Predictability Characteristics of Global and Limited Area Models

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9408047 Paegle "Predictability Characteristics of Global and Limited Area Models" Under this award, Dr. Paegle will continue his investigations of atmospheric predictability, and in particular, the effects of uncertainties in the initial conditions, both local and remote, on numerical predictions. Studies will be carried out for global and limited-area models. Specifically, he will: 1) conduct experiments with a variable resolution global model, using resolutions spanning three orders of magnitude, to ascertain theoretical and ppactical limits of predictability and how the limits depend on local, remote, and global uncertainties. The results should have practical implications for the design of numerical models and observing systems. 2) perform experiments with a high resolution local model designed to assess the "value- added" by resolution enhancement relative to the uncertainty associated with imperfect boundary conditions provided from operational forecasts used to initialize the model. The goal is to quantify the relative forecast improvement which can be realized within the inner (local) model domain from improvements in the forecast skill of the outer (regional or global) model that supplies the boundary conditions. The results of this research have obvious potential for improving numerical weather prediction on both short and longer time scales. The Mesoscale Dynamic Meteorology and Large-scale Dynamic Meteorology Programs will share in the support of this award. ***