The ocean displays variability of physical parameters across a very wide range of spatial and temporal scales, from minutes to centuries and millennia and from centimeters to the dimension of ocean basins (Benway et al., 2019). As shown in Figure 3.4, this feature makes the ocean a greatly complex system, characterized by interactions between a great deal of processes at many different time/space scales (in which small scales can affect large ones and vice versa).
Operational forecasting services, as defined in Section 3.1, typically deal with problems with a forecast horizon from hours to days, and time intervals at which the solutions are presented to users can vary from hours to minutes. Nevertheless, ocean models can be used for other purposes at longer time scales, such as seasonal prediction and climate modeling. Climate models are based on well-established physical principles, and it has been shown that they can reproduce observed features of recent climate and past climate changes.
There is considerable confidence that AOGCMs provide credible quantitative estimates of future climate change, particularly at large scales, although uncertainties still remain. As stated in the Randall et al. (2007) contribution to the Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the IPCC, there are different levels of skill in simulating the various ECVs.
Long-term climate change projections reflect how human activities and/or natural effects can alter the climate over decades and centuries. The principal driver of long-term warming is the large cumulative emission of CO2 over time from many anthropogenic sources. In this context, it is important defining scenarios, using specific time series of emissions, land use, atmospheric concentrations or radiative forcing across multiple models, which allows for coherent climate model intercomparisons and synthesis. As stated by Collins et al. (2013), for the above purpose is used information from a range of different modeling tools, from simple energy balance models to the highly complex Earth System dynamical climate models. The CMIP Phase 5 utilizes an unprecedented level of information on base projections, including the more complete representation of forcings, and has produced new RCP scenarios (i.e. RCP2.6, RCP4.5, RCP6, and RCP8.5). Thanks to the coordination of model experiments and outputs by the CMIP5 group, the World Climate Research Program and its Working Group on Climate Models have been able to step up efforts to evaluate the ability of models to simulate past and current climate and to compare future climate change projections. This ‘multi-model’ approach is now a standard technique used by the climate science community to generate and assess projections of a specific climate variable.
Substantial progress has been made in understanding the climate scales, as well as in simulating important modes of climate variability; as a consequence, the overall confidence in the capacity of models to represent important climate processes has increased. These improvements in AOGCMs are due in large part to the continuous development of the oceanic model component in recent years. There have been improvements in terms of resolution, computational methods, and parametrizations; furthermore, additional new processes have been progressively added to the ocean models used to simulate multi-year periods and climate projections, enhancing the complexity of the ocean climate model component.
As previously mentioned, ocean model resolution has increased (currently, the state-of-the-art is eddy-resolving models) and ocean climate models, especially regional models, are abandoning the ‘rigid lid’ treatment of the ocean surface that filters out some high frequency processes. New physical numerical parametrizations, including true freshwater fluxes, and/or improved river and estuary mixing schemes, better advection and mixing schemes are now widely used. All these improvements have led to the reduction of the uncertainty associated with the use of less sophisticated parametrizations. Finally, it should be mentioned that there has been substantial progress in developing the cryospheric components of AOGCMs. Almost all state-of-the-art AOGCMs now include sea ice, with more elaborate sea ice dynamics, while many also include several sea ice thickness categories with relatively advanced thermodynamics and rheology.
Efforts to enhance the quality of climate projections are always related to the computational resources dedicated to the ocean modeling component, but currently there is no consensus on the optimal way to divide computer resources among the following components:
- Finer numerical grids, which allow for better simulations;
- Greater numbers of ensemble members, which allow for better statistical estimates of uncertainty;
- Inclusion of a more complete set of processes (e.g. carbon feedbacks).
Finally, it has to be mentioned that there is also an important ongoing activity in terms of ocean climate regionalization, which has been developed in the framework of national and regional climate services initiatives with special emphasis on coastal climate impacts and applications.
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