P1H.5 Using the JPL Tropical Cyclone Information System for Research and Applications

Tuesday, 29 April 2008
Palms ABCD (Wyndham Orlando Resort)
Svetla M. Hristova-Veleva, JPL, Pasadena, CA; and C. Ao, Y. Chao, V. Dang, R. Fovell, M. Garay, Z. Haddad, B. Knosp, B. Lambrigtsen, P. P. Li,, K. J. Park, W. Poulsen, H. Su, S. Tanelli, D. Vane, Q. A. Vu, J. Willis, and D. L. Wu

Despite the many datasets collected from satellite, aircraft and in situ platforms, there is no one place where a researcher could easily gather all the information (including both images and data) that pertains to a particular tropical cyclone or an ocean basin. The lack of such an organized hurricane information system presents a significant barrier in the advancement of our understanding and modeling of the physical processes that govern tropical cyclone genesis and evolution. To address this need, we have developed a tropical cyclone information system which includes a comprehensive set of multiparameter observations and model output that are relevant to both the large-scale and the storm-scale processes in the atmosphere and in the ocean. Our tropical cyclone database, analysis tools and web portal prototype have several unique features that are described in detail in a companion paper titled “The JPL Tropical Cyclone Information System: Design and Implementation” by Brian Knosp et al..

In this presentation, we will illustrate how the information system can be used for hurricane research and applications. Specifically, we will use the hurricane observations to evaluate the members of an ensemble forecast and to select the one that compares best to observations. Operational hurricane forecasting agencies such as the National Hurricane Center use a large number of hurricane forecasts, known as an “ensemble,” to base their issuance of hurricane watches and warnings. To date, ensembles of hurricane tracks are used to yield (i) probabilistic guidance of hurricane force winds over a certain area of coastline and (ii) an estimate of the confidence in a forecast. With a new ensemble of high-resolution model forecasts, these principles could also be extended to prediction of hurricane intensity and rainfall. However, the careful construction of an ensemble is necessary. We will compare and contrast high-resolution Weather Research and Forecasting (WRF) model simulations with different physical parameterizations and assumptions. The evaluation of forecast errors in WRF forecasts will lead us to determine those parameterizations that yield a realistic forecast and those parameterizations that do not. Microphysical processes and their representation in hurricane models are of crucial importance for accurately simulating hurricane intensity and evolution since they represent the phase changes of the water and the associated hydrometeor production and latent heat release that take place during the convective process. The buoyancy of the air, generated by the released latent heat, drives the vertical motion and determines the storm's intensity. The vertical distribution of the latent heat source determines the vertical structure of the storm and its interaction with the large-scale environment, thus affecting its track. The accurate model representation of the microphysical processes becomes increasingly important when running high-resolution numerical models that should properly reflect the convective processes in the hurricane eyewall. We will focus on the uncertainty that is created by the microphysical parameterizations. Each member of the ensemble will represent a realization with different microphysical assumptions. We will also address the importance of model resolution.

We envision that the developed tropical cyclone information system will help advance the understanding, modeling and prediction of hurricane genesis and intensity changes by providing a means to diagnose and monitor the storm structure and evolution and to address the interplay between the different important processes. Such knowledge will have an impact on: i) building and testing hypotheses; ii) validating models; iii) providing data for assimilation in the new generation weather models that can assimilate and run at high resolution; iv) creating a climate record to answer questions regarding how climate change affects hurricane frequency, size and intensity; v) determining what scientifically important measurements are still missing.

The work reported here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

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