Objective Center-Finding Algorithm for Tropical Cyclones in Numerical Models

Zhao, Chenghui; Song, Jun; Leng, Hongze; Zhao, Juan

doi:10.3390/atmos10070376

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…But, when the morphological structure characteristics of tropical cyclone are not obvious, the morphological model analysis method cannot locate the center of tropical cyclone. The wind field analysis method is to locate the center of tropical cyclone according to the characteristics of cyclone [22,23]. The minimum wind speed and the maximum vorticity are the central features of the tropical cyclone.…”

Section: Introductionmentioning

confidence: 99%

A method of locating tropical cyclone center based on gaussian model

You

Qian

2023

Preprint

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The Tropical cyclones usually refer to low-pressure eddies that rotate rapidly in the tropics. It seriously threatens the life and property safety,Therefore, the prediction of both the accurate location of the tropical cyclone center and the tropical cyclone path is the key to preventing tropical cyclone disasters. In this paper, a fast method for calculating the center of tropical cyclone using infrared satellite image or visible satellite image is proposed. A two-dimensional Gaussian normal distribution model is used to simulate the gray characteristics of tropical cyclone images. The gray distribution of tropical cyclone satellite image approximates to a two-dimensional Gaussian distribution. In multiple directions, the pixel gray values of tropical cyclone are accumulated, and a set of one-dimensional Gaussian normal distribution functions are used to fit these accumulated values. The peak positions of these one-dimensional Gaussian functions are calculated by derivation. Then, a linear function is fitted according to the relationship between the peak position of the group of Gaussian functions and the selected angle. The coefficient of the fitting linear function is exactly the central coordinate of the tropical cyclone. The proposed method for locating the center of tropical cyclone is tested using visible and infrared satellite images. The results are compared with the best trajectory provided by the Japan Meteorological Agency.

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Section: Introductionmentioning

confidence: 99%

A method of locating tropical cyclone center based on gaussian model

You

Qian

2023

Preprint

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“…Considering the influence of clouds and rain belts around the wind eye on the positioning process, the experimental results for infrared satellite cloud images indicated that the best average error of the model in the longitude and latitude directions reached 0.12238 (approximately 13.58 km). Zhao et al (2019) used the centroid algorithm from two-dimensional Fourier filtering to detect potential cyclone vortices based on eliminating small-scale perturbations and finally calculated the vortex center. The advantage of this algorithm is that the parameters are automatically adjusted according to the size of the target vortex.…”

Section: Introductionmentioning

confidence: 99%

A New Objective Typhoon Location Algorithm Considering a Perturbation Factor Based on FY-4A Brightness Temperature Data

Xie

Chen

Yan³

2022

Journal of Atmospheric and Oceanic Technology

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In this paper, a new objective typhoon positioning algorithm was proposed. The algorithm uses L1 12-channel far-infrared data of the FY-4A geostationary meteorological satellite for objective positioning, verified against best path data provided by the Tropical Cyclone Data Center of the China Meteorological Administration (CMA). By calculating the tangential and radial perturbation values of infrared brightness temperature images, the perturbation factor can be obtained. By adopting the position of the maximum perturbation factor as the center of a circle and considering a radius of no more than 20 km, the position of the minimum perturbation factor was determined; this value represents the central position of the typhoon. Tropical cyclones in 2019 and 2020 were selected for objective positioning, and the objective positioning results were verified against the corresponding time in the best path dataset. The results included centralized verification results for 29 typhoons and optimal path data in 2019. The maximum average error reached 54.67 km, with an annual average typhoon positioning error of 16.15 km. The centralization verification results for 23 typhoons and optimal path data in 2020 indicated a minimum average error of 12.71 km, a maximum average error of 18.56 km, and an annual average typhoon positioning error of 14.82 km. The positioning results for these two years suggest that the longitude obtained with the perturbation factor positioning method is satisfactory, exhibiting an error of less than 20 km.

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“…The second kind of method is based on the wind field analysis [ 21 , 22 ]. The center of tropical cyclone is determined by finding the minimum value of wind speed or the maximum value of cyclone vortices [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

A Tropical Cyclone Center Location Method Based on Satellite Image

You

Qian

et al. 2022

Computational Intelligence and Neuroscience

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Accurately detecting and locating the center of the tropical cyclone is critical for the trajectory forecasting. This study proposed an automatic method for centers’ location of the tropical cyclones based on the visible or the infrared satellite images. The morphological structure of the tropical cyclone is modeled using the circular pattern. The tropical cyclone center is located based on regional pixels instead of skeleton points. All pixels in a segmented cloud cluster vote for a 2-dimensional accumulator. The center of the cloud cluster is computed by the mean voting distances, which are calculated by fitting quadratic functions in every column of the two-dimensional (2D) accumulator. Then, a linear function is fitted according to the functional relationship between the mean voting distance and voting angle. The fitted coefficients of the linear function are the center coordinates of the tropical cyclone. The proposed method for centers location of the tropical cyclones is tested using visible and infrared satellite images. The results of center location are compared with the best track provided in JMA datasets.

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Objective Center-Finding Algorithm for Tropical Cyclones in Numerical Models

Cited by 7 publications

References 47 publications

A method of locating tropical cyclone center based on gaussian model

A method of locating tropical cyclone center based on gaussian model

A New Objective Typhoon Location Algorithm Considering a Perturbation Factor Based on FY-4A Brightness Temperature Data

A Tropical Cyclone Center Location Method Based on Satellite Image

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