Preprints
https://doi.org/10.5194/sp-2024-10
https://doi.org/10.5194/sp-2024-10
01 Oct 2024
 | 01 Oct 2024
Status: this preprint is currently under review for the journal SP.

Improving Accuracy and providing Uncertainty Estimations: Ensemble Methodologies for Ocean Forecasting

Ibrahim Hoteit, Eric Chassignet, and Mike Bell

Abstract. Ensemble forecasting has emerged as an essential approach for addressing the uncertainties inherent in ocean prediction, offering a probabilistic framework that enhances accuracy of both short-term and long-range forecasts. By more effectively addressing the intrinsic chaotic nature of mesoscale and sub-mesoscale variability, ensemble methods offer critical insights into forecast errors and improve the reliability of predictions. This paper reviews the ensemble methodologies currently used in ocean forecasting, including techniques borrowed from weather prediction like virtual ensembles and Monte Carlo methods. It also explores the latest advancements in ensemble data assimilation, which have been successfully integrated into both ocean general circulation models and operational forecasting systems. These advancements enable more accurate representation of forecast uncertainties (error-of-the-day) by sampling perturbations conditioned on available observations. Despite the progress made, challenges remain in fully realizing the potential of ensemble forecasting, particularly in developing tools for analyzing results and incorporating them into decision-making processes. This paper highlights the crucial role of ensemble forecasting in improving ocean predictions and advocates for its wider adoption in operational systems.

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Ibrahim Hoteit, Eric Chassignet, and Mike Bell

Status: open (until 26 Nov 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on sp-2024-10', Anonymous Referee #1, 07 Oct 2024 reply
Ibrahim Hoteit, Eric Chassignet, and Mike Bell
Ibrahim Hoteit, Eric Chassignet, and Mike Bell

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Short summary
This paper explores how using multiple predictions instead of just one can improve ocean forecasts and help prepare for changes in ocean conditions. By combining different forecasts, scientists can better understand the uncertainty in predictions, leading to more reliable forecasts and better decision-making. This method is useful for responding to hazards like oil spills, improving climate forecasts, and supporting decision-making in fields like marine safety and resource management.
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