4A.7 Evaluation of tropical cyclone surface wind structure in operational NWP model forecasts (2008

4A.7

Evaluation of tropical cyclone surface wind structure in operational NWP model forecasts

Timothy Marchok, NOAA/GFDL, Princeton, NJ; and R. Rogers and M. Powell

The property damage and loss of life from Atlantic hurricanes

over the last several years has highlighted the importance of

tropical cyclone intensity prediction. Hurricanes Katrina (2005)

and Charley (2004), two intense hurricanes of markedly differing

sizes at landfall, have also shown that the prediction of surface

wind structure is just as important as the prediction of storm

intensity when assessing the potential for damage from a

landfalling cyclone. In this paper, we examine new methods of

evaluating forecasts of tropical cyclone wind structure from

dynamical models, and we apply these methods to forecasts for

storms from the 2007 Atlantic hurricane season.

One new method involves the evaluation of model-predicted

surface wind values at specified radii along 45-degree

azimuths in each storm quadrant. This method provides a

continuous wind profile for each model in each quadrant. This

is in contrast to the standard method of determining the radii

of 34-, 50- and 64-kt winds, which often results in incomplete

datasets due to the models often having difficulty in producing

winds at these thresholds.

Another new method involves the application of techniques

described by Powell and Reinhold (2007) to evaluate the near-

surface integrated kinetic energy (IKE) in each model. Various

IKE quantities will be evaluated for each of the models. A third

method involves evaluating the distribution of winds in each storm

quadrant. Comparisons between profiles of forecast and observed

wind distributions will be shown, and validation statistics will

be presented, including probability of detection and false alarm

rates.

In the talk, we will describe the methods used and provide

evaluation of these methods for selected 2007 Atlantic storms

for forecasts from the GFS, UKMET, ECMWF, NOGAPS, CMC, GFDL

and HWRF models.