Documentation

Decadal Predictions

The evolution of the climate systems in the near future depends on changes in atmospheric composition and other external forcings as well as in the slow naturally generated internal climate variability. Until very recently, the only sources of future climate information that were available to interested users were seasonal predictions and climate projections. The former provide a future outlook of the earth’s climate system for a period ranging from 1 to 18 months into the future while the latter covers a continuous temporal range from the past century to the end of this century (or beyond) but with no relationship with the contemporaneous internal climate variability. At the seasonal timescale, the climate evolution mainly depends on the internally generated variabilities of the climate system and less on the changes in the externally forced components that occur over the period of forecast. On the other hand, climate projections are solely driven by changes in external forcings without constraints on the internal variability.

As an alternative to these types of climate information, recently developed decadal climate prediction systems attempt to fill the gap that exists between these two timescales (i.e. from a year up to a decade), where the evolution of the climate is impacted by both internally generated variability and externally forced components. Decadal prediction is then, in simple terms, the extension of seasonal forecasts wherein climate models are initialized by introducing observation-based data and run for a decade or so under the influence of contemporaneous changing external forcings (for instance, with rising greenhouse-gas concentration), as in climate projection. Predicting the variations in climate at this timescale is considered one of the most challenging problems faced by the climate forecasting community due to the relatively weak constraints that can be applied on the internal variability and the relatively weak anthropogenic external forcings at this timescale.

The first attempt at producing decadal climate predictions was made in the framework of the EU-funded ENSEMBLES project (2004-2009). Several studies investigated the capacity of different decadal prediction systems to accurately “predict” past climate variability in retrospective experiments called hindcasts (as opposed to the actual future predictions, called forecasts). Since then, the field of decadal prediction has grown significantly, in part due to the large socio-economic interest generated by these predictions. Clear examples of the growing interest in this field of research are the inclusion of decadal predictions in the recent phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6), the production and publication of real-time decadal predictions and a growing body of literature on potential applications of these forecasts.

Decadal prediction lies at the boundary between seasonal forecasting and climate change projections. While seasonal forecasting is considered an initial value problem (the evolution of the atmosphere-ocean system is largely determined by the initial condition) and climate projections a boundary value problem (the system evolution depends on the external forcing and formulation of boundary condition), decadal prediction is considered a joint initial-boundary value problem (Figure 1), with both internal processes and external forcings playing a role in decadal climate variations.

At the decadal timescale, the observed climate variability can be understood as the superimposition of an anthropogenically-driven trend on natural fluctuations. This simple view assumes that there is no interaction between the trend and the natural fluctuations, which might not be necessarily the case. While the trend is driven by changes in anthropogenic emissions, the natural fluctuations are generated internally by the interactions of the different components of the climate system (atmosphere, ocean and sea ice) or externally by other factors such as volcanic eruptions and solar activity. Provided that these different factors operate on a sufficiently long timescale (multiannual or longer) and their influence can be estimated with a sufficient level of accuracy, they can potentially be a source of skill in a decadal prediction context.

For a more simplified introduction to decadal predictions and the potential uses of such predictions in the agriculture sector, please see the infosheet "A brief introduction to decadal predictions".

EC-Earth forecasts system and data access

EC-Earth is a global climate model system based on the idea to use the world-leading weather forecast model of the ECMWF (European Centre of Medium Range Weather Forecast) in its seasonal prediction configuration as the base of climate model. The model system can be used in several configurations including the classical climate model (atmosphere, soil, ocean, sea ice) and Earth System configurations (adding atmospheric chemistry and aerosols, ocean bio-geo-chemistry, dynamic vegetation and a Greenland ice sheet).

The model is developed by the European EC-Earth consortium bringing together 27 research institutes from 10 European countries to collaborate on the development of an Earth System Model. The model in its different configurations and resolutions is used for climate change projections, predictions and process studies. EC-Earth 3, the current version, has been prepared for the 6th phase of the Climate Model Intercomparison Project (CMIP6).

Technical Details

The BSC-ES has been a member of the EC-Earth consortium since 2009, and is both a user and a developer of the coupled global climate model EC-Earth (http://www.ec-earth.org), which is a crucial component of the forecast system. EC-Earth is a combination of the IFS model (atmosphere), NEMO (ocean) and the LIM model (sea-ice), assembled using the OASIS coupler. More details on the forecast system are provided in the table below.