Oceanic stochastic parametrizations in a seasonal forecast system

TL;DR

This study evaluates the effects of three stochastic parametrizations on ocean model forecasts over seasonal timescales, highlighting the dominant role of atmospheric forcing in ensemble spread and the limited impact of current schemes on forecast error.

Contribution

It provides a comparative analysis of stochastic parametrizations in ocean models, revealing their varying impacts on forecast spread and bias, and suggests directions for developing more effective schemes.

Findings

SPPT scheme significantly increases ensemble spread in key regions.

Atmospheric forcing is the main source of ocean variability.

Current stochastic schemes do not substantially reduce forecast error.

Abstract

We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.