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\begin{document}

\title{Can artificial intelligence-based weather prediction models simulate the
butterfly effect?}



\author[1]{Tobias Selz}%
\author[2]{George C. Craig}%
\affil[1]{Deutsches Zentrum für Luft- und Raumfahrt}%
\affil[2]{Institute of Meteorology - University of Munich}%


\vspace{-1em}



  
  \date{June 05, 2024}


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\begin{abstract}
We investigate error growth from small-amplitude initial condition
perturbations, simulated with a recent artificial intelligence-based
weather prediction model. From past simulations with standard
physically-based numerical models as well as from theoretical
considerations it is expected that such small-amplitude initial
condition perturbations would grow very fast initially. This fast growth
then sets a fixed and fundamental limit to the predictability of
weather, a phenomenon known as the butterfly effect. We find however,
that the AI-based model completely fails to reproduce the rapid initial
growth and hence would suggest an infinite predictability of the
atmosphere. In contrast, if the initial perturbations are large and
comparable to current uncertainties in the estimation of the initial
state, the AI-based model basically agrees with physically-based
simulations, although some deficits are still present.%
\end{abstract}%



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