Impact of uncertainties in atmospheric boundary conditions on ocean model solutions. (April 2016)

• Record Type: Journal Article
• Authors: Chaudhuri, Ayan H.; Ponte, Rui M.; Forget, Gael
• Is Part Of: Ocean modelling. Volume 100(2016:Apr.)
• Page Start: 96
• Page End: 108
• Publication Date: 2016-04
• Subjects: Reanalysis -- Atmospheric uncertainty -- Global ocean modeling; Oceanography -- Periodicals; Océanographie -- Périodiques; Oceanography; Periodicals; 551.46
• DOI: 10.1016/j.ocemod.2016.02.003
• Languages: English
• ISSNs: 1463-5003

Abstract

Highlights: We quantify differences in ocean simulations due to uncertainties in atmospheric forcing. Differences are akin to model-data misfits in the tropics but smaller at high latitudes. Differences are largest near the surface but can propagate to depths of 4000 m. Differences are mainly dominated by large spatial scales and specific time scales. Abstract: We quantify differences in ocean model simulations derived solely from atmospheric uncertainties and investigate how they relate to overall model errors as inferred from comparisons with data. For this purpose, we use a global configuration of the MITgcm to simulate 4 ocean solutions for 2000–2009 using 4 reanalysis products (JRA-25, MERRA, CFSR and ERA-Interim) as atmospheric forcing. The simulations are compared against observations and against each other for selected variables (temperature, sea-level, sea-ice, streamfunctions, meridional heat and freshwater transports). Forcing-induced differences are comparable in magnitude to model-observation misfits for most near-surface variables in the tropics and sub-tropics, but typically smaller at higher latitudes and polar regions. Forcing-derived differences are expectedly largest near the surface and mostly limited to the upper 1000 m but can also be seen as deep as 4000 m, especially in regions of deep water formation. Errors are not necessarily local in nature and can be advected to different basins. Results indicate that while forcing adjustments might suffice in optimization procedures of near-surface fields and at low-to-mid latitudes, other control parameters are likely needed elsewhere. Forcing-induced differences can be dominated by large spatial scales and specific time scales (e.g. annual), and thus appropriate error covariances in space and time need to be considered in optimization methodologies.