• Atmosphere
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• v.24 no.4
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• pp.503-514
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• 2014

Evaluation of predictability of numerical models for tropical cyclone track was performed using along-and cross-track component. The along-and cross-track bias were useful indicators that show the numerical models predictability associated with cause of errors. Since forecast errors, standard deviation and consistency index of along-track component were greater than those of cross-track component, there was some rooms for improvement in alongtrack component. There was an overall slow bias. The most accurate model was JGSM for 24-hour forecast and ECMWF for 48~96-hour forecast in direct position error, along-track error and cross-track error. ECMWF and GFS had a high variability for 24-hour forecast. The results of predictability by track type showed that most significant errors of tropical cyclone track forecast were caused by the failure to estimate the recurvature phenomenon.

• Journal of Environmental Science International
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• v.21 no.2
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• pp.263-266
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• 2012

To compare the effects of two external forcing on track of typhoon, TWRF(Typhoon WRF) based ensemble experiments are carried out in the case of Typhoon Morako which is the 8th typhoon at Northwest Pacific region in 2009. The two forcing are tropical SST and topography induced thermal and mechanical forcing, respectively. According to the result of numerical experiment for five-day forecast, the effect of mechanical forcing is about two times stronger than thermal forcing on the track error of the typhoon. More case study for other typhoon will be done as a next paper.

• Atmosphere
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• v.32 no.4
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• pp.381-394
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• 2022

The Korea Meteorological Administration (KMA) National Typhoon Center has been officially releasing reanalyzed best tracks for the previous year's northwest Pacific typhoons since 2015. However, while most typhoon researchers are aware of the data released by other institutions, such as the Joint Typhoon Warning Center (JTWC) and the Regional Specialized Meteorological Center (RSMC) Tokyo, they are often unfamiliar with the KMA products. In this technical note, we describe the best track data released by KMA, and the algorithms that are used to generate it. We hope that this will increase the usefulness of the data to typhoon researchers, and help raise awareness of the product. The best track reanalysis process is initiated when the necessary database of observations-which includes satellite, synoptic, ocean, and radar observations-has become complete for the required year. Three categories of best track information-position (track), intensity (maximum sustained winds and central pressure), and size (radii of high-wind areas)-are estimated based on scientific processes. These estimates are then examined by typhoon forecasters and other internal and external experts, and issued as an official product when final approval has been given.

• Journal of the Korean Institute of Navigation
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• v.18 no.3
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• pp.19-30
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• 1994

By use of the recent tropical cyclones' data in the Northwest Pacific Ocean, the occurrence frequency and region of typhoon as well as the features of the monthly mean track were analyzed. As the result of this study, (1) mean occurrence frequency of typhoon per year is 27.5, and 68% of total typhoons were formed in July to October and shown the highest frequency in August. (2) The ave-rage duration of typhoons is 8.5 days, and super typhoon which maximum sustained surface wind speeds is more than 130 knots occurs most frequently in October and November. (3) The highest frequency ap-pears around the Caroline, Mariana and Marshall Islands, and in wintertime, typhoon occurs in lower lati-tude comparing with those in summertime. (4) The typhoon track depends upon the distribution of pres-sure system and steering current in neighbouring areas. The mean track of typhoon can be classified into three types such as westward-moving type, northward-moving type and abnormally moving type. The west-ward-moving typhoons make landfall on the southern China by way of the South China Sea in June and July, on mid-part of China in August and September, and on Indo-china Peninsula in October and Novem-ber. The northward-moving typhoons approximately move on north~northwestward track to $20~30^{\circ}N$ from the occurrence region, then recurve to the East Sea through Korean Peninsula and Kyushu Island in June and July, to the Noth Pacific Ocean along the Japanese Islands in August and September and to the North Pacific Ocean through the seas far south off the Japan in October and November.

• Atmosphere
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• v.21 no.2
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• pp.209-220
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• 2011

A new consensus algorithm for the prediction of tropical cyclone track has been developed. Conventional consensus is a simple average of a few fixed models that showed the good performance in track prediction for the past few years. Meanwhile, the consensus in this study is a weighted average of a few models that may change for every individual forecast time. The models are selected as follows. The first step is to find the analogous past tropical cyclone tracks to the current track. The next step is to evaluate the model performances for those past tracks. Finally, we take the weighted average of the selected models. More weight is given to the higher performance model. This new algorithm has been named as DYTRAP (DYnamic data-base Typhoon tRAck Prediction) in the sense that the data base is used to find the analogous past tracks and the effective models for every individual track prediction case. DYTRAP has been applied to all 2009 tropical cyclone track prediction. The results outperforms those of all models as well as all the official forecasts of the typhoon centers. In order to prove the real usefulness of DYTRAP, it is necessary to apply the DYTRAP system to the real time prediction because the forecast in typhoon centers usually uses 6-hour or 12-hour-old model guidances.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.311-315
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• 2004

This paper is aimed to develop a mathematical model for making the forecast information of typhoon's movement such as the estimated movement direction and positions after 24 and 48 hours. The proposed model calculates such kind of information of a typhoon by similar past typhoon's track data which are selected with three similarity criteria among the database of typhoons' tracks for past fifty years. We carried out a simulation forecast with No.14 typhoon formed in 1997, and found that the results of the proposed model were reasonable and it would be suitable for a simulation system for training mariners so that they can take suitable actions to evade the typhoons.

• Atmosphere
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• v.24 no.3
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• pp.419-432
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• 2014

An assessment of typhoon intensity predictability of numerical models was conducted to develop the typhoon intensity forecast guidance comparing with the RSMC-Tokyo best track data. Root mean square error, box plot analysis and time series of wind speed comparison were performed to evaluate the each model error level. One of noticeable fact is that all models have a trend of error increase as typhoon becomes stronger and the Global Forecast System showed the best performance among the models. In the detailed analysis in two typhoon cases [Danas (1324) and Haiyan (1330)], GFS showed good performance in maximum wind speed and intensity trend in the best track, however it could not simulate well the rapid intensity increasing period. On the other hand, ECMWF and Hurricane-WRF overestimated the typhoon intensity but simulated track trend well.

• Wind and Structures
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• v.35 no.4
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• pp.287-296
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• 2022

Analyzing the typhoon wind hazards is crucial to determine the extreme wind load on engineering structures in the typhoon prone region. In essence, the typhoon hazard analysis is a high-dimensional problem with randomness arising from the typhoon genesis, environmental variables and the boundary layer wind field. This study suggests a dimension reduction approach by decoupling the original typhoon hazard analysis into two stages. At the first stage, the randomness of the typhoon genesis and environmental variables are propagated through the typhoon track model and intensity model into the randomness of the key typhoon parameters. At the second stage, the probability distribution information of the key typhoon parameters, combined with the randomness of the boundary layer wind field, could be used to estimate the extreme wind hazard. The Chinese southeast coastline is taken as an example to demonstrate the adequacy and efficiency of the suggested decoupling approach.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.241-253
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• 2015

In this paper we predict the track of typhoons using a Bayesian principal component regression model based on wind field data. Data is obtained at each time point and we applied the Bayesian principal component regression model to conduct the track prediction based on the time point. Based on regression model, we applied to variable selection prior and two kinds of prior distribution; normal and Laplace distribution. We show prediction results based on Bayesian Model Averaging (BMA) estimator and Median Probability Model (MPM) estimator. We analysis 8 typhoons in 2006 using data obtained from previous 6 years (2000-2005). We compare our prediction results with a moving-nest typhoon model (MTM) proposed by the Korea Meteorological Administration. We posit that is possible to predict the track of a typhoon accurately using only a statistical model and without a dynamical model.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.93-102
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• 2019

In this study, in order to analyze the possibility of observing a typhoon track based on the Global Navigation Satellite System(GNSS), Typhoon NARI, the 11th typhoon of 2007, was analyzed in terms of the typhoon track as well as the local variation of perceptible water over time. The perceptible water was estimated using data obtained from observatories located on the typhoon track from Jeju to the southern coast of Korea for a total of 18 days from September 7(DOY 250) to September 24(DOY 267), 2007, including the period when the observatories were affected by the typhoon at full-scale, as well as one previous week and one following week. The results show that the trend of the variation of perceptible water was similar between the observatories near the typhoon track. Variation of perceptible water over time depending on the development and landing of the typhoon was distinctively observed. Several hours after the daily maximum of perceptible water was found at the JEJU Observatory, the first struck by the typhoon on the typhoon track, the maximum value was found at other observatories located on the southern coast. In the observation period, the time point at which the maximum perceptible water was recorded in each location was almost the same as the time point at which the typhoon landed at the location. To analyze the accuracy of the GNSS-based perceptible water measurement, the data were compared with radiosonde-based perceptible water data. The mean error was 0.0cm, and the root mean square error and the standard deviation were both 0.3cm, indicating that the GNSS-based perceptible water data were highly accurate and precise. The results of the this study show that the GNSS-based perceptible water data may be used as highly accurate information for the analysis of typhoon tracks over time.