Study showing how small errors in observations and models can impact predictability published in Chaos – Hurricane Research Division
A study conducted using a simple chaotic system found that both model error and initial condition errors have significant impacts on predictability. The findings suggest that small changes to the equations can influence the predictability limit, which could have implications for the design of computer forecast models. In addition, the study showed that the common expectation of increasing the predictability limit through improved initial conditions is not valid if the equations themselves are even slightly in error. The research supports the necessity of focusing not only on improving observations but also on refining the models themselves in order to enhance the effectiveness of weather forecasts. Multiple ways to design ensemble forecasting systems were also discussed, emphasizing the importance of understanding how initial and model errors interact.
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