Examining Trends in Satellite-Detected Tropical Overshooting Tops as a Potential Predictor of Tropical Cyclone Rapid Intensification

Sarah A. Monette Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

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Christopher S. Velden Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

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Kyle S. Griffin Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Christopher M. Rozoff Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

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Abstract

A geostationary satellite–derived cloud product that is based on a tropical-overshooting-top (TOT) detection algorithm is described for applications over tropical oceans. TOTs are identified using a modified version of a midlatitude overshooting-top detection algorithm developed for severe-weather applications. The algorithm is applied to identify TOT activity associated with Atlantic Ocean tropical cyclones (TCs). The detected TOTs can serve as a proxy for “hot towers,” which represent intense convection with possible links to TC rapid intensification (RI). The purpose of this study is to describe the adaptation of the midlatitude overshooting-top detection algorithm to the tropics and to provide an initial exploration of possible correlations between TOT trends in developing TCs and subsequent RI. This is followed by a cursory examination of the TOT parameter’s potential as a predictor of RI both on its own and in multiparameter RI forecast schemes. RI forecast skill potential is investigated by examining empirical thresholds of TOT activity and trends within prescribed radii of a large sample of developing North Atlantic TC centers. An independent test on Atlantic TCs in 2006–07 reveals that an empirically based TOT scheme has potential as a predictor for RI occurring in the subsequent 24 h, especially for RI maximum wind thresholds of 25 and 30 kt (24 h)−1 (1 kt ≈ 0.5 m s−1). As expected, the stand-alone TOT-based RI scheme is comparatively less accurate than existing objective multiparameter RI prediction methods. A preliminary experiment that adds TOT-based predictors to an objective logistic regression-based scheme is shown to improve slightly the forecast skill of RI, however.

Current affiliation: Department of Atmospheric and Oceanic Sciences, University of Wisconsin—Madison, Madison, Wisconsin.

Corresponding author address: Sarah A. Monette, Cooperative Institute for Meteorological Satellite Studies, 1225 W. Dayton St., Madison, WI 53706. E-mail: sarah.monette@ssec.wisc.edu

Abstract

A geostationary satellite–derived cloud product that is based on a tropical-overshooting-top (TOT) detection algorithm is described for applications over tropical oceans. TOTs are identified using a modified version of a midlatitude overshooting-top detection algorithm developed for severe-weather applications. The algorithm is applied to identify TOT activity associated with Atlantic Ocean tropical cyclones (TCs). The detected TOTs can serve as a proxy for “hot towers,” which represent intense convection with possible links to TC rapid intensification (RI). The purpose of this study is to describe the adaptation of the midlatitude overshooting-top detection algorithm to the tropics and to provide an initial exploration of possible correlations between TOT trends in developing TCs and subsequent RI. This is followed by a cursory examination of the TOT parameter’s potential as a predictor of RI both on its own and in multiparameter RI forecast schemes. RI forecast skill potential is investigated by examining empirical thresholds of TOT activity and trends within prescribed radii of a large sample of developing North Atlantic TC centers. An independent test on Atlantic TCs in 2006–07 reveals that an empirically based TOT scheme has potential as a predictor for RI occurring in the subsequent 24 h, especially for RI maximum wind thresholds of 25 and 30 kt (24 h)−1 (1 kt ≈ 0.5 m s−1). As expected, the stand-alone TOT-based RI scheme is comparatively less accurate than existing objective multiparameter RI prediction methods. A preliminary experiment that adds TOT-based predictors to an objective logistic regression-based scheme is shown to improve slightly the forecast skill of RI, however.

Current affiliation: Department of Atmospheric and Oceanic Sciences, University of Wisconsin—Madison, Madison, Wisconsin.

Corresponding author address: Sarah A. Monette, Cooperative Institute for Meteorological Satellite Studies, 1225 W. Dayton St., Madison, WI 53706. E-mail: sarah.monette@ssec.wisc.edu
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