Tropical Cyclone Track Prediction Research Articles

Typhoon Ensemble Prediction System Developed at the Japan Meteorological Agency

Abstract The Japan Meteorological Agency (JMA) Typhoon Ensemble Prediction System (TEPS) and its performance are described. In February 2008, JMA started an operation of TEPS that was designed for providing skillful tropical cyclone (TC) track predictions in both deterministic and probabilistic ways. TEPS consists of 1 nonperturbed prediction and 10 perturbed predictions based on the lower-resolution version (TL319L60) of the JMA Global Spectral Model (GSM; TL959L60) and a global analysis for JMA/GSM. A singular vector method is employed to create initial perturbations. Focusing on TCs in the western North Pacific Ocean and the South China Sea (0°–60°N, 100°E–180°), TEPS runs 4 times a day, initiated at 0000, 0600, 1200, and 1800 UTC with a prediction range of 132 h. The verifications of TEPS during the quasi-operational period from May to December 2007 indicate that the ensemble mean track predictions statistically have better performance as compared with the control (nonperturbed) predictions: the error reduction in the 5-day predictions is 40 km on average. Moreover, it is found that the ensemble spread of tracks is an indicator of position error, indicating that TEPS will be useful in presenting confidence information on TC track predictions. For 2008 when TEPS was in operational use, however, it was also found that the ensemble mean was significantly worse than the deterministic model (JMA/GSM) out to 84 h.

The Sanders Barotropic Tropical Cyclone Track Prediction Model (SANBAR)

Abstract Sanders designed a barotropic tropical cyclone (TC) track prediction model for the North Atlantic TC basin that became known as the Sanders barotropic (SANBAR) model. It predicted the streamfunction of the deeplayer mean winds (tropical circulation vertically averaged from 1000 to 100 hPa) that represents the vertically averaged tropical circulations. Originally, the wind input for the operational objective analysis (OA) consisted of winds measured by radiosondes and 44 bogus winds provided by analysis at the National Hurricane Center (NHC), which corresponded to the vertically averaged flow over sparsely observed tropical, subtropical, and midlatitude oceanic regions. The model covered a fixed regional area and had a grid size of ~ 154 km. It estimated the initial storm motion solely on the basis of the large-scale flow from the OA, not taking into account the observed storm motion. During 1970, the SANBAR model became the first dynamical TC track model to be run operationally at NHC. Track forecasts of SANBAR were verified from the 1971 TC season when track model verifications began at NHC until its retirement after the 1989 Atlantic TC season. The average annual SANBAR forecast track errors were verified relative to Climatology and Persistence (CLIPER), the standard no-skill track forecast. Comparison with CLIPER determines the skill of track forecast methods. Verifications are presented for two different versions of the SANBAR model system used operationally during 1973–84 and 1985–89. In homogeneous comparisons (i.e., includes only forecasts for the same initial times) for the former period, SANBAR's track forecasts were slightly better than CLIPER at 24–48-h forecast intervals; however, from 1985 to 1989 the average SANBAR track forecast errors from 24–72 h were ~10% more skillful than homogeneous CLIPER track forecasts.

Weighted Position and Motion Vector Consensus of Tropical Cyclone Track Prediction in the Western North Pacific

Abstract Two approaches are developed and tested to improve the unweighted position consensus for 96-, 108-, and 120-h tropical cyclone track guidance in the western North Pacific. A weighted position guidance technique uses a weighting factor for each model that is inversely proportional to how far the 60-, 66-, and 72-h positions of that model are from the corresponding positions of the 11-member position consensus. The weighted position consensus of 96-, 108-, and 120-h track errors for a sample of 24 storms during the 2006 season are consistently smaller than for the unweighted position consensus. In the second approach, a weighted motion vector consensus is developed that uses the same weighting factors as in the weighted position consensus, except that the weights are applied to 12-h motion vectors between 84 and 120 h. This weighted motion vector consensus has substantially smaller errors than the unweighted position consensus, and results in smoother tracks when one or more of the model tracks drops out of the consensus. It is proposed that the weighted motion vector consensus would provide improved guidance for the 96-, 108-, and 120-h tropical cyclone track forecasts.

The performance of the new tropical cyclone track prediction system of the China National Meteorological Center

The global spectral model (GSM) at T213 horizontal resolution with 31 vertical levels has been used operationally in the China National Meteorological Center (CNMC) since 2002. The results show that the GSM is skillful in predicting large-scale circulations because of both the high spatial resolution and the improved model physics. However, because of the low skill in predicting the tropical cyclone (TC) genesis, the model has low skill in predicting TC tracks. In order to improve the prediction skill for TC tracks, an asymmetric bogus vortex scheme was implemented in the CNMCs operational GSM, and has being run in an experimental mode in 2003 and in an operational mode since 2004.

Impact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.

Current status of tropical cyclone track prediction techniques and forecast errors

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 Thanks to advanced data assimilation techniques, continuous model development, higher resolutions, and vortex specification, there has been considerable progress in the reduction of global tropical cyclone forecast errors during past few decades. It has been observed that world-wide rate of reduction of forecast errors was of the order of 1%-2% per year for all time horizons, with most rapid improvement at longer durations (beyond 48 hours). While other basins like Atlantic and Pacific oceans reported greater rate of decline of these errors due to various factors, the trend has been quite modest for Indian region. The only factor responsible for reduction of errors in the region was the greater use of synthetic vortex by operational NWP centres like India Meteorological Department (IMD) and National Centre for Medium Range Weather Forecasting (NCMRWF) in their Regional & Global model analyses. The current emphasis of international tropical cyclone research is to achieve greater accuracy of TC track prediction, especially in the short range, by maximizing the use of non-conventional data, meso-scale analysis, use of synthetic data for vortex specification, and the performance of physical parameterization at higher model resolution. The current research and operational emphasis of the ongoing Hurricane WRF project for land falling cyclones, is expected to benefit the Indian region in the years to come. Nevertheless, the Indian region needs to assign higher priority to the greater availability of conventional & non-conventional data and use of advanced data assimilation technique for model analysis besides its concerted efforts on model developments.

An application of the adjoint method to a statistical-dynamical tropical-cyclone prediction model (SD-90) II: Real tropical cyclone cases

In the first paper in this series, a variational data assimilation of ideal tropical cyclone (TC) tracks was performed for the statistical-dynamical prediction model SD-90 by the adjoint method, and a prediction of TC tracks was made with good accuracy for tracks containing no sharp turns. In the present paper, the cases of real TC tracks are studied. Due to the complexity of TC motion, attention is paid to the diagnostic research of TC motion. First, five TC tracks are studied. Using the data of each entire TC track, by the adjoint method, five TC tracks are fitted well, and the forces acting on the TCs are retrieved. For a given TC, the distribution of the resultant of the retrieved force and Coriolis force well matches the corresponding TC track, i.e., when a TC turns, the resultant of the retrieved force and Coriolis force acts as a centripetal force, which means that the TC indeed moves like a particle; in particular, for TC 9911, the clockwise looping motion is also fitted well. And the distribution of the resultant appears to be periodic in some cases. Then, the present method is carried out for a portion of the track data for TC 9804, which indicates that when the amount of data for a TC track is sufficient, the algorithm is stable. And finally, the same algorithm is implemented for TCs with a double-eyewall structure, namely Bilis (2000) and Winnie (1997), and the results prove the applicability of the algorithm to TCs with complicated mesoscale structures if the TC track data are obtained every three hours.

Initialisation using high spatial, temporal and spectral resolution satellite observations

Recent advances in numerical weather prediction and data assimilation, combined with the availability of high spatial, temporal and spectral resolution satellite observations and burgeoning computer power are leading to significant improvements in our ability to predict weather phenomena at higher and more appropriate resolutions. Here, we describe recent work, illustrating such improvements. High spatial and temporal (at least hourly) resolution data from sequential geostationary multispectral imagery have been used to initialise a high resolution (15km) 4-D variational assimilation (4-D Var.) system to improve tropical cyclone track prediction. The same wind data, sometimes with the addition of TOVS data from NOAA operational satellites, have also been used at higher resolution (5km) to estimate tropical cyclone intensity, demonstrating the importance of very high resolution modelling and data for this enterprise. Finally, we are using very high resolution (1km) 4-D Var. with very high spatial temporal and spectral resolution observations available from experimental advanced sounder instruments such as the High resolution Interferometer Sounder (HIS) and the NPOESS Aircraft Sounder Testbed - Interferometer (NAST - I) to examine the impact after initialisation of the improved delineation of the thermal and moisture fields by these next-generation sounders. This we believe is the first use of advanced sounder data with 4-D Var. and will assist in exploiting such data from the experimental Advanced Infrared Sounder (AIRS), the operational Infrared Atmospheric Sounding Interferometer (IASI), the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) and Cross-track Interferometer Sounder (CrIS) instruments.

Tropical cyclone track and intensity prediction: The generation and assimilation of high-density, satellite-derived data

The impact of recent scientific and technological advances in tropical cyclone track, intensity and structure modeling is discussed. Since the early 1990s, developments have occurred in remote sensing, data assimilation procedures, numerical models and high performance computing. In particular, there is now quasi-continuous high spatial and temporal resolution data coverage over the previously data-sparse oceans where tropical cyclones spend most of their life cycles. There has been a rapid development of data assimilation methodologies capable of using these data to initialize high-resolution prediction models. Model developments have reached a stage of maturity where the representation of many of the physical processes necessary for improved tropical cyclone track and intensity prediction are now included. Finally, available computer power has reached the teraflop range. Most operational centers have high performance computers capable of tropical cyclone modeling at resolutions necessary for skillful track and intensity simulations. This article focuses on combining all of the above developments in a tropical cyclone data analysis and prediction system. The system has produced statistically significant reductions in the mean forecast error statistics for tropical cyclone track predictions and resulted in far more realistic simulations of tropical cyclone intensity and structure. A large number of tropical cyclones have been modeled, with emphasis on those classified as being “difficult” storms to predict accurately. These difficult storms are most responsible for rapidly growing forecast errors. Our results are illustrated by case studies of such tropical cyclones.

Meeting summary: Third COMPARE Workshop: A Model Intercomparison Experiment of Tropical Cyclone Intensity and Track Prediction

The Third Comparison of Mesoscale Prediction and Research Experiment (COMPARE) workshop was held in Tokyo, Japan, on 13–15 December 1999, cosponsored by the Japan Meteorological Agency (JMA), Japan Science and Technology Agency, and the World Meteorological Organization. The third case of COMPARE focuses on an event of explosive tropical cyclone [Typhoon Flo (9019)] development that occurred during the cooperative three field experiments, the Tropical Cyclone Motion experiment 1990, Special Experiment Concerning Recurvature and Unusual Motion, and TYPHOON-90, conducted in the western North Pacific in August and September 1990. Fourteen models from nine countries have participated in at least a part of a set of experiments using a combination of four initial conditions provided and three horizontal resolutions. The resultant forecasts were collected, processed, and verified with analyses and observational data at JMA. Archived datasets have been prepared to be distributed to participating members for use in further evaluation studies. In the workshop, preliminary conclusions from the evaluation study were presented and discussed in the light of initiatives of the experiment and from the viewpoints of tropical cyclone experts. Initial conditions, depending on both large-scale analyses and vortex bogusing, have a large impact on tropical cyclone intensity predictions. Some models succeeded in predicting the explosive deepening of the target typhoon at least qualitatively in terms of the time evolution of central pressure. Horizontal grid spacing has a very large impact on tropical cyclone intensity prediction, while the impact of vertical resolution is less clear, with some models being very sensitive and others less so. The structure of and processes in the eyewall clouds with subsidence inside as well as boundary layer and moist physical processes are considered important in the explosive development of tropical cyclones. Follow-up research activities in this case were proposed to examine possible working hypotheses related to the explosive development. New strategies for selection of future COMPARE cases were worked out, including seven suitability requirements to be met by candidate cases. The VORTEX95 case was withdrawn as a candidate, and two other possible cases were presented and discussed.

Beta Test of the Systematic Approach Expert System Prototype as a Tropical Cyclone Track Forecasting Aid

Abstract The authors have developed error mechanism conceptual models with characteristic track departures and anomalous wind or sea level pressure patterns for dynamical tropical cyclone track predictions primarily occurring in tropical regions or those associated with midlatitude circulation patterns. These conceptual models were based on a retrospective study in which it was known that the 72-h track error exceeded 300 n mi (555 km). A knowledge-based expert system module named the Systematic Approach Forecast Aid (SAFA) has been developed to assist the forecaster in the information management, visualization, and proactive investigation of the frequently occurring error mechanisms. A beta test of the SAFA module was carried out for all available track forecasts for the western North Pacific cyclones 19W–30W during 1999. The objective was to determine if the SAFA module could guide the team to apply the conceptual models in a real-time scenario to detect dynamical model tracks likely to have 72-h errors...

An Adaptive Multigrid Barotropic Tropical Cyclone Track Model

Abstract This paper describes the application of adaptive multigrid techniques to the problem of tropical cyclone track prediction. Based on the nondivergent barotropic vorticity equation, the model uses an adaptive multigrid method to refine the mesh around the moving vortex. Like conventional nested-grid models, this model achieves nonuniform resolution by superimposing uniform grids of different mesh sizes. Unlike nested-grid models, multigrid processing uses the interplay between solutions on fine and coarse grids—in regions where they overlap—to 1) solve the implicit problem for the streamfunction with optimum efficiency, 2) automatically achieve two-way interaction at the grid interfaces, and 3) provide accurate truncation error estimates for use in determining where to refine or coarsen the grids. An exchange rate algorithm accomplishes the latter task, approximately optimizing the grid selection based on a user-specified trade-off between accuracy and computational work. Numerical results demonstr...

Improved tropical cyclone track predictions using error recycling

Errors produced by a nonlinear predictive scheme contain information about both the observations and the prediction system. Therefore, its error history would be expected to contribute to increasing the skill of the predictions if it is included in the forecast. In this study an error recycling procedure is developed for tropical cyclone track prediction. Errors are defined here as differences between the model forecast and the best track position. Error histories are incorporated into a nonlinear analogue, or simplex, forecast scheme and applied to tropical cyclone track prediction, using the archives of observed position data associated with the forecast errors. Various forecast experiments of the cyclone tracks are performed: standard simplex predictions using observed positions only; simplex predictions improved by error forecasts based on libraries of both observations and the recycled forecast errors; and, finally, predictions that include NWP-model forecasts and their errors as predictors. The resulting gains in skill of predictions out to 72 hours ahead are found to be substantial.

Tropical cyclone track predictability

In this study an attempt is made to estimate theinherent limits to tropical cyclone mean absolute track position errors out to 72 hours ahead and to compare these estimates with the position errors currently being obtained inpractice at weather centres around the world. A knowledge of the magnitude of the difference between the lower limit to predictability and that being achieved with state-of-the-art numerical weather prediction (NWP) models is of vital importance. A small difference would indicate that there is little further need for continued initiatives in the prediction of tropical cyclone tracks. On the other hand, a large difference would imply either that the problem requires continued emphasis or if there has been no significant trend towards reducing the forecast track errors, that present research and development techniques need to be extended or new procedures developed. It was found that the difference between the inherent and practical limits of tropical cyclone track position errors is presently about 35 to 40 per cent for advanced baroclinic NWP systems, a moderate to large difference, and one that is almost invariant between tropical cyclone basins. For simpler models, such as barotropic models, the difference is closer to 45 per cent but is again almost invariant. As far as the authors are aware, these are the first estimates of the lower bounds of tropical cyclone track predictability. Finally, very recent research studies with emerging range of high quality data, high density data sources, improved models and new data assimilation techniques suggest that the difference possibly is now down to about 30 to 35 per cent. This value is encouragingly small but still large enough to continue active research programs in improving tropical cyclone motion prediction. Much of the forecast track errors now come from major forecast errors associated with tropical cyclones that follow erratic tracks.

Cloud and water vapour motion vectors in tropical cyclone track forecasting — A review

Tropical cyclone track prediction remains a vexing problem in meteorology, particularly for numerical weather prediction. While there has been significant improvement in forecast skill in recent years, errors in prognosis, particularly for recurving cyclones still remain unacceptably high. Consistent with track prediction being to a significant extent an initial value problem, there has been, in recent years, cogent evidence that, a combination of high resolution numerical modelling, the use of appropriate assimilation techniques and the exploitation of high spatial and temporal resolution observations can improve the accuracy of tropical cyclone forecasts. Before landfall, tropical cyclones have their genesis and move over the data-sparse tropical oceans. Here the prediction of their movement is an application for which remotely sensed data are quintessential. In this context, this paper examines the increasingly important contribution of cloud and water vapour motion vectors to tropical cyclone prediction and evaluates their import to accurate prediction in terms of both the numerical modelling characteristics and the data assimilation techniques employed. Overall, it is shown that cloud and water vapour drift winds have made a significant contribution to the tropical cyclone track forecasting problem when used with conventional intermittent assimilation techniques, such as 6-hourly cycling, and, more recently, with continuous assimilation techniques such as 3- and 4-dimensional variational assimilation. These continuous assimilation schemes appear to have the potential to use near continuous asynoptic wind data in the most effective way.

On impacts of cloud-tracked wind observations on numerical tropical cyclone forecasts

The impacts of the cloud-tracked winds on tropical cyclone forecasts, which were reprocessed for the period of the tropical cyclone field experiments TCM-90 operated in the western North Pacific in August and September 1990, were investigated. To achieve this purpose, we made reanalysis and forecast experiments with the operational global analysis and forecast models of the JMA. Our results are as follows: (1) The predicted tracks of tropical cyclones successfully improved by the reprocessed cloud-tracked winds. (2) Forecasts of geopotential fields in the western North Pacific areas in which these observations were distributed, also improved by the reprocessed winds. These results suggest that the improvement of tropical cyclone track prediction depends on the improvement of forecasts of large scale fields. (3) With level reassignment of the cloud-tracked winds as in the operational model, their impacts were not so significant. Rash enhancement of observations does not introduce the improvement of tropical cyclone forecast. The appropriate level assignment is more important.

Tropical cyclone track prediction by a high resolution limited area model using synthetic observations

ABSTRACT. Results of tropical cyclone track prediction experiments in die Indian seas by a high resolution limited area numerical weather prediction model (1° × 1° lat./long. grid) are presented. As the tropical cyclones form in data sparse regions of tropical oceans, and are, therefore, not well analysed in die initial fields, a scheme has been developed for generation of synthetic observations -based on die empirical structure of tropical cyclones, and their assimilation into the objective analysis, for preparing initial fields for running a forecast model. Experiments on track prediction have beat : conducted for die cyclones forming in the Bay of Bengal and Arabian Sea during the period 1990-95. Forecast errors of the model for 24 hr and 48 hr forecasts have been computed. A sensitivity experiment has been carried out to demonstrate the importance of initial humidity field on forecast model performance. The experiment brings out crucial important of the initial humidity field prescription in accurate track prediction by die forecast model.
 

Deterministic methods for prediction of tropical cyclone tracks

ABSTRACT. The paper presents a state-of-art review of different objective techniques available for tropical cyclone track prediction. A brief description of current theories of tropical cyclone motion is given. Deterministic models with statistical and dynamical methods have been discussed. Recent advances in the understanding of cyclone structure and motion aspects have led to improved prediction of tropical cyclones. There has been considerable progress in the field of prediction by dynamical methods. High resolution Limited Area Models (LAM) as well as Global Circulation Models (GCM) are now being used extensively by most of the leading operational numerical weather prediction (NWP) centres in the world The major achievements towards improvement of such models have come from improved horizontal resolution of the models, inclusion of physical processes, use of synthetic and other non-conventional data in the data assimilation schemes and nudging method for initial matching of analysed cyclone centres with corresponding observations.
 A brief description of further improvement in deterministic approach for prediction of tropical cyclone tracks is outlined.

Satellite-based monitoring and prediction of tropical cyclone intensity and movement


 
 ABSTRACT. Capabilities of meteorological satellites have gone a long way in meeting requirements of synoptic analysis and forecasting of tropical cyclones. This paper shows the impact made by the satellite data in the intensity estimation and track prediction of tropical cyclones in the Indian Seas and also reviews the universally applied Dvorak algorithm for performing tropical cyclone intensity analysis.
 Extensive use of Dvorak's intensity estimation scheme has revealed many of its limitations and elements of subjectivity in the analysis of tropical cyclones over the Arabian Sea and the Bay of Bengal, which, like cyclones in other ocean basins, also exhibit wide structural variability as seen in the satellite imagery.
 Satellite-based cyclone tracking techniques include: (i) use of satellite-derived mean wind flow, (ii) animation of sequence of satellite images and extrapolation of the apparent motion of the cloud system and (iii) monitoring changes in the upper level moisture patterns in the water vapour absorption channel imagery.
 Satellite-based techniques on tropical cyclone intensity estimation and track prediction have led to very significant improvement in disaster warning and consequent saving of life and property.
 

Evaluation of the performance of tropical cyclone track prediction techniques

ABSTRACT. This paper reviews the methods by which techniques for predicting tropical cyclone (TC) motion can be evaluated. Different error measures (forecast error, systematic error, and cross-track and along-track errors) are described in detail. Examples are then given to show how these techniques can be further evaluated by stratifying the forecasts based on factors related to the TC, including latitude, longitude, intensity change, size and past movement. Application of the Empirical-Orthogonal-Function (EOF) approach to represent the environmental flow associated with the TCs is also proposed. The magnitudes of the EOF coefficients can then be used to stratify the forecasts since these coefficients represent different types of flow fields. A complete evaluation of a forecast technique then consists of a combination of analyzing the different error measures based on both the storm- related factors and the EOF coefficients.