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The Environment of Hurricane Debby (1982). Part I: Winds

Stephen J. LordHurricane Research Division/AOML/NOAA, 4301 Rickenbacker Causeway, Miami, FL 33149

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James L. FranklinHurricane Research Division/AOML/NOAA, 4301 Rickenbacker Causeway, Miami, FL 33149

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Abstract

A three-dimensional, nested analysis of wind fields in the environment of Hurricane Debby (1982) has been completed. The basic analysis tool uses a two-dimensional least-squares fitting algorithm combined with a derivative constraint that acts as a spatial low-pass filter on the analyzed field. Gridded results of horizontally analyzed fields are combined into vertical cross sections and then analyzed to produce vertical continuity. Consequently, a three-dimensional analysis is obtained.

The database for the analysis comes primarily from Omega dropwindsondes (ODWs), rawinsondes, and satellite-derived winds above 400 mb in the environment of Hurricane Debby near 0000 UTC 16 September 1982. Since these data come from many different sources, and thus are not evenly distributed in the horizontal or vertical, techniques have been developed to alleviate difficulties associated with inhomogeneous data. The analyzed wind fields provide an independent evaluation of satellite-derived winds at and below 400 mb.

General features of the environmental wind fields surrounding Debby are described. The wind analyses are then used to diagnose terms in the vorticity equation. The spatial orientation of a calculated dipole in the horizontal vorticity flux convergence term indicates that it is an approximate indicator of Debby's observed short-term motion.

Finally, to provide an initial assessment of the wind analysis quality, experimental track forecasts with a barotropic model are performed with the layer-mean wind fields and operationally available data outside the analysis domain. Initial errors in the forecast tracks are directly related to the orientation of the diagnosed vorticity flux convergence dipole. The research wind analysis results in a substantial reduction in track error for short-term (12 h) forecasts compared to analyses from operationally available data. This reduction is due to an improved representation of the wind fields in the near-storm environment.

Abstract

A three-dimensional, nested analysis of wind fields in the environment of Hurricane Debby (1982) has been completed. The basic analysis tool uses a two-dimensional least-squares fitting algorithm combined with a derivative constraint that acts as a spatial low-pass filter on the analyzed field. Gridded results of horizontally analyzed fields are combined into vertical cross sections and then analyzed to produce vertical continuity. Consequently, a three-dimensional analysis is obtained.

The database for the analysis comes primarily from Omega dropwindsondes (ODWs), rawinsondes, and satellite-derived winds above 400 mb in the environment of Hurricane Debby near 0000 UTC 16 September 1982. Since these data come from many different sources, and thus are not evenly distributed in the horizontal or vertical, techniques have been developed to alleviate difficulties associated with inhomogeneous data. The analyzed wind fields provide an independent evaluation of satellite-derived winds at and below 400 mb.

General features of the environmental wind fields surrounding Debby are described. The wind analyses are then used to diagnose terms in the vorticity equation. The spatial orientation of a calculated dipole in the horizontal vorticity flux convergence term indicates that it is an approximate indicator of Debby's observed short-term motion.

Finally, to provide an initial assessment of the wind analysis quality, experimental track forecasts with a barotropic model are performed with the layer-mean wind fields and operationally available data outside the analysis domain. Initial errors in the forecast tracks are directly related to the orientation of the diagnosed vorticity flux convergence dipole. The research wind analysis results in a substantial reduction in track error for short-term (12 h) forecasts compared to analyses from operationally available data. This reduction is due to an improved representation of the wind fields in the near-storm environment.

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