Tropical Cyclone Energy Energetics and Intensity Prediction

The lack of improvement of numerical models in predicting tropical cyclone intensity over the past 2 decades is well documented. Recently, the HRH study showed that intensity prediction was not substantially improved even with increases of resolution, where presumably clouds are more accurately represented. The consensus of the HFiP study, was that problems in initialization and lack of real predictability were the primary factors to blame for this stalemate. We offer a new explanation, more specifically, that the dynamics cores of regional numerical models are often inadequately formulated to simulate the internal energy exchanges that together drive intensity evolution. It is well understood that the maximum potential intensity (MPI) of a tropical cyclone is determined by the equilibrium structural form of a tropical cyclone that generates energy from a Carnot cycle – like thermodynamic process that is used to perform work against friction. This simple model treats many details implicitly, such as the roles of turbulence and its dissipation, work performed on the environment, energy storage and so on in order to demonstrate this first order principle. In complex cloud-resolving numerical models, these energy exchanges are formulated explicitly, but should reach the implicit balances in the equilibrium limit. Surprisingly they do not and very possibly can not, and the error is first order. As a consequence, many or most regional models create or leak energy numerically and so may be ultimately incapable of simulating intensity. In the oral presentation the internal energy exchanges that occur in the NMS model are diagnosed and their influence on intensity change is shown. It will be shown how common model formulations incorrectly represent exchanges and how the simulated intensity is hyper-responsive to these shortcomings. Finally, the results of tests that correct these errors will be shown to dramatically improve intensity prediction.