A Diagnostic Phase Space for the Structural State of Pre-genesis Tropical Convective Systems

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Wednesday, 5 February 2014
Hall C3 (The Georgia World Congress Center )
Charles N. Helms, SUNY Albany, Albany, NY; and J. P. Dunion and L. F. Bosart

A multifaceted phase space is being developed for use in both research and operational applications pertaining to pre-genesis tropical convective systems. The forecasting community has greatly benefited from the use of phase spaces such as the Hart Cyclone Phase Space (describing the transition from tropical cyclone to extratropical cyclone) and the Real-time Multivariate MJO phase space (RMM; describing the state of the Madden-Julian Oscillation). In addition to forecasting applications, the RMM phase space has seen widespread use in both tropical and non-tropical research applications. While these examples demonstrate that the concept of using a phase space in research or forecasting is not a new one, this is the first attempt, to the authors' knowledge, to construct a phase space designed to track the structure of tropical convective systems prior to cyclogenesis.

The phase space is constructed so as to identify the current state of the structure and immediate environment of pre-genesis tropical convective systems. The immediate research application of this tool is to produce homogeneous subsets of cases for compositing. This approach to compositing retains the positive characteristics of both case studies and composite studies (the detailed analysis and representativeness, respectively) while minimizing the drawbacks of each (the lack of representativeness and loss of highly variable details, respectively). Additionally, insight on the variability of the system structural evolution can be gained by examining the variations in the trajectories through the phase space. Applying the pre-genesis phase space in real-time using operational models will provide a visualization of the current and forecasted state of a tropical convective system. Furthermore, application to model ensemble output presents the opportunity to examine the uncertainty in the forecasted structure and could potentially pave the way for future predictability studies regarding the structure of these systems.