Dynamics, statistics and predictability of a simple limited-area forecasting model

A canonical model describing the instability of plane wave solutions toward inhomogeneous long wave fluctuations emulating mesoscale atmospheric variability is used to analyze the performance of nested limited-area forecasting models. Comparative studies between a reference fine grid ‘‘perfect’’ model and the ones provided, successively, by a globally coarse and a nested, fine scale, limited-area one are carried out. The statistical properties of the relevant fields are first analyzed, and an optimal size for which the deviations between the ‘‘perfect’’ model and the limited-area one are minimized is identified. Predictability analysis reveals that, although the Lyapunov exponents of the ‘‘perfect’’ model are smaller than those of the globally coarse model, operational error growth proceeds eventually faster in the nested limited-area model than in the globally coarse one.