A Parametric Model for Predicting Hurricane Rainfall

Manuel Lonfat Risk Management Solutions, Ltd., London, United Kingdom

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Robert Rogers NOAA/AOML/Hurricane Research Division, Miami, Florida

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Timothy Marchok NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Frank D. Marks Jr. NOAA/AOML/Hurricane Research Division, Miami, Florida

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Abstract

This study documents a new parametric hurricane rainfall prediction scheme, based on the rainfall climatology and persistence model (R-CLIPER) used operationally in the Atlantic Ocean basin to forecast rainfall accumulations. Although R-CLIPER has shown skill at estimating the mean amplitude of rainfall across the storm track, one underlying limitation is that it assumes that hurricanes produce rain fields that are azimuthally symmetric. The new implementations described here take into account the effect of shear and topography on the rainfall distribution through the use of parametric representations of these processes. Shear affects the hurricane rainfall by introducing spatial asymmetries, which can be reasonably well modeled to first order using a Fourier decomposition. The effect of topography is modeled by evaluating changes in elevation of flow parcels within the storm circulation between time steps and correcting the rainfall field in proportion to those changes. Effects modeled in R-CLIPER and those from shear and topography are combined in a new model called the Parametric Hurricane Rainfall Model (PHRaM). Comparisons of rainfall accumulations predicted from the operational R-CLIPER model, PHRaM, and radar-derived observations show some improvement in the spatial distribution and amplitude of rainfall when shear is accounted for and significant improvements when both shear and topography are modeled.

Corresponding author address: Dr. Manuel Lonfat, Risk Management Solutions, Ltd., Peninsular House, 30 Monument St., London EC3R 8HB, United Kingdom. Email: manuel.lonfat@rms.com

Abstract

This study documents a new parametric hurricane rainfall prediction scheme, based on the rainfall climatology and persistence model (R-CLIPER) used operationally in the Atlantic Ocean basin to forecast rainfall accumulations. Although R-CLIPER has shown skill at estimating the mean amplitude of rainfall across the storm track, one underlying limitation is that it assumes that hurricanes produce rain fields that are azimuthally symmetric. The new implementations described here take into account the effect of shear and topography on the rainfall distribution through the use of parametric representations of these processes. Shear affects the hurricane rainfall by introducing spatial asymmetries, which can be reasonably well modeled to first order using a Fourier decomposition. The effect of topography is modeled by evaluating changes in elevation of flow parcels within the storm circulation between time steps and correcting the rainfall field in proportion to those changes. Effects modeled in R-CLIPER and those from shear and topography are combined in a new model called the Parametric Hurricane Rainfall Model (PHRaM). Comparisons of rainfall accumulations predicted from the operational R-CLIPER model, PHRaM, and radar-derived observations show some improvement in the spatial distribution and amplitude of rainfall when shear is accounted for and significant improvements when both shear and topography are modeled.

Corresponding author address: Dr. Manuel Lonfat, Risk Management Solutions, Ltd., Peninsular House, 30 Monument St., London EC3R 8HB, United Kingdom. Email: manuel.lonfat@rms.com

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