10.3 Improvements to Operational Statistical Tropical Cyclone Intensity Forecast Models

Wednesday, 10 January 2018: 2:00 PM
615 AB (Hilton) (Austin, Texas)
Galina Chirokova, CIRA/Colorado State Univ., Fort Collins, CO; and J. A. Knaff, M. DeMaria, and A. B. Schumacher

The Statistical Hurricane Intensity Prediction Scheme (SHIPS) and the Logistic Growth Equation Model (LGEM) are statistical-dynamical tropical cyclone (TC) intensity forecast models used in operations at both NOAA’s National Hurricane Center (NHC) and DOD’s Joint Typhoon Warning Center (JTWC). SHIPS and LGEM have consistently provided skillful operational intensity guidance and have been continually improved throughout their operational existence. Recent upgrades to SHIPS and LGEM that were developed with the Joint Hurricane Testbed (JHT) support will be presented. These improvements include replacing weekly sea surface temperatures (SSTs) with 1° spatial resolution with daily SSTs with 0.25° resolution, and using depth-averaged ocean temperature to add a physical mechanism to account for storm-induced SST cooling. The use of higher-resolution SST improves the maximum potential intensity (MPI) estimates, one of the primary predictors used in SHIPS, and also helps forecasts of intensity change when sharp SST gradients are encountered along the forecast track. The depth-averaged temperature is a more physically-based representation of ocean cooling than the traditional ocean heat content (OHC) between the surface and the depth of 26oC isotherm, and could replace the empirical SST cooling algorithm and the OHC predictor currently used in the operational models. Finally, a statistical-dynamical method to predict tropical cyclone wind structure in terms of wind radii and mean sea level pressure (MSLP) has been developed. This enables forecasts of wind radii and MSLP that are consistent with the SHIPS and/or LGEM intensity forecasts. The details of the upgrades and the impact on the intensity forecasts will be discussed.

Disclaimer: The views, opinions, and findings contained in this article are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration (NOAA) or U.S. Government position, policy, or decision.

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