85th AMS Annual Meeting

Thursday, 13 January 2005
Flow and Regime dependent mesoscale predictability
Fuqing Zhang, Texas A&M University, College Station, TX; and C. Snyder and R. Rotunno
Although the synoptic-scale evolution of the typical midlatitude weather system is relatively well-forecasted, numerical weather-prediction models still have difficulties in forecasting the “mesoscale details” which are of most concern to the typical user of the model’s forecast. It is of great interest to assess the predictability of these mesoscale weather systems, particularly with respect to the amount and spatial distribution of the associated precipitation. This study seeks to estimate the predictability of mesoscale features embedded within different synoptic-scale flow regimes and to identify key physical processes that control the limit of predictability at the mesoscale through explicit simulations of idealized moist baroclinic waves and case studies of high-impact weather events. Understanding of the limit of mesoscale predictability and the associated error growth dynamics is essential for setting up expectations and priorities for advancing deterministic mesoscale forecasting and for providing guidance on the design, implementation and application of short-range ensemble prediction systems.

There were dramatic differences between operational forecasts of two winter events, with the “Storm of the Century (SOC)” of March 1993 being one of the most successful heavy snow and blizzard forecasts ever for a major winter storm while the “surprise” snowstorm of January 2000 having very limited predictability at all scales. Preliminary experiments suggested that the error growth rate in the “SOC” is smaller than that in the “surprise” snowstorm of 2000. Ongoing research is to determine key dynamical differences in the flows that lead to different mesoscale error growth dynamics between two major extratropical cyclogenesis events and to generalize results of flow-dependent mesoscale predictability concluded from real case studies through explicit simulations of idealized moist baroclinic waves. The study of mesoscale predictability is further extended to an extreme warm-season flooding event in south-central Texas of July 2002. This warm-season event is subtropical in nature with strong conditional instability but weak baroclinicity in strong contrast to mid-latitude extratropical cyclones. It is found that the initial error growth is rapid and occurs at the convective scales but the subsequent upscale growth is relatively weak, perhaps because of the weak subsynoptic features. Through these case studies and idealized simulations, a multistage conceptual model, in which moist processes impose fundamental limits on mesoscale predictability but the error-growth dynamics is strongly dependent on the larger-scale background flow and its attendant dynamics, is being tested.

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