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The Influence of Shallow Convection on Tropical Cyclone Track Forecasts

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  • 1 Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York
  • | 2 National Center for Atmospheric Research,* Boulder, Colorado
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ABSTRACT

Accurate tropical cyclone (TC) track forecasts depend on having skillful numerical model predictions of the environmental wind field. Given that wind and temperature are related through thermal wind balance, structural errors in the processes that determine the tropical temperature profile, such as shallow convection, can therefore lead to biases in TC position. This paper evaluates the influence of shallow convection on Advanced Hurricane Weather Research and Forecasting Model (AHW) TC track forecasts by cycling an ensemble data assimilation during a 1-month period in 2008 where cumulus convection is parameterized on the coarse-resolution domain using the Kain–Fritsch scheme or the modified Tiedtke scheme, which contains a more appropriate treatment of oceanic shallow convection. Short-term forecasts with the Kain–Fritsch scheme are characterized by a 1-K, 700-hPa temperature bias over much of the western Atlantic Ocean, which is attributed to a lack of shallow convection within that scheme. In turn, the horizontal gradients in this temperature bias are associated with wind biases in the region where multiple TCs move during this period. By contrast, the Tiedtke scheme does not suffer from this temperature bias, thus the wind biases are smaller. AHW forecasts initialized from the data assimilation system that uses the Tiedtke scheme have track errors that are up to 25% smaller than forecasts initialized from the data assimilation system that uses Kain–Fritsch.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Ryan Torn, University at Albany, State University of New York, ES 351, 1400 Washington Ave., Albany, NY 12222. E-mail: torn@atmos.albany.edu

ABSTRACT

Accurate tropical cyclone (TC) track forecasts depend on having skillful numerical model predictions of the environmental wind field. Given that wind and temperature are related through thermal wind balance, structural errors in the processes that determine the tropical temperature profile, such as shallow convection, can therefore lead to biases in TC position. This paper evaluates the influence of shallow convection on Advanced Hurricane Weather Research and Forecasting Model (AHW) TC track forecasts by cycling an ensemble data assimilation during a 1-month period in 2008 where cumulus convection is parameterized on the coarse-resolution domain using the Kain–Fritsch scheme or the modified Tiedtke scheme, which contains a more appropriate treatment of oceanic shallow convection. Short-term forecasts with the Kain–Fritsch scheme are characterized by a 1-K, 700-hPa temperature bias over much of the western Atlantic Ocean, which is attributed to a lack of shallow convection within that scheme. In turn, the horizontal gradients in this temperature bias are associated with wind biases in the region where multiple TCs move during this period. By contrast, the Tiedtke scheme does not suffer from this temperature bias, thus the wind biases are smaller. AHW forecasts initialized from the data assimilation system that uses the Tiedtke scheme have track errors that are up to 25% smaller than forecasts initialized from the data assimilation system that uses Kain–Fritsch.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Ryan Torn, University at Albany, State University of New York, ES 351, 1400 Washington Ave., Albany, NY 12222. E-mail: torn@atmos.albany.edu
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