecast of Chaba in Fig. 1 may not (symbols each 24 h) beginning 0600 UTC 21 Aug 2004. The bold- conclusively indicate E-DCI is occurring, inspection of face, solid line with circles represents the tropical cyclone best the forecast fields reveals a circulation adjacent to the track. tropical cyclone. The motion of this adjacent circulation viewed in conjunction with the forecast motion of the tropical cyclone should be a clue for the forecaster that that would be more accurate. A case study will outline mutual interaction between the two circulations is oc- how the forecaster can easily identify the key features curring. An additional case of E-DCI-t is discussed by that lead to the occurrence of E-DCI-t in the models. Kehoe (2005). b. Case study Both the NOGAPS and GFDN forecasts of Typhoon 5. Key midlatitude-related error mechanisms Chaba (19W) experienced E-DCI-t problems for a total of 16 model integrations. The E-DCI-t first emerged in After a tropical cyclone begins moving poleward, the the 1800 UTC 19 August 2004 model integration of transition from the Tropics to the midlatitudes is usu- NOGAPS and in the 1200 UTC 19 August 2004 inte- ally complete within 2–3 days. Because the tropical cy- gration of GFDN (Table 3, row 3). The forecast tracks clone is near or poleward of the subtropical ridge, its for 19W (Fig. 1) by both NOGAPS and GFDN are fast, motion is directly impacted by midlatitude circulations and they are easternmost outliers of all the models and, (cyclones, troughs, anticyclones, or ridges). Poorly pre- in hindsight, of the tropical cyclone best track. Because dicted development, dissipation, and/or movement of the GFDN is a regional model embedded in the these midlatitude circulations, which occur indepen- NOGAPS, the lateral boundary conditions for the dently of the tropical cyclone, can have a negative im- GFDN are interpolated from the previous NOGAPS pact on predicted tropical cyclone tracks (Carr and Els- integration. When significant interactions of the tropi- berry 2000b). Therefore, it is no surprise that 83% cal cyclone with the midlatitude flows are predicted by (87%) of all large errors at 96 and 120 h in NOGAPS NOGAPS as in Fig. 1, this may contribute to GFDN (GFDN) during 2004 were due to midlatitude influ- track errors via the lateral boundary contributions. ences (Table 2). Large track error mechanisms due to The NOGAPS and GFDN mean sea level pressure midlatitude influences (Table 2, bottom) include the fields for Chaba in the 0600 UTC 21 August 2004 fore- following: response to vertical wind shear (RVS), baro- cast reveal a classic case of E-DCI. Comparing the fore- clinic cyclone interaction (BCI), midlatitude cyclogen- cast mean sea level pressure fields of GFDN (Fig. 2, esis (MCG), midlatitude cyclolysis (MCL), midlatitude row 1, column 2) to those of the verifying NOGAPS anticyclogenesis (MAG), midlatitude anticyclolysis analysis (Fig. 2, row 3, column 2), the strength (esti- (MAL), and, added in this study, direct cyclone inter- mated from the number of contours) of Chaba (the action-midlatitude (DCI-m). Only those error mecha- eastern tropical cyclone) in the two panels is similar, nisms that occurred frequently will be described here. but Chaba has a much smaller horizontal scale in the More discussion of the midlatitude-related error GFDN fields. At the same time, GFDN portrays Aere mechanisms is found in Kehoe (2005).

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FIG. 2. Mean sea level pressure (mb; contour in- terval, 2 mb) fields for 19W (left) at the initial time and the (right) forecasts (top) by GFDN and (middle) NOGAPS. (bottom) The verifying NOGAPS analysis at 0000 UTC 24 Aug 2004.

a. Direct cyclone interaction-midlatitude (DCI-m) over 2000 n mi, which is twice as large as the largest E-DCI-t errors. Thus, correctly identifying and remov- The conceptual model of E-DCI-m is the same as ing models displaying E-DCI-m would reduce the con- that of E-DCI-t. However, the cause of E-DCI-m is sensus track error. overly deep penetration of an upper-level midlatitude In the 2004 sample, the six occurrences of E-DCI-m cyclonic circulation into the lower troposphere where it in NOGAPS involved only (04W) and can affect the steering of the tropical cyclone. The E- the five in GFDN involved three tropical cyclones: two DCI-m errors normally occur as the tropical cyclone is occurrences in Nida, two in Typhoon Dianmu (09W), moving into the midlatitude , and instead of and one in Typhoon Tingting (11W)(see Table 4, col- moving to the east in these westerlies, the model incor- umn 3). The environmental structure change during rectly predicts the tropical cyclone to rotate CCW each occurrence was from standard/poleward flow to around a large midlatitude cyclone. When this occurred midlatitude/poleward flow as the tropical cyclone was during the 2004 season, the largest 120-h errors were moving through the axis of the subtropical ridge and

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TABLE 4. Cases of model-predicted E-DCI-m in three western North Pacific tropical cyclones in 2004.

TC No. Start time and date of No. of cases for Synoptic environment Intensity during Nature/location affected model runs NOGAPS (GFDN) of affected TC interaction (kt) of second cyclone 04W 0000 UTC 17 May– 6 (2) S/PF → M/PF 130–135 Midlatitude to NNW 0600 UTC 18 May 09W 1800 UTC 23 Jun– (2) S/PF → M/PF 115–120 Midlatitude to NNW 0000 UTC 24 Jun 11W 0000 UTC 29 Jun (1) S/PF → M/PF 80 Midlatitude to NNW interacting with the midlatitude westerlies (Table 4, cyclone is then absorbed into the midlatitude cyclone in column 4). In each occurrence, the tropical cyclone was both models (Fig. 4, rows 1 and 2, column 2). However, a moderate to strong typhoon ranging from 80 to 135 kt the verifying analyses (Fig. 4, row 3, columns 1 and 2) (Table 4, column 5), which is significant because a mod- indicate that the tropical cyclone’s remnants remained erate vertical structure of the tropical cyclone is re- in the westerlies and tracked to the southeast (Fig. 3). quired for it to interact with the overly deep penetra- In summary, every occurrence of E-DCI-m during tion of the midlatitude cyclone into the lower tropo- the 2004 season resulted from a false interaction of a sphere. As in E-DCI-t, no instances of an exaggeration tropical cyclone with a strong midlatitude cyclone to of an actual DCI event by the model were observed. the northwest. While the key indicators of E-DCI-m are Rather, every occurrence was falsely predicted to oc- the same as those of E-DCI-t, an additional feature to cur. Therefore, the forecaster is once again justified in cue the forecaster is a departure from a northeastward omitting the model track displaying E-DCI-m from the track to a northwestward track in midlatitude/poleward consensus. flow. Moreover, there were no occurrences of an exag- In the 0600 UTC 18 May 2004 forecast of Nida geration of an actual DCI event between a tropical cy- (04W), three of the four 120-h model tracks indicated clone and a deep midlatitude cyclone. The forecaster is the tropical cyclone would turn to the northwest once it therefore justified in omitting the model displaying E- was north of 40°N (Fig. 3). Notice that the best track DCI-m from the consensus forecast. has been extended to maximize the 96- and 120-h model verifications beyond the time JTWC declared b. Midlatitude system evolutions (MSEs) the storm to be extratropical. To ensure continuity with The midlatitude system evolution (MSE)-related the posttropical cyclone positions in Fig. 3, the last best- large 120-h errors by NOGAPS (GFDN) contributed track position, at 0600 UTC 21 May 2004, was discarded 52% (65%) of all large errors and, thus, should be a as it was considered to be an unrepresentative extrapo- lated position associated with the rapidly accelerating motion of the upper-level remnants of Nida. In addition to NOGAPS and GFDN, the GFS forecast also pre- dicts a northwest track in the midlatitudes. Whereas the model tracks form a tight cluster up to 72 h, a large spread in the models occurs beyond 72 h. Both the GFDN and NOGAPS models appeared to have a good initialization (not shown) of the tropical cyclone and the deep midlatitude 500-mb trough over eastern Russia and . During the second and third days, the tropical cyclone is interacting with the mid- latitude trough and has accelerated to a position near 38°N, 146°E. However, the forecast positions are slow and west of the verifying position, with some errors greater than 300 n mi (Fig. 3). It becomes apparent in the 90-h forecasts of GFDN and NOGAPS (Fig. 4, rows 1 and 2, column 1) that the tropical cyclone and mid- FIG. 3. As in Fig. 1 but for the interpolated forecast tracks for latitude low are interacting as both models predict a 04W by NOGAPS, GFDN, UKMO, and GFS for the 5-day fore- CCW rotation with the tropical cyclone track turning to cast beginning 0600 UTC 18 May 2004. The extended track veri- the northwest. The 500-mb circulation of the tropical fication is represented by the heavy dashed line and solid circles.

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FIG. 4. Similar to Fig. 2 but for 500-mb streamline and isotach (shaded; beginning at 20 kt; contour interval, 10 kt) forecast fields for 04W by (top) GFDN initiated at 1800 UTC 17 May, (middle) NOGAPS initiated at 0000 UTC 18 May, and (bottom) verifying NOGAPS analyses at the times indicated relative to the operational forecast initial time of 0600 UTC 18 May 2004. First column contains the 90-h forecasts and the second column contains the 114-h forecast for NOGAPS and the 108-h GFDN forecast because the later forecast was not available. Note that the tropical cyclone was approaching the eastern boundary of the GFDN domain. major focus for the forecaster. As described in Carr and sented below (Fig. 5). Before midlatitude cyclogenesis Elsberry (2000b), the fundamental idea of the MSE (MCG) takes place, the tropical cyclone labeled D in error mechanisms is one of changes to the tropical cy- Fig. 5a is south of the subtropical ridge axis and is in a clone steering flow due to development, dissipation, standard/tropical easterlies pattern/region, but then and/or movement of midlatitude circulations (cyclones, tropical cyclone D undergoes a transition to the stan- troughs, anticyclones, ridges) that occur essentially in- dard/poleward flow pattern/region as the developing dependently of the tropical cyclone. midlatitude trough or cyclone breaks the ridge and cre- A generalized conceptual model of MSEs is pre- ates an environment of poleward flow in the vicinity of

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FIG. 5. Schematics of the MSEs affecting the subtropical cells (A) and thus the steering-level flow (arrows) that may lead to large tropical cyclone (labeled B, D, E, and F) track changes with larger or smaller poleward motions. The deepening of the midlatitude trough from (a) to (b) depicts MCG and the reverse order [(b) to (a)] implies MCL. Similarly, the midlatitude anticyclone change poleward of the tropical cyclone from (c) to (d) depicts MAG and the reverse order [(d) to (c)] implies MAL (from Carr and Elsberry 2000b). the tropical cyclone (Fig. 5b). A vigorous MCG event Fig. 5c. The process of midlatitude anticyclolysis could change the direction of the environmental steer- (MAL) is simply the reversed order of MAG depicted ing flow and result in a more poleward rather than in Fig. 5 [i.e., from panel d to panel c; Carr and Elsberry westward track as depicted by the transition from Figs. (2000b)]. 5a and 5b. Similarly, tropical cyclone B north of the If any of the MSEs are predicted to occur to a greater subtropical anticyclone in Fig. 5a could also have a (lesser) extent by the model than in reality such that a track change to a more poleward position. The process significant track error results, then the prefix of exces- of midlatitude cyclolysis (MCL) is simply the reversed sive (E) [insufficient (I)] is assigned to the event. It is order of MCG depicted in Fig. 5 [i.e., from panel b to stressed that the four MSE depictions in Fig. 5 are sim- panel a; see also Carr and Elsberry (2000b)]. ply an idealized representation of such events. These When midlatitude anticyclogenesis (MAG) (Figs. 5c should be considered flexible templates in that they can and 5d) takes place, a tropical cyclone labeled F in Fig. be manipulated to fit all of the complex shapes and 5c that has been moving northward in the standard/ amplitudes of the midlatitude synoptic circulations. In poleward flow southeast of the col in the subtropical addition, these MSE depictions of amplitude changes ridge may be turned more westward as the developing are generalized to also allow for changes in the tropical midlatitude ridge or anticyclone increases the strength cyclone steering flow associated with the translation of of the subtropical ridge poleward of tropical cyclone F. the midlatitude circulations, rather than with amplifi- If MAG builds the ridge sufficiently, then the tropical cation as in Fig. 5. cyclone will undergo a transition to a standard/tropical easterlies or even a standard/equatorward flow pattern/ 1) FREQUENCY AND CHARACTERISTICS region. For example, the change in direction of the en- A more simple combination of the MSE-related er- vironmental steering flow may result in a more west- rors of NOGAPS and GFDN can be made by classify- ward rather than poleward track for tropical cyclone F ing the midlatitude-related errors in Table 2 into two as depicted in the transition from Fig. 5c to Fig. 5d. The groups. The first group comprises the I-MCG, E-MCL, MAG also may cause a track deflection of tropical cy- E-MAG, and I-MAL events, which are all representa- clone E to the north of the subtropical anticyclone in tive of erroneously predicted environmental flows that

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TABLE 5. Two groups of MSE-related errors from Table 2.

No. of No. of NOGAPS GFDN Phenomenon forecasts forecasts Erroneous prediction of environmental 75 57 flow dominated by a ridge Erroneous prediction of environmental 834 flow dominated by a trough Total of all degraded forecasts 83 91 are dominated by a ridge. The second group comprises the E-MCG, I-MCL, I-MAG, and E-MAL events, which are all representative of erroneously predicted environmental flows that are dominated by a trough. With this classification, the MSE events in NOGAPS were one sided in that while NOGAPS was indicating FIG. 6. As in Fig. 1 but for interpolated forecast tracks for 27W the environmental flow of the tropical cyclone would be by NOGAPS, GFDN, UKMO, and GFS for the 5-day forecast dominated by the ridge (Table 5), in reality the domi- beginning 1800 UTC 17 Oct 2004. The extended track verification nant feature was a midlatitude trough. Unfortunately, a is represented by the heavy dashed line. similar conclusion cannot be drawn for the GFDN er- rors as the MSE events in GFDN were two sided. That is, there were a large number of excessive and insuffi- maximum to the northwest of Tokage in the GFDN cient MSE events in GFDN (Table 2). model indicates that the ridge to the northwest of Tok- Because of the two-sided errors in GFDN, no further age is the dominant influence on the environmental conclusions could be drawn as to systematic biases of steering flow, and trough G has moved eastward with- the GFDN model always over- or underpredicting the out “catching” Tokage (Fig. 7, row 1, column 2). The amplitude or translation of the midlatitude features. verifying analysis for the same time illustrates that Tok- Thus, a more in-depth study is needed to uncover the age has been caught in the flow of trough V (Fig. 7, row underlying causes of the combined total of 174 falsely 3, column 2). By 66 h, the interaction of Tokage with predicted MSE events by NOGAPS and GFDN (Table trough V (Fig. 7, row 3, column 2) has led to a rapid 5) as they accounted for many of the large errors at 96 acceleration to the northeast (Fig. 6), so the 120-h and 120 h. One factor to be explored further is the GFDN track error is very large. Thus, the I-MCG error extent to which the GFDN midlatitude-related errors mechanism is assigned to the GFDN forecast because it arise because of improper lateral boundary conditions had underpredicted the amplification of trough G and provided by an inaccurate NOGAPS position. Given thus did not move Tokage into the midlatitude wester- the sparsity of upstream observations over Russia, lies. Although the forecast fields for the UKMO model NOGAPS errors may be introduced in the GFDN even are not available, the similarity of the position in the though the outer domain is 75° latitude ϫ 75° longi- GFDN in Fig. 6 would suggest a similar error for the tude. UKMO model.

2) INSUFFICIENT-MIDLATITUDE CYCLOGENESIS 3) EXCESSIVE-MIDLATITUDE CYCLOLYSIS (I-MCG) (E-MCL) This example will demonstrate for the forecast of This same example will demonstrate how the E-MCL beginning 1800 UTC 17 October 2004 error mechanism can cause a similar forecast track ten- how the most frequently occurring error mechanism, dency as for I-MCG. In this case, the forecast track I-MCG, caused the GFDN track forecast error (Fig. 6). error is due to a translation speed of the midlatitude Notice that the GFDN track is very slow. trough that is too fast, rather than an amplitude change In the 42-h GFDN forecast (Fig. 7, row 1, column 1), as depicted in the conceptual model in Fig. 5. As de- trough G is predicted to be too weak relative to the scribed in section 5b(1), the E-MCL is part of the first verifying trough V (Fig. 7, row 3, column 1). Instead, grouping in Table 5 and although other assignments the GFDN forecast suggests the ridge to the northwest may be appropriate at times, an MCL assignment in this of Tokage will build eastward. By 66 h, the isotach case was considered to best represent the cause of the

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FIG. 7. Similar to Fig. 4 but for 700-mb streamline and isotach forecast fields for 27W by (top) GFDN initiated at 0600 UTC 17 Oct, (middle) NOGAPS initiated at 1200 UTC 17 Oct, and (bottom) verifying NOGAPS analyses for the times indicated relative to the operational forecast initial time of 1800 UTC 17 Oct 2004. First column contains the 42-h forecasts and the second column contains the 66-h forecasts. Troughs in the GFDN, NOGAPS, and verifying analyses are labeled G, N, and V. track error. By 66 h, trough N in the NOGAPS model In this NOGAPS forecast, the trough was somewhat has moved east without “catching” Tokage (Fig. 7, row too deep, but the track error was due to the too fast 2, column 2), while the verifying analysis illustrates that eastward translation of the trough, which caused the Tokage has been caught in the flow of V (Fig. 7, row 3, tropical cyclone to encounter a ridge instead of a trough column 2). Later in the NOGAPS forecast (not shown), during the middle stage of the forecast integration. The the model representation of Tokage does interact with E-MCL error mechanism is therefore assigned to the a second midlatitude trough and does accelerate to the NOGAPS model. Although NOGAPS does predict re- northeast (Fig. 6). curvature and poleward acceleration, it is due to the

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By 54 h, the trough in the GFDN forecast extends farther south and is approaching the coast of China (Fig. 9, top left), whereas the trough in the verifying analysis does not have such a southern extent (Fig. 9, bottom left). By contrast, the NOGAPS forecast that had an excellent track forecast suggests that Nida (04W) is only beginning to interact with a major mid- latitude trough to the northwest. By 90 h, the GFDN forecast has merged the tropical cyclone with the deeper, faster-moving trough (Fig. 9, top right), while the verifying analysis indicates the trough is farther to the west, and the tropical cyclone and trough are still separate entities (Fig. 9, bottom right). The NOGAPS forecast (Fig. 9, middle right) has a much better prediction of the interaction between Nida (04W) and the midlatitude trough, so it is not surprising that the NOGAPS 120-h track forecast is excellent (Fig. 8). While it is clear in this retrospective study that the

FIG. 8. As in Fig. 1 but for interpolated forecast tracks for 04W GFDN error is due to E-MCG, in real time the fore- by NOGAPS, GFDN, UKMO, and GFS for the 5-day forecast caster may have suspected that the NOGAPS model beginning 1800 UTC 15 May 2004. had an insufficient MCG error, which happens fre- quently (Table 2). The fact that the UKMO also pre- incorrect interaction with the second midlatitude dicted a similar 120-h position as the GFDN might give trough (not shown). support to that scenario, although the GFS 120-h fore- A key result for the forecaster is that both I-MCG cast position in Fig. 8 similarly might support the and E-MCL contributed to numerous forecast degra- NOGAPS forecast. In the SAFA framework, the rec- dations in both GFDN and NOGAPS forecasts. They ommendation would be to accept the consensus of the occurred so frequently that it would behoove the fore- four model tracks if the forecaster could not confidently caster to investigate how the model in question is rep- establish that the GFDN (and not the NOGAPS) was resenting the midlatitude trough compared to the other likely to be in error. models when the NOGAPS and/or GFDN track fore- cast is an outlier. It is also important for the forecaster 5) EXCESSIVE-MIDLATITUDE ANTICYCLOGENESIS to recall that once the error appears, it will likely afflict (E-MAG) the model in question for several successive integra- The E-MAG error mechanism was the third most tions. Thus, the forecaster should monitor the track frequently occurring midlatitude error (Table 2). It af- trend display. fected nine forecasts by the GFDN for five tropical cyclones during the 2004 season, while six forecasts in 4) EXCESSIVE-MIDLATITUDE CYCLOGENESIS one tropical cyclone had this error in the NOGAPS. (E-MCG) Because the GFDN is more susceptible to E-MAG, a The E-MCG error mechanism was the second most case study of E-MAG occurring in GFDN will be illus- frequently occurring error mechanism during the 2004 trated. The track forecasts for 0600 UTC 2 September season and affected 28 (6) GFDN (NOGAPS) forecasts 2004 for Tropical Cyclone Songda (22W) indicate that (Table 2). Since the GFDN has many more E-MCG the GFDN and UKMO tracks are outliers to the far left cases, these GFDN errors are not likely due to errone- of the other 120-h tracks (Fig. 10). Whereas both the ous lateral boundary conditions provided by the NOGAPS and GFS correctly predict a recurvature- NOGAPS model in these cases. Because the GFDN type track, both fail to predict the rapid acceleration to model was more susceptible to E-MCG, a case study of the northeast of Songda (22W). E-MCG in GFDN will be illustrated. The forecast By 42 h (not shown), the GFDN has predicted a tracks from 1800 UTC 15 May 2004 for Nida (04W) midlatitude anticyclone to develop over the Yellow indicate that Nida is predicted to translate faster in both Sea, but this is not substantiated in the verifying analy- the GFDN and UKMO outputs than in those of sis. The NOGAPS forecast (not shown) has a much NOGAPS and GFS (Fig. 8). weaker ridge directly to the north of Songda, but the

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FIG. 9. As in Fig. 4 but for 500-mb streamline and isotach forecast fields for 04W by (top) GFDN initiated at 0600 UTC 15 May, (middle) NOGAPS initiated at 1200 UTC 15 May, and (bottom) verifying NOGAPS analyses for the times indicated relative to the operational forecast initial time of 1800 UTC 15 May 2004. First column contains the 54-h forecasts and the second column contains the 90-h forecasts. ridge to the northeast has been predicted to extend latitude anticyclone is a weak ridge at 700 mb and does westward too far. Consequently, the NOGAPS track is not add appreciably to the strength of the subtropical also too far westward (Fig. 10). ridge. Thus, Songda actually undergoes a transition to a By 54 h, the GFDN predicts this midlatitude anticy- standard/poleward flow pattern/region because the clone will translate to the northeast and merge with the dominant steering current is the subtropical ridge to the subtropical ridge to form a substantial ridge to the east-northeast of the tropical cyclone (Fig. 11, bottom north of Songda (Fig. 11, top left which is consistent left). By 114 h (Fig. 11, top right), the earlier westward with the predicted westward track. The verifying analy- and equatorward error in the track forecast then leaves sis (Fig. 11, bottom left) reveals instead that this mid- Songda too far south and west so that no interaction

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selective consensus track forecast by correctly rejecting the erroneous cluster containing GFDN to create an improved selective consensus. The forecaster can then potentially improve upon the selective consensus by re- alizing that the remaining models have a one-sided ten- dency to falsely predict an environment that is domi- nated by a ridge (e.g., NOGAPS does not move pole- ward fast enough). This requires examination of the forecast fields with thorough knowledge of the concep- tual model error mechanisms and their frequency.

c. Excessive response to vertical wind shear (E-RVS) In the RVS error conceptual model introduced by Carr and Elsberry (2000b, their Fig. 3), the basic as- FIG. 10. As in Fig. 1 but for interpolated forecast tracks for 22W sumption is that a significant difference exists in the by NOGAPS, GFDN, UKMO, and GFS for the 5-day forecast vertical depth between the actual and model-predicted beginning 0600 UTC 2 Sep 2004. tropical cyclone in the presence of a vertically sheared environmental flow. A deeper (less deep) vertical ex- with the passing midlatitude trough is predicted by tent of the tropical cyclone causes the model-predicted GFDN. Instead, the dominant influence on the GFDN tropical cyclone to have a faster (slower) translation forecast track is another strong midlatitude anticyclone speed (especially in the midlatitude westerlies) than that is not substantiated by the verifying analysis (Fig. that of the actual tropical cyclone. Typically, the differ- 12, bottom right). Whereas the NOGAPS forecast has ence in vertical structure between the model-depicted a somewhat better depiction of the midlatitude circula- and actual tropical cyclones tends to grow with increas- tion to the north of Songda, its prior westward and ing forecast interval, which accentuates the differences southward track error does not put Songda in the in translation speeds and, thus, the track errors. proper position to interact strongly with the midlatitude Excessive-RVS (E-RVS) is said to be occurring when trough. the model-depicted tropical cyclone is too shallow and A forecaster examining the model track forecasts of excessively tilted downstream. When this occurs, the Fig. 10 in real time would see two clusters. The GFDN upper (and possibly middle) vortex is sheared from the and UKMO models form a cluster that implies Songda lower vortex that is then advected by the low-level en- will track westward. However, the NOGAPS and GFS vironmental flow. Steering by only the low-level flow predict that Songda will turn poleward after 72 h. Be- will then cause a slow bias compared to steering by cause 57 GFDN forecasts during the 2004 season were stronger upper-level flow. degraded by an erroneous prediction of environmental Carr and Elsberry (2000b) suggested the use of sea flow dominated by a ridge (Table 5), the expectation level pressure forecasts to identify E-RVS. It was found might be that the GFDN model is in error. By contrast, in this study that geopotential heights (not available to NOGAPS forecasts during 2004 were degraded by Carr and Elsberry in SAFA) at 850, 700, and 500 mb overly weak troughs (53 occurrences of I-MCG com- were also a useful tool. Those tropical cyclones that had pared to 6 occurrences of E-MCG in Table 2), which less deep (deeper) vertical structures were found to results in erroneous track forecasts that remain in the have fewer (more) concentric geopotential isopleths at Tropics too long. Since NOGAPS rarely predicts a higher isobaric levels. That is, fewer (more) closed geo- track that is too far poleward when an MSE scenario is potential isopleths existed at 500 and 700 mb for a less involved, the forecaster should expect that the deep (deeper) tropical cyclone. NOGAPS forecast is probably a more reliable forecast The RVS events during the 2004 season were all ex- in this case. cessive and occurred only in NOGAPS (Table 2). Although this forecast scenario is difficult in that the These E-RVS events were responsible for 26 degraded actual tropical cyclone track is to the east of all four forecasts in five tropical cyclones during the 2004 sea- model predictions, this bifurcation scenario between a son. In all cases, the tropical cyclone was in the stan- recurvature track cluster and a westward track cluster is dard/poleward flow or midlatitude/poleward flow with one in which the forecaster can add value over a non- an approaching upper-level midlatitude trough that im-

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FIG. 11. As in Fig. 7 but for 700-mb streamline and isotach forecast fields for 22W by (top) GFDN initiated at 1800 UTC 1 Sep, (middle) NOGAPS initiated at 0000 UTC 2 Sep, and (bottom) verifying NOGAPS analyses for the times indicated relative to the operational forecast initiated at 0600 UTC 2 Sep 2004. First column contains the 54-h forecasts and the second column contains the 114-h forecasts. posed vertical wind shear over the tropical cyclone. A The track forecasts for Meari (25W) from 0600 UTC key indication [not included in the Carr and Elsberry 26 September 2004 in Fig. 12 have a large spread about (2000b) description] that E-RVS was occurring was the consensus mean (not shown) with longer-range when the tropical cyclone track suddenly switched from forecast tracks that are highly diverse. The NOGAPS a poleward to an equatorward track, which suggested track forecast has a sudden reversal from poleward to that the upper vortex was being decoupled from the equatorward flow near 31°N, 131°E, which may indi- lower vortex. Since the lower vortex was only being cate E-RVS is a possible error. Whereas the GFDN and steered by the low-level environmental flow, the model GFS models also have a reversal of track directions, predicted a slower and more equatorward track. they have a more arcing track. It is suspected that the

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6. Summary and conclusions

This study has extended the large track error concep- tual models of Carr and Elsberry (2000a,b) to 96- and 120-h forecasts by the NOGAPS and GFDN models during the 2004 western North Pacific season. Large track errors are defined to be 400 n mi at 96 h and 500 n mi at 120 h. This study maximized the number of 120-h forecast verifications for both NOGAPS and GFDN by manually extending the best-track positions beyond the point of extratropical declaration using mean sea level pressure analyses. By following these procedures, an increase of nearly 28% (24%) in the number of cases with large 120-h forecast errors was realized for NOGAPS (GFDN). An important conclusion is that all of these large- FIG. 12. As in Fig. 1 but for interpolated forecast tracks for 25W error cases not associated with false alarms, tracker er- by NOGAPS, GFDN, UKMO, and GFS for the forecast begin- rors, or field nonavailability could be attributed to the ning 0600 UTC 26 Sep 2004. The extended track verification is models not properly representing the physical pro- represented by the heavy dashed line. cesses known to control tropical cyclone motion, which were classified in a series of conceptual models by Carr and Elsberry for either tropical-related or midlatitude- UKMO forecast track was also affected by E-RVS, but related mechanisms. In contrast to the large 72-h errors no forecast fields were available to investigate further. during the 1997 season studied by Carr and Elsberry, a Comparison with the verifying analysis (Fig. 13, row 2, smaller fraction of the 96- and 120-h errors are tropical column 1) confirms that the NOGAPS forecast (Fig. 13, related, with only 17% (13%) for the NOGAPS row 1, column 1) has an even weaker 700-mb circula- (GFDN) forecasts. However, the direct cyclone inter- tion and smaller horizontal scale. By 90 h, only one action error mechanism continues to be the most fre- closed 700-mb isopleth is predicted, and it lags behind quent contributor to large errors, and always in the the midlatitude trough (Fig. 13, row 1, column 2). In sense of being excessively predicted in the forecasts. addition, the 500-mb forecast (not shown) indicates the For those large-error cases in which an error mecha- upper and lower vortices have separated with the 500- nism could be established, midlatitude influences mb vortex farther to the northeast, which is another caused 83% (87%) of the NOGAPS (GFDN) errors. indicator of vertical wind shear (Carr and Elsberry The most common midlatitude-related errors in the 2000b). By contrast, the verifying 700-mb analysis (Fig. NOGAPS tracks arise from an erroneous prediction of 13, row 2, column 2) has Meari embedded in the trough the environmental flow dominated by a ridge in the and with a much stronger circulation. midlatitudes. Errors in the GFDN tracks are caused by Several clues that a tropical cyclone moving pole- both ridge-dominated and trough-dominated environ- ward is experiencing vertical wind shear are described mental flows in the midlatitudes. Case studies illustrat- above. The NOGAPS (and likely other global models) ing the key error mechanisms indicate that the proper are susceptible to vertical wind shear because the resil- prediction of the amplitude, scales, and transition of iency of the actual vortex cannot be simulated on a midlatitude synoptic features is a critical component of coarse grid. If the NOGAPS model predicts a slowing 120-h tropical cyclone track forecasting. The NOGAPS of the motion, or a turn equatorward as in this example, and GFDN models had significant problems both in the the E-RVS mechanism should be expected. The proper development and movement of midlatitude troughs. identification and removal of the NOGAPS track fore- Now that some of the four longer-range forecasts are cast displaying E-RVS would normally provide a selec- available each 6 h, the tendency for repeated error tive consensus that is more accurate than the average of mechanisms of the same type is more obvious, and the all four model tracks. However, in the 0600 UTC 26 forecaster may be able to detect the error by examining September 2004 forecast for Tropical Cyclone Meari, the track trends over 36–48 h. all four forecast tracks (Fig. 12) are outliers and there- As expected, a global model such as NOGAPS is fore eliminating just the NOGAPS track would go susceptible to vertical wind shear causing excessive de- against the rules set forth in SAFA. cay of the tropical cyclone vortex, and this is an impor-

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FIG. 13. Forecasts of 700-mb geopotential height (m) fields for 25W by (top) NOGAPS initiated at 0000 UTC 26 Sep and (bottom) verifying NOGAPS analyses at the times indicated relative to the operational forecast initial time of 0600 UTC 26 Sep 2004. First column contains the 66-h forecasts and the second column contains the 90-h forecasts. tant factor if the cyclone moves toward the midlatitudes 2000). However, removing even one of the four 120-h during the 120-h forecast. Both the forecast wind fields model tracks that compose the 96- and 120-h consen- and geopotential fields provide evidence that the vortex suses does raise concerns about the accuracy of the is being excessively decoupled during these vertical remaining three-model consensus. Jeffries and Fukada wind shear scenarios. (2002) noted that the consensus forecasts were more The hypothesis in this study is that the proper iden- accurate if more than three track forecasts were avail- tification and removal of any model track forecast dis- able. Thus, a dilemma occurs when one of the four playing one of these conceptual error mechanisms 120-h models has a highly erroneous track, since having could provide a selective consensus that is more accu- only three model tracks may cause the consensus to be rate than a nonselective consensus of all four longer- degraded. Therefore, it remains to be demonstrated range forecasts. As outlined in Carr and Elsberry that an improved consensus track forecast can be (2000a,b), this would require the availability and the achieved by eliminating the positively identified erro- capability to display the analysis and forecast fields neous track through the conceptual error models out- from the model. Application of the conceptual models lined in this study. Adding more skillful longer-range presented here requires either the streamlines/isotachs, track forecast models to the consensus will help if their the sea level pressures, or the geopotential heights. The error characteristics are also known. ability to determine conclusively the existence of these likely erroneous tracks in real time is not tested in this Acknowledgments. This work is part of the M.S. the- retrospective study of known large errors. sis of R. M. Kehoe (Capt., USAF), who was supported An ability to identify confidently these error mecha- by the Air Force Institute of Technology. M. A. Boothe nisms and thereby eliminate likely erroneous tracks and R. L. Elsberry were supported by the Office of from the consensus has been shown to improve the Naval Research’s Marine Division. The accuracy of 72-h track forecasts (Elsberry and Carr datasets were provided by the Joint Typhoon Warning

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Center in . The manuscript was expertly pre- ——, ——, and J. E. Peak, 2001: Beta test of the systematic ap- pared by Mrs. Penny Jones. proach expert system prototype as a tropical cyclone track forecasting aid. Wea. Forecasting, 16, 355–368. Elsberry, R. L., and L. E. Carr III, 2000: Consensus of dynamical REFERENCES tropical cyclone track forecasts—Error versus spread. Mon. Wea. Rev., 128, 4131–4138. Carr, L. E., III, and R. L. Elsberry, 1999: Systematic and inte- Goerss, J., 2000: Tropical cyclone track forecasts using an en- grated approach to tropical cyclone track forecasting. Part semble of dynamical models. Mon. Wea. Rev., 128, 1187– III: Traits knowledge base for JTWC track forecast models in 1193. the western North Pacific. Tech. Rep. NPS-MR-99-002, Na- Jeffries, R. A., and E. J. Fukada, 2002: Consensus approach to val Postgraduate School, Monterey, CA, 227 pp. track forecasting. Extended Abstracts, Fifth Int. Workshop on ——, and ——, 2000a: Dynamical tropical cyclone track forecast Tropical Cyclones, Cairns, Australia, World Meteorological errors. Part I: Tropical region errors. Wea. Forecasting, 15, Organization, TP3.2. 641–661. Kehoe, R. M., 2005: Characteristic errors in 120-h tropical cyclone ——, and ——, 2000b: Dynamical tropical cyclone track forecast track forecasts in the western North Pacific. M.S. thesis, Na- errors. Part II: Midlatitude circulation influences. Wea. Fore- val Postgraduate School, 111 pp. [Available online at http:// casting, 15, 662–681. theses.nps.navy.mil/05Mar_Kehoe.pdf.]

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