About | Decadal Climate Predictions

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.

Who we are

The Department of Earth Sciences of the Barcelona Supercomputing Centre-Centro Nacional de Supercomputación is one of the most active groups in climate prediction and climate services in Europe. The department is currently composed of over 100 people structured in four interacting research groups. The department’s mission is to perform research on and developing methods for environmental forecasting, with a particular focus on the atmosphere-ocean-biosphere system. This includes managing and transferring technology to support the main societal challenges through the use of models and data applications in high-performance computing and Big data infrastructures. It also includes the dissemination of real-time air quality and climate information based on its research expertise in collaboration with both the Spanish authorities and the World Meteorological Organisation (WMO). The decadal climate predictions displayed here result from the collaboration of three groups within the Earth Science department: the Climate Prediction group, the Earth System Services group and Computational Earth Sciences group.

Climate Prediction

The Climate Prediction group aims at developing climate prediction capability for time scales ranging from a few weeks to a few decades and from regional to global scales. This objective relies on a deep analysis of the strengths and weaknesses of state-of-the-art climate forecast systems, via a thorough comparison with the most up-to-date observational datasets, and on exploiting these detailed analyses to refine the representation of processes relevant to climate in our forecast systems and their initialization. The group activities focus both on understanding climate variability and the sources of predictability and improving forecast quality.

Earth System Services

The Earth System Service group facilitates the interpretation and application of research coming from the BSC-ES. The group also carries out applied research to demonstrate the ongoing value of these services to advance sustainable development in key sectors of society and economy such as renewable energy, urban development, insurance, agriculture, water management or health. The Earth System Services group aims at developing tailored services on weather and atmospheric composition model simulations (focusing on short-term time scales) and climate predictions (focusing on the sub-seasonal, seasonal and decadal timescales).

Computational Earth Sciences

The Computational Earth Sciences group is a multidisciplinary group with members of different technical and scientific profiles, that interacts closely with the other groups of the Department. The group provides help and guidance on the technical aspects of the scientists’ work and develops a framework that ensures an efficient use of high-performance computing resources.

Acknowledgements

The decadal climate prediction website has been developed as part of the CLINSA project (CGL2017-85791-R), funded by the Spanish Ministry of Economy and Competitiveness (MINECO).