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dc.contributor.authorSanikommu, Siva Reddy
dc.contributor.authorToye, Habib
dc.contributor.authorZhan, Peng
dc.contributor.authorLangodan, Sabique
dc.contributor.authorKrokos, Georgios
dc.contributor.authorKnio, Omar
dc.contributor.authorHoteit, Ibrahim
dc.date.accessioned2020-07-16T09:03:17Z
dc.date.available2020-07-16T09:03:17Z
dc.date.issued2020-08-19
dc.date.submitted2019-09-04
dc.identifier.citationSanikommu, S., Toye, H., Zhan, P., Langodan, S., Krokos, G., Knio, O., & Hoteit, I. (2020). Impact of Atmospheric and Model Physics Perturbations On a High-Resolution Ensemble Data Assimilation System of the Red Sea. Journal of Geophysical Research: Oceans. doi:10.1029/2019jc015611
dc.identifier.issn2169-9275
dc.identifier.issn2169-9291
dc.identifier.doi10.1029/2019jc015611
dc.identifier.urihttp://hdl.handle.net/10754/664239
dc.description.abstractThe Ensemble Adjustment Kalman Filter (EAKF) of the Data Assimilation Research Testbed (DART) is implemented to assimilate observations of satellite sea surface temperature, altimeter sea surface height and in situ ocean temperature and salinity profiles into an eddy-resolving 4 km Massachusetts Institute of Technology general circulation model (MITgcm) of the Red Sea. We investigate the impact of three different ensemble generation strategies (1) Iexp – uses ensemble of ocean states to initialize the model on 1st January, 2011 and inflates filter error covariance by 10%, (2) IAexp – adds ensemble of atmospheric forcing to Iexp , and (3) IAPexp – adds perturbed model physics to IAexp . The assimilation experiments are run for one year, starting from the same initial ensemble and assimilating data every three days. Results demonstrate that the Iexp mainly improved the model outputs with respect to assimilation-free MITgcm run in the first few months, before showing signs of dynamical imbalances in the ocean estimates, particularly in the data-sparse subsurface layers. The IAexp yielded substantial improvements throughout the assimilation period with almost no signs of imbalances, including the subsurface layers. It further well preserved the model mesoscale features resulting in an improved forecasts for eddies, both in terms of intensity and location. Perturbing model physics in IAPexp slightly improved the forecast statistics and also the placement of basin-scale eddies. Increasing hydrographic coverage further improved the results of IAPexp compared to IAexp in the subsurface layers. Switching off multiplicative inflation in IAexp and IAPexp leads to further improvements, especially in the subsurface layers.
dc.publisherAmerican Geophysical Union (AGU)
dc.relation.urlhttps://onlinelibrary.wiley.com/doi/abs/10.1029/2019JC015611
dc.rightsArchived with thanks to Journal of Geophysical Research: Oceans
dc.titleImpact of Atmospheric and Model Physics Perturbations On a High-Resolution Ensemble Data Assimilation System of the Red Sea
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentEarth Fluid Modeling and Prediction Group
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalJournal of Geophysical Research: Oceans
dc.eprint.versionPost-print
dc.identifier.arxivid2002.01825
kaust.personSanikommu, Siva Reddy
kaust.personToye, Habib
kaust.personZhan, Peng
kaust.personLangodan, Sabique
kaust.personKrokos, Georgios
kaust.personKnio, Omar
kaust.personHoteit, Ibrahim
dc.date.accepted2020-07-06
refterms.dateFOA2020-07-16T09:04:16Z
dc.date.published-online2020-08-19
dc.date.published-print2020-08
dc.date.posted2020-02-05


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