Characterization of the long-time and short-time predictability of low-order models of the atmosphere

Details Characterization of the long-time and short-time predictability of low-order models of the atmosphere Characterization of the long-time and short-time predictability of low-order models of the atmosphere

1999-05-08

arxiv.org/abs/chao-dyn/9905009v1

Nonlinear Sciences

Chaotic Dynamics

To appear in Journal of the Atmospheric Sciences

Scientific paper

10.1175/1520-0469(1999)056<3495:

Methods to quantify predictability properties of atmospheric flows are proposed. The ``Extended Self Similarity'' (ESS) technique, recently employed in turbulence data analysis, is used to characterize predictability properties at short and long times. We apply our methods to the low-order atmospheric model of Lorenz (1980). We also investigate how initialization procedures that eliminate gravity waves from the model dynamics influence predictability properties.

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