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Uncertainty forecast from 3-D super-ensemble multi-model combination: validation and calibration
Mourre, B.; Chiggiato, J.; Lenartz, F.; Rixen, M. (2012). Uncertainty forecast from 3-D super-ensemble multi-model combination: validation and calibration. Ocean Dynamics 62(2): 283-294. dx.doi.org/10.1007/s10236-011-0504-6
In: Ocean Dynamics. Springer-Verlag: Berlin; Heidelberg; New York. ISSN 1616-7341; e-ISSN 1616-7228
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| Author keywords |
Coastal operational oceanography; Ocean temperature; Uncertaintyforecast; Super-ensemble; Decision support; Ligurian Sea; REP10 |
| Auteurs | | Top |
- Mourre, B.
- Chiggiato, J.
- Lenartz, F.
- Rixen, M.
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| Abstract |
Measurements collected during the Recognized Environmental Picture 2010 experiment (REP10) in the Ligurian Sea are used to evaluate 3-D super-ensemble (3DSE) 72-hour temperature predictions and their associated uncertainty. The 3DSE reduces the total Root-Mean-Square Difference by 12 and 32% respectively with reference to the ensemble mean and the most accurate of the models when comparing to regularly distributed surface temperature data. When validating against irregularly distributed in situ observations, the 3DSE, ensemble mean and most accurate model lead to similar scores. The 3DSE temperature uncertainty estimate is obtained from the product of a posteriori model weight error covariances by an operator containing model forecast values. This uncertainty prediction is evaluated using a criterion based on the 2.5th and 97.5th percentiles of the error distribution. The 3DSE error is found to be on average underestimated during the forecast period, reflecting (i) the influence of ocean dynamics and (ii) inaccuracies in the a priori weight error correlations. A calibration of the theoretical 3DSE uncertainty is proposed for the REP10 scenario, based on a time-evolving amplification coefficient applied to the a posteriori weight error covariance matrix. This calibration allows the end-user to be confident that, on average, the true ocean state lies in the -2/+2 3DSE uncertainty range in 95% of the cases. |
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