Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-5957-2021
https://doi.org/10.5194/gmd-14-5957-2021
Model description paper
 | 
04 Oct 2021
Model description paper |  | 04 Oct 2021

SymPKF (v1.0): a symbolic and computational toolbox for the design of parametric Kalman filter dynamics

Olivier Pannekoucke and Philippe Arbogast

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Latest update: 24 May 2024
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Short summary
This contributes to research on uncertainty prediction, which is important either for determining the weather today or estimating the risk in prediction. The problem is that uncertainty prediction is numerically very expensive. An alternative has been proposed wherein uncertainty is presented in a simplified form with only the dynamics of certain parameters required. This tool allows for the determination of the symbolic equations of these parameter dynamics and their numerical computation.