Growth of Errors in Weather Prediction with Use of Low-dimensional Atmospheric Model

Abstract

The paper studies low-dimensional atmospheric model introduced by Lorenz in 1996. The relevance and common properties of the model are discussed with regard to chaotic behavior identification under selected conditions.

For this purpose, Lyapunov exponents are estimated and compared with the ensemble prediction approach. The comparison discovers different initial error growth of these methods.

The consequences of the results for this and for more complex models are discussed.

Keywords

• Growth
• Errors
• Weather
• Prediction
• with
• Use
• Low-dimensional
• Atmospheric
• Model