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Dynamical Tropical Cyclone Track Forecast Errors. Part I: Tropical Region Error Sources

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Dynamical Tropical Cyclone Track Forecast Errors. Part I: Tropical Region Error Sources VOLUME 15 WEATHER AND FORECASTING DECEMBER 2000 Dynamical Tropical Cyclone Track Forecast Errors. Part I: Tropical Region Error Sources LESTER E. CARR III AND RUSSELL L. ELSBERRY Naval Postgraduate School, Monterey, California (Manuscript received 28 January 2000, in ®nal form 16 June 2000) ABSTRACT All highly erroneous (.300 n mi or 555 km at 72 h) Navy Operational Global Atmospheric Prediction System (NOGAPS) and U.S. Navy version of the Geophysical Fluid Dynamics Laboratory model (GFDN) tropical cyclone track forecasts in the western North Paci®c during 1997 are examined. Responsible error mechanisms are described by conceptual models that are all related to known tropical cyclone motion processes that are being misrepresented in the dynamical models. Error mechanisms that predominantly occur while the tropical cyclone is still in the Tropics are described in this paper, and those errors that are more related to midlatitude circulations are addressed in a companion paper. Of the 69 NOGAPS large-error cases, 39 were attributed to excessive direct cyclone interaction (E-DCI), 12 cases of excessive ridge modi®cation by the tropical cyclone (E-RMT), and 10 cases of excessive reverse trough formation (E-RTF). Of the 50 GFDN large-error cases, 31 were E-DCI, and only two E-RMT and two E-RTF cases were found, but 9 cases involving a single cyclone were attributed to excessive tropical cyclone size (E-TCS). Characteristics and symptoms in the forecast tracks and model ®elds that accompany these frequently occurring error mechanisms are documented and illustrative case studies are presented. When a sudden deviation from previous track guidance or a track outlier from the other dynamical model guidance appears, the forecaster should diagnose whether this is an error, or is indicative of a real track change. If the conceptual models of large-error mechanisms proposed from this retrospective study can be applied in real time, track forecasting will be improved. 1. Introduction track forecast guidance for the forecaster has been achieved since 1994. First, the Geophysical Fluid Dy- The long-range objective of the systematic and in- namics Laboratory (GFDL) model was demonstrated to tegrated approach to tropical cyclone (TC) track fore- provide superior guidance over the other statistical and casting (hereafter the systematic approach) of Carr and empirical techniques (Kurihara et al. 1995). That re- Elsberry (1994) is to assist the forecaster achieve sig- ni®cant improvements in of®cial track forecasts. When gional model was subsequently modi®ed to use the ini- the systematic approach was developed, the TC fore- tial conditions and lateral boundary conditions from the casters relied primarily on statistical and empirical track Navy Operational Global Atmospheric Prediction Sys- guidance (Elsberry 1995). Although dynamical model tem (NOGAPS) for provision of track forecast guidance guidance was available, nearly all of the models had in the western North Paci®c, and is referred to as the systematic errors (e.g., a marked poleward bias for low- GFDN model. Both the NOGAPS and the U.K. Met. latitude TCs moving westward). In the original system- Of®ce (UKMO) global models were signi®cantly im- atic approach concept, the plan had been to apply sta- proved in October 1994 by the introduction of improved tistical corrections for different synoptic patterns to cor- TC synthetic observations (Goerss and Jeffries 1994; rect for systematic errors in the dynamical model guid- Heming et al. 1995). Various improvements were intro- ance. A reduction in the systematic errors of the duced to the Japan Meteorological Agency Global Spec- dynamical models used by the forecaster at that time tral Model (JGSM) and Typhoon Model (JTYM) prior would presumably have led to a reduction in the annual to the 1997 typhoon season. Thus, three global (NO- average track errors. GAPS, UKMO, and JGSM) and two regional (GFDN A major gain in the accuracy of the dynamical TC and JTYM) tracks are typically available for western North Paci®c TCs at the synoptic (0000 and 1200 UTC) and off-synoptic (0600 and 1800 UTC) times, respec- tively. Corresponding author address: L. E. Carr III, Department of Me- One recent improvement in the dynamical model teorology, Code MR/Cr, 589 Dyer Rd., Room 254, Monterey, CA 93943-5114. guidance has been the reduction in the systematic errors. E-mail: [email protected] Although Elsberry et al. (1999) have shown it is possible 641 Unauthenticated | Downloaded 09/28/21 01:18 AM UTC 642 WEATHER AND FORECASTING VOLUME 15 caster detect when the dynamical guidance is likely to be erroneous and thus should be rejected during prepa- ration of the warning. Elsberry and Carr (2000) have examined the track forecast errors as a function of the spread (maximum distance to consensus centroid) among these ®ve dynamical models. Their ®ve-member consen- sus approach is an extension of the Goerss (2000) three- global-model or two-regional-model consensus technique at the synoptic and off-synoptic times, respectively. Goerss demonstrated that his consensus forecasts were either the best or the second-best guidance in about 70% of the forecasts. As might be expected based on expe- rience with ensemble prediction systems, an average of ®ve independent dynamical models with only small sys- tematic errors provides an improvement over the three- member or two-member consensus. Although Elsberry and Carr (2000) documented that a small spread (,300 FIG. 1. Frequency of occurrence of 72-h track errors for the NO- n mi, or 555 km) along the ®ve model tracks often im- GAPS (solid) and GFDN (open) forecasts of western North Paci®c plied a small consensus forecast error, in a sizeable frac- TCs during 1997. tion of the small spread cases the consensus error ex- ceeded 300 n mi. Another important result was that a to apply a statistical adjustment to improve the NO- large spread among the ®ve model tracks did not nec- GAPS tracks at 12±36 h, no statistically signi®cant im- essarily imply a large consensus track error, because the provement was achieved beyond 36 h. With the reduc- errors of two (or more) of the models may be compen- tion in systematic errors, old rules about the perfor- sating. Elsberry and Carr (2000) did demonstrate that a mance of the models as a function of initial latitude or large spread implies that at least one of the dynamical track orientation are not as valid. As this research has models will have an error larger than that spread. They found [see examples in Elsberry and Carr (2000) and propose a selective consensus approach in which the Carr and Elsberry (2000)], the same dynamical model model guidance suspected to have a 72-h error greater that was good in one case (e.g., recurvature) can be the than 300 n mi is ®rst eliminated prior to calculating the worst in another essentially identical case. Thus, the average of the remaining four model tracks. They dem- original systematic approach concept of applying sta- onstrate that simply omitting the worst of the ®ve dy- tistical adjustments to the dynamical model tracks need- namical model tracks would indeed improve the selective ed to be changed. consensus over the nonselective consensus. Although the dynamical models typically have skill This paper describes the characteristics and symptoms relative to a climatology and persistence forecast, the in the forecast tracks and model ®elds that a forecaster dynamical models occasionally have large errors. For might use to detect likely cases of large (300 n mi at 72 example, the distribution of 72-h NOGAPS and GFDN h) dynamical TC track errors. Conceptual models and track forecast errors during the 1997 western North Pa- case studies are presented in this paper for large-error ci®c season are shown in Fig. 1. Notice these two model scenarios that are most common when the TC is still in error distributions are skewed toward the larger errors. the Tropics, that is, equatorward of the subtropical ridge. Even though the largest NOGAPS error (1226 n mi or In a companion paper (Carr and Elsberry 2000), those 2268 km) is signi®cantly larger than for the GFDN mod- conceptual models that apply more frequently when the el (931 n mi or 1722 km), the percentages of 72-h fore- TC is poleward of the subtropical ridge will be described. cast errors exceeding 300 n mi (555 km) are very similar As demonstrated by Elsberry and Carr (2000), a suc- (33.1% for NOGAPS and 34.5% for GFDN). cessful application of these conceptual models by the Thus, the new systematic approach focus is the re- forecaster would reduce the TC track forecast errors. duction in the number of of®cial track forecasts with large errors. Although not numerous during most sea- 2. Methodology sons, these forecast ``busts'' provide such poor guidance to the customer that con®dence is degraded. If these The approach has been to identify and analyze cases large errors could be eliminated, the warnings would be during 1997 of large (300 n mi or 555 km at 72 h) track more consistent in time. Then the areas warned would errors by the NOGAPS or GFDN models (Fig. 1). Of be reduced so that customers in adjacent areas would the ®ve dynamical models mentioned above, only for not unnecessarily make preparations, and those custom- these two models were the analyses and forecast ®elds ers in the warned areas could more con®dently make available to search for explanations of the large errors. the appropriate preparations. Only the tracks of the other three models were available The basic motivation for this work is to help the fore- (®elds for JGSM and the UKMO model have recently Unauthenticated | Downloaded 09/28/21 01:18 AM UTC DECEMBER 2000 CARR AND ELSBERRY 643 become available and appear to have similar character- In the following sections, conceptual models of the istics when large errors occurred; these evaluations will mechanisms leading to the large track errors will be be published separately).
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