Extended Abstract (668K)P1.1
Mesoscale Predictability Estimated through Explicit Simulation of Moist Baroclinic Waves
Zhe-Min Tan, Nanjing University, Nanjing, China; and R. Rotunno, C. Snyder, and F. Zhang
Recent papers by Zhang, Snyder and Rotunno (2002a, 2002b) focussing on the "surprise" snowstorm of 24-25 January 2000 demonstrated the influence of initial errors of small scale and small amplitude on that storm. Such errors grew rapidly, appearing first as differences in the timing and placement of (marginally resolved) convective cells and then spreading upscale to alter the shape and location of the surface cyclone in the 36-hour forecast.
The growth of error from convective or smaller scales places a fundamental limit on the predictability of larger scales, as first suggested by Lorenz (1969). In order to generalize the results from the "suprise" snowstorm and to understand better the mechanisms by which error spreads from convective to synoptic scales, we are performing idealized simulations of moist baroclinic waves using the PSU/NCAR mesoscale model MM5; these simulations begin from a zonal jet in a channel to which an upper-level disturbance is added to trigger cyclogenesis. Preliminary solutions from two slightly different initial conditions show error growth that is qualitatively similar to that found in the previous case study. We are investigating the dependence of this error growth on the synoptic-scale characteristics of the flow, such as the amount and spatial extent of potential instability. The impact of model resolution and parameterizations on the error growth will also be further investigated and will be presented in the conference.
Poster Session 1, Weather Analysis, Forecasting and Numerical Prediction
Monday, 12 August 2002, 3:00 PM-4:30 PM
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