Toward an Uncertainty Budget for a Coastal Ocean Model

Abstract

Estimates of three components of an uncertainty budget for a coastal ocean model in a wind-forced regime are made based on numerical simulations. The budget components behave differently in the shelf regime, inshore of the 200-m isobath, and the slope-interior regime, between the 200-m isobath and a fixed longitude (1268W) that is roughly 150 km offshore. The first of the three budget components is an estimate of the uncertainty in the ocean state given only a known history of wind stress forcing, with errors in the wind forcing estimated from differences between operational analyses. It is found that, over the continental shelf, the response to wind forcing is sufficiently strong and deterministic that significant skill in estimating shelf circulation can be achieved with knowledge only of the wind forcing, and no ocean data, for wind fields with these estimated errors. The second involves initial condition error and its influence on uncertainty, including both error growth with time from well-known initial conditions and error decay with time from poorly known initial conditions but with well-known wind forcing. The third component is that of boundary condition error and its influence on the interior solutions, including the dependence of that influence on the specific location along the boundary of the boundary condition error. Boundary condition errors with amplitude comparable to the root-mean-square variability at the boundary lead eventually to errors equal to the root-mean-square variability in the slope-interior regime, and somewhat smaller errors in the shelf regime. Covariance estimates based on differences of the wind-forced solutions from the ensemble mean are not dramatically different from those based on the full fields, and do not show strong state dependence.

Sensitivity and uncertainty analysis of model hypoxia estimates for the Texas‐Louisiana shelf

“…Previous studies of model uncertainty and sensitivity have focused on physical ocean models [ Lermusiaux , ; Kim et al . ; Thacker et al . ].…”

“…[4] Previous studies of model uncertainty and sensitivity have focused on physical ocean models [Lermusiaux, 2006;Kim et al, 2010;Thacker et al, 2012]. Sensitivity analyses are also commonly found in the field of ecosystem modelling [Clancy et al, 2010;Makler-Pick et al, 2011;Gibson and Spitz, 2011;Melbourne-Thomas et al, 2011] but not typically for coupled three-dimensional biologicalphysical models.…”

Estimating uncertainties on a Gulf Stream mixed-layer heat budget from stochastic modeling

“…Alves and Robert, 2005;Leeuwenburgh, 2005). Similarly, in sensitivity studies, such as Lucas et al (2008) and Kim et al (2011), it is assumed that the errors on the atmospheric reanalyses used to force the ocean model can be estimated from the differences between reanalyses. Other options include building atmospheric perturbations from a Gaussian distribution with given spatial and temporal scales (AndreuBurillo et al, 2002).…”

“…There is however a growing interest in the oceanographic community to provide budget for uncertainties on simulated or forecasted ocean quantities (e.g. Kim et al, 2011).…”

Characterisation of errors of a regional model of the Bay of Biscay in response to wind uncertainties: a first step toward a data assimilation system suitable for coastal sea domains

“…is not yet widespread in regional and coastal systems 1,2 , it aims to provide best estimates of marine variables based firstly on the information at hand, namely data and model outputs, and secondly on error estimates of those pieces of information.…”