Editorial Type:
Article
Article Type:
Research Article

Tropical Cyclone–like Vortices Detection in the NCEP 16-Day Ensemble System over the Western North Pacific in 2008: Application and Forecast Evaluation

Hsiao-Chung Tsai Central Weather Bureau, Taipei, Taiwan

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Kuo-Chen Lu Central Weather Bureau, Taipei, Taiwan

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Russell L. Elsberry Graduate School of Engineering and Applied Sciences, Department of Meteorology, Naval Postgraduate School, Monterey, California

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Mong-Ming Lu Central Weather Bureau, Taipei, Taiwan

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Chung-Hsiung Sui Institute of Hydrological and Oceanic Sciences, and Department of Atmospheric Sciences, National Central University, Jhongli City, Taiwan

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Print Publication:
01 Feb 2011
DOI:
https://doi.org/10.1175/2010WAF2222415.1
Page(s):
77–93
Restricted access

Abstract

An automated technique has been developed for the detection and tracking of tropical cyclone–like vortices (TCLVs) in numerical weather prediction models, and especially for ensemble-based models. A TCLV is detected in the model grid when selected dynamic and thermodynamic fields meet specified criteria. A backward-and-forward extension from the mature stage of the track is utilized to complete the track. In addition, a fuzzy logic approach is utilized to calculate the TCLV fuzzy combined-likelihood value (TFCV) for representing the TCLV characteristics in the ensemble forecast outputs. The primary objective of the TCLV tracking and TFCV maps is for use as an evaluation tool for the operational forecasters. It is demonstrated that this algorithm efficiently extracts western North Pacific TCLV information from the vast amount of ensemble data from the NCEP Global Ensemble Forecast System (GEFS). The predictability of typhoon formation and activity during June–December 2008 is also evaluated. The TCLV track numbers and TFCV averages around the formation locations during the 0–96-h period are more skillful than for the 102–384-h forecasts. Compared to weak tropical cyclones (TCs; maximum intensity ≤ 50 kt), the storms that eventually become stronger TCs do have larger TFCVs. Depending on the specified domain size and the ensemble track numbers to define a forecast event, some skill is indicated in predicting the named TC activity. Although this evaluation with the 2008 typhoon season indicates some potential, an evaluation with a larger sample is necessary to statistically verify the reliability of the GEFS forecasts.

Corresponding author address: Dr. Kuo-Chen Lu, Weather Forecast Center, Central Weather Bureau, No. 64, Gongyuan Rd., Taipei City 10048, Taiwan. Email: gcleu@cwb.gov.tw

Abstract

An automated technique has been developed for the detection and tracking of tropical cyclone–like vortices (TCLVs) in numerical weather prediction models, and especially for ensemble-based models. A TCLV is detected in the model grid when selected dynamic and thermodynamic fields meet specified criteria. A backward-and-forward extension from the mature stage of the track is utilized to complete the track. In addition, a fuzzy logic approach is utilized to calculate the TCLV fuzzy combined-likelihood value (TFCV) for representing the TCLV characteristics in the ensemble forecast outputs. The primary objective of the TCLV tracking and TFCV maps is for use as an evaluation tool for the operational forecasters. It is demonstrated that this algorithm efficiently extracts western North Pacific TCLV information from the vast amount of ensemble data from the NCEP Global Ensemble Forecast System (GEFS). The predictability of typhoon formation and activity during June–December 2008 is also evaluated. The TCLV track numbers and TFCV averages around the formation locations during the 0–96-h period are more skillful than for the 102–384-h forecasts. Compared to weak tropical cyclones (TCs; maximum intensity ≤ 50 kt), the storms that eventually become stronger TCs do have larger TFCVs. Depending on the specified domain size and the ensemble track numbers to define a forecast event, some skill is indicated in predicting the named TC activity. Although this evaluation with the 2008 typhoon season indicates some potential, an evaluation with a larger sample is necessary to statistically verify the reliability of the GEFS forecasts.

Corresponding author address: Dr. Kuo-Chen Lu, Weather Forecast Center, Central Weather Bureau, No. 64, Gongyuan Rd., Taipei City 10048, Taiwan. Email: gcleu@cwb.gov.tw

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