Articles | Volume 24, issue 4
https://doi.org/10.5194/hess-24-1677-2020
https://doi.org/10.5194/hess-24-1677-2020
Research article
 | 
08 Apr 2020
Research article |  | 08 Apr 2020

On the assimilation of environmental tracer observations for model-based decision support

Matthew J. Knowling, Jeremy T. White, Catherine R. Moore, Pawel Rakowski, and Kevin Hayley

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Latest update: 28 Mar 2024
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Short summary
The incorporation of novel and diverse data sources into predictive models is expected to improve the reliability of model forecasts. This study critically and rigorously explores the extent to which this expectation holds given the imperfect nature of numerical models (and therefore their compromised ability to appropriately assimilate information-rich data). We show that environmental tracer observations may be of variable benefit in reducing forecast uncertainty and may induce forecast bias.