DECADAL CLIMATE PREDICTION
The Barcelona Supercomputing Center has been designated as a Global Producing Center of Near-Term Climate Prediction by the World Meteorological Organization (WMO). It is also involved in research on decadal predictions, including on ways to transfer relevant information present in these forecasts to interested users. To preview our latest forecast, please follow the link below.
ABOUT
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. To find out more about the research activities in decadal climate predictions at the Barcelona Supercomputing Center, please follow the link below.
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. Recently pioneered decadal climate prediction systems attempt to fill the gap that exists between these two timescales (i.e. from a year up to a decade). Predicting the variations in climate over this time horizon 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. However, it is also of great interest to users because the period over which it provides information coincides with their operational planning. To find out more about the research activities in decadal climate predictions at the Barcelona Supercomputing Center, please follow the link below.
FAQ
Decadal predictions are typically produced using a technique similar to that used for seasonal forecasts, i.e. by initializing a climate model and integrating it forward in time. These climate models are a mathematical representation of the Earth’s climate and are built using the basic laws of classical physics and thermodynamics. By initializing the model, we align its natural variability with that of the Earth climate system. The most common source of initial conditions are reanalyses data. Reanalyses are a combined form of observational data and climate models, thus representing a best estimate of the climate system at a specific time.
Decadal prediction systems will typically forecast surface variables such as temperature or precipitation over multiple years. Other times, they will forecast slowly varying climate oscillations that are known to impact the climate of certain regions such as the Atlantic Multidecadal Variability (AMV). It’s important to note that they do not predict the exact weather conditions at a precise date and location in the future, but only the average conditions over an extended period of time (in this case, multiple years).
Systems used in the context of decadal predictions typically include an atmosphere, ocean, sea ice and land surface components. The addition of other components (e.g. vegetation and carbon models) could potentially contribute to improving the skill of the forecasts and there is research currently underway to incorporate some of these components in the decadal prediction framework and study their impact. However, current decadal prediction systems are typically limited to these four components. More details on our forecasting system can be found in the Documentation section.
Yes. All of our data are freely available on the ESGF nodes.
Evaluating the quality of the predictions is considered a fundamental step in climate prediction because it assesses whether the prediction system can be trusted to forecast certain events. This verification process is typically based on validating extensive sets of hindcasts or retrospective predictions against observational references.
To evaluate the quality of our forecasts, we use both deterministic and probabilistic metrics. While deterministic measures provide information on the ensemble mean or a deterministic categorical forecast, probabilistic metrics attempt to evaluate the full hindcast distribution in order to provide a more comprehensive picture of system performance. In the Forecast section, we provide examples of such evaluation along with the actual forecast.
While decadal predictions have an enormous potential for helping a wide range of end-users, they are mostly a research activity at this stage and there are relatively few studies assessing the added value of decadal predictions for decision-making. Scientists from the Earth System Services group are investigating various ways this type of climate information can benefit stakeholders in different sectors. If you are interested in using this type of information, please get in touch.