Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty
Quarterly Journal of the Royal Meteorological Society Wiley 144:715 (2018) 1947-1964
Abstract:
Accurate forecasts of the ocean state and the estimation of forecast uncertainties are crucial when it comes to providing skilful seasonal predictions. In this study we analyse the predictive skill and reliability of the ocean component in a seasonal forecasting system. Furthermore, we assess the effects of accounting for model and observational uncertainties. Ensemble forcasts are carried out with an updated version of the ECMWF seasonal forecasting model System 4, with a forecast length of ten months, initialized every May between 1981 and 2010. We find that, for essential quantities such as sea surface temperature and upper ocean 300 m heat content, the ocean forecasts are generally underdispersive and skilful beyond the first month mainly in the Tropics and parts of the North Atlantic. The reference reanalysis used for the forecast evaluation considerably affects diagnostics of forecast skill and reliability, throughout the entire ten‐month forecasts but mostly during the first three months. Accounting for parametrization uncertainty by implementing stochastic parametrization perturbations has a positive impact on both reliability (from month 3 onwards) as well as forecast skill (from month 8 onwards). Skill improvements extend also to atmospheric variables such as 2 m temperature, mostly in the extratropical Pacific but also over the midlatitudes of the Americas. Hence, while model uncertainty impacts the skill of seasonal forecasts, observational uncertainty impacts our assessment of that skill. Future ocean model development should therefore aim not only to reduce model errors but to simultaneously assess and estimate uncertainties.Eddy-mixing entropy and its maximization in forced-dissipative geostrophic turbulence
Journal of Statistical Mechanics: Theory and Experiment
IOP Publishing 2018:2018 (2018) 073206
Abstract:
An equilibrium, or maximum entropy, statistical mechanics theory can be derived for ideal, unforced and inviscid, geophysical flows. However, for all geophysical flows which occur in nature,forcing and dissipation play a major role. Here, a study of eddy-mixing entropy in a forced dissipative barotropic ocean model is presented. We heuristically investigate the temporal evolution of eddy-mixing entropy, as defined for the equilibrium theory, in a strongly forced and dissipative system. It is shown that the eddy-mixing entropy provides a descriptive tool for understanding three stages of the turbulence life cycle: growth of instability; formation of large scale structures; and steady state fluctuations. The fact that the eddy-mixing entropy behaves in a dynamically balanced way is not a priori clear and provides a novel means of quantifying turbulent disorder in geophysical flows. Further, by determining the relationship between the time evolution of entropy and the maximum entropy principle, evidence is found for the action of this principle in a forced dissipative flow. The maximum entropy potential vorticity statistics are calculated for the flow and are compared with numerical simulations. Deficiencies of the maximum entropy statistics are discussed in the context of the mean-field approximation for energy. This study highlights the importance of entropy and statistical mechanics in the study of geostrophic turbulence.The signature of oceanic processes in decadal extratropical SST anomalies
Geophysical Research Letters John Wiley & Sons 45:15 (2018) 7719-7730
Abstract:
The relationship between decadal SST and turbulent heat‐fluxes is assessed and used to identify where oceanic processes play an important role in extratropical decadal SST variability. In observational datasets and coupled climate model simulations from the CMIP5 archive, positive correlations between upward turbulent heat flux and SSTs indicate an active role of oceanic processes over regions in the North Atlantic, Northwest Pacific, Southern Pacific and Southern Atlantic. The contrasting nature of oceanic influence on decadal SST anomalies in the Northwest Pacific and North Atlantic is identified. Over the Northwest Pacific, SST anomalies are consistent with changes in the horizontal wind‐driven gyre circulation on timescales of between 3‐7 years, in both the observations and models. Over the North Atlantic, SST anomalies are also preceded by atmospheric circulation anomalies, though the response is stronger at longer timescales ‐ peaking at around 20‐years in the observations and at around 10‐years in the models.Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study
Climate Dynamics (2018) 1-19
Abstract:
© 2018 Springer-Verlag GmbH Germany, part of Springer Nature A suite of statistical linear inverse models (LIMs) are used to understand the remote and local SST variability that influences SST predictions over the North Pacific region. Observed monthly SST anomalies in the Pacific are used to construct different regional LIMs for seasonal to decadal predictions. The seasonal forecast skills of the LIMs are compared to that from three operational forecast systems in the North American Multi-Model Ensemble (NMME), revealing that the LIM has better skill in the Northeastern Pacific than NMME models. The LIM is also found to have comparable forecast skill for SST in the Tropical Pacific with NMME models. This skill, however, is highly dependent on the initialization month, with forecasts initialized during the summer having better skill than those initialized during the winter. The data are also bandpass filtered into seasonal, interannual and decadal time scales to identify the relationships between time scales using the structure of the propagator matrix. Moreover, we investigate the influence of the tropics and extra-tropics in the predictability of the SST over the region. The Extratropical North Pacific seems to be a source of predictability for the tropics on seasonal to interannual time scales, while the tropics enhance the forecast skill for the decadal component. These results indicate the importance of temporal scale interactions in improving the predictions on decadal timescales. Hence, we show that LIMs are not only useful as benchmarks for estimates of statistical skill, but also to isolate contributions to the forecast skills from different timescales, spatial scales or even model components.The impact of tropical precipitation on summertime Euro-Atlantic circulation via a circumglobal wave-train
Journal of Climate American Meteorological Society 31:16 (2018) 6481-6504