An Algorithm for Tracking Eyes of Tropical Cyclones

Pao-Liang Chang Central Weather Bureau, Taipei, Taiwan

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Ben Jong-Dao Jou Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan

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Jian Zhang Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Abstract

A tropical cyclone (TC) eye tracking (TCET) algorithm is presented in this study to objectively identify and track the eye and center of a tropical cyclone using radar reflectivity data. Twelve typhoon cases were studied for evaluating the TCET algorithm. Results show that the TCET can track TC centers for several hours. The longest tracking time is about 35 h. Eye locations estimated from different radars showed consistency with a mean distance bias of about 3.5 km and a standard deviation of about 1.5 km. The TCET analysis shows decreasing eye radius as TCs approach land, especially within 50 km of the coastline.

The TCET algorithm is computationally efficient and can be automated by using the TC center in the previous volume or the estimated center from satellite images as an initial guess. The TCET may not accurately find the TC center when a TC is weak or does not have an enclosed eyewall or when it does have highly noncircular eyes. However, the algorithm is still suitable for operational implementation and provides high spatial and temporal resolution information for TC centers and eye radii, especially for intense TCs.

Corresponding author address: Pao-Liang Chang, Meteorological Satellite Center, Central Weather Bureau, No. 64, Gongyuan Road, Taipei, Taiwan. Email: larkdi@msc.cwb.gov.tw

Abstract

A tropical cyclone (TC) eye tracking (TCET) algorithm is presented in this study to objectively identify and track the eye and center of a tropical cyclone using radar reflectivity data. Twelve typhoon cases were studied for evaluating the TCET algorithm. Results show that the TCET can track TC centers for several hours. The longest tracking time is about 35 h. Eye locations estimated from different radars showed consistency with a mean distance bias of about 3.5 km and a standard deviation of about 1.5 km. The TCET analysis shows decreasing eye radius as TCs approach land, especially within 50 km of the coastline.

The TCET algorithm is computationally efficient and can be automated by using the TC center in the previous volume or the estimated center from satellite images as an initial guess. The TCET may not accurately find the TC center when a TC is weak or does not have an enclosed eyewall or when it does have highly noncircular eyes. However, the algorithm is still suitable for operational implementation and provides high spatial and temporal resolution information for TC centers and eye radii, especially for intense TCs.

Corresponding author address: Pao-Liang Chang, Meteorological Satellite Center, Central Weather Bureau, No. 64, Gongyuan Road, Taipei, Taiwan. Email: larkdi@msc.cwb.gov.tw

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