OS1.12 | Random intrinsic variability and uncertainties in the ocean: characteristics and implications.
EDI
Random intrinsic variability and uncertainties in the ocean: characteristics and implications.
Co-organized by NP2
Convener: Thierry Penduff | Co-conveners: Lin Lin, Sally Close, Takaya Uchida

Theoretical and model studies show that the non-linear ocean spontaneously generates a strong, multi-scale random intrinsic variability. Equivalently, uncertainties in initial ocean states tend to grow and strongly affect the simulated variability up to multidecadal and basin scales, with or without coupling to the atmosphere. In addition, ocean simulations require both the use of subgrid-scale parameterizations that crudely mimic unresolved processes, and the calibration of the parameters associated with these parameterizations. In this context of multiple uncertainties, oceanographers are increasingly adopting ensemble simulation strategies, probabilistic analysis methods, and developing stochastic parameterizations for modeling and understanding the ocean variability in response to (or in interaction with) the atmospheric evolution.

Presentations are solicited about the conception and analysis of ocean ensemble simulations, the characterization of ocean model uncertainties, and the development of parameterizations for ocean models. The session will also cover the dynamics and structure of intrinsic ocean variability, its relationship with atmospheric variability, and the use of adequate concepts (based on e.g. dynamical systems, information, or other theories) for the investigation of oceanic variability. We welcome as well studies about the propagation of intrinsic ocean variability towards other components of the climate system, about its implications regarding ocean predictability, operational forecasts, detection and attribution of climate signals, climate simulations and projections.

Theoretical and model studies show that the non-linear ocean spontaneously generates a strong, multi-scale random intrinsic variability. Equivalently, uncertainties in initial ocean states tend to grow and strongly affect the simulated variability up to multidecadal and basin scales, with or without coupling to the atmosphere. In addition, ocean simulations require both the use of subgrid-scale parameterizations that crudely mimic unresolved processes, and the calibration of the parameters associated with these parameterizations. In this context of multiple uncertainties, oceanographers are increasingly adopting ensemble simulation strategies, probabilistic analysis methods, and developing stochastic parameterizations for modeling and understanding the ocean variability in response to (or in interaction with) the atmospheric evolution.

Presentations are solicited about the conception and analysis of ocean ensemble simulations, the characterization of ocean model uncertainties, and the development of parameterizations for ocean models. The session will also cover the dynamics and structure of intrinsic ocean variability, its relationship with atmospheric variability, and the use of adequate concepts (based on e.g. dynamical systems, information, or other theories) for the investigation of oceanic variability. We welcome as well studies about the propagation of intrinsic ocean variability towards other components of the climate system, about its implications regarding ocean predictability, operational forecasts, detection and attribution of climate signals, climate simulations and projections.