Articles | Volume 11, issue 10
https://doi.org/10.5194/gmd-11-4011-2018
https://doi.org/10.5194/gmd-11-4011-2018
Methods for assessment of models
 | 
05 Oct 2018
Methods for assessment of models |  | 05 Oct 2018

Data assimilation cycle length and observation impact in mesoscale ocean forecasting

Paul Sandery

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AR by Anna Mirena Feist-Polner on behalf of the Authors (14 Aug 2018)  Author's response
ED: Publish as is (28 Aug 2018) by Paul Halloran
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Short summary
This article compares global mesoscale ocean forecasts with different data assimilation cycle lengths. Mean absolute increment is used to quantify differences in the overall impact of observations. Greater observation impact does not necessarily improve a forecast system. Experiments show a 1-day cycle generates improved 7-day forecasts when compared to a 3-day cycle. Cycle length is an important choice that influences system bias and predictability.