Abstract
Abstract. In this paper, a generic implementation approach is presented, with the aim of transforming a deterministic ocean model (like NEMO) into a probabilistic model. With this approach, several kinds of stochastic parameterizations are implemented to simulate the non-deterministic effect of unresolved processes, unresolved scales and unresolved diversity. The method is illustrated with three applications, showing that uncertainties can produce a major effect in the circulation model, in the ecosystem model, and in the sea ice model. These examples show that uncertainties can produce an important effect in the simulations, strongly modifying the dynamical behaviour of these three components of ocean systems.
Highlights
The first requirement of an ocean model is the definition of the system that the model is going to represent
A few exploratory studies have attempted to explicitly simulate uncertainties in realistic dynamical ocean models: this has been done for the ocean circulation (Brankart, 2013), for the ocean ecosystem (Arhonditsis et al, 2008), and for the sea ice dynamics (Juricke et al, 2013). These preliminary studies already show that uncertainties can play a major role in dominant dynamical behaviours of marine systems. In line with these studies, the objective of this paper is to propose a generic implementation of these stochastic parameterizations, and to investigate several applications in which the randomness of the ocean system may be an important issue
The third application is an attempt to reproduce the parameterization developed in Juricke et al (2013) in our ocean model using the generic implementation presented in Sect. 2, and to illustrate the randomness that is generated in the interannual variability of sea ice thickness
Summary
The first requirement of an ocean model is the definition of the system that the model is going to represent. The future evolution of A does depend on its own dynamics and initial condition, and on the interactions between A and B This means that the only two ways of obtaining a deterministic model for A are either to assume that the evolution of B is known (as is usually done for the atmosphere in stand-alone ocean models) or to assume that the effect of B can be parameterized as a function of what happens in A (as is usually done for unresolved scales and unresolved diversity). These preliminary studies already show that uncertainties can play a major role in dominant dynamical behaviours of marine systems In line with these studies, the objective of this paper is to propose a generic implementation of these stochastic parameterizations, and to investigate several applications in which the randomness of the ocean system may be an important issue. The third application (sea ice model) is an attempt to reproduce the parameterization developed in Juricke et al (2013) in our ocean model using the generic implementation presented in Sect. 2, and to illustrate the randomness that is generated in the interannual variability of sea ice thickness
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
