Predicting climate evolution over interannual-to-decadal timescales represents a grand challenge for climate scientists, and an unprecedented opportunity for decision-makers to calibrate plans and actions over a temporal horizon of a few years.
In a new study recently published on Climate Dynamics a team of scientists (among them, CMCC researchers A. Bellucci, S. Gualdi, P.J. Athanasiadis from SERC Division) examined a multi-model ensemble of decadal prediction experiments, performed in the framework of the EU-funded COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) project following the 5th Coupled Model Intercomparison Project protocol.
A primary objective of COMBINE was to improve currently available Earth-system models by including key physical and biogeochemical processes so as to represent more accurately the forcing mechanisms and the feedbacks at work in the climate system. The decadal integrations were part of a broad assessment focusing on the predictive skill featured by a set of European state-of-the-art climate models. The simulations were performed following the CMIP5 protocol for near-term predictions, and therefore they contributed to the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5).
The lessons learnt in this pioneering pre-operational stage will help to design the next generation of coordinated decadal climate forecast experiments, out to CMIP6 and beyond.
The abstract of the paper:
A multi-model ensemble of decadal prediction experiments, performed in the framework of the EU-funded COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) Project following the 5th Coupled Model Intercomparison Project protocol is examined. The ensemble combines a variety of dynamical models, initialization and perturbation strategies, as well as data assimilation products employed to constrain the initial state of the system. Taking advantage of the multi-model approach, several aspects of decadal climate predictions are assessed, including predictive skill, impact of the initialization strategy and the level of uncertainty characterizing the predicted fluctuations of key climate variables. The present analysis adds to the growing evidence that the current generation of climate models adequately initialized have significant skill in predicting years ahead not only the anthropogenic warming but also part of the internal variability of the climate system. An important finding is that the multi-model ensemble mean does generally outperform the individual forecasts, a well-documented result for seasonal forecasting, supporting the need to extend the multi-model framework to real-time decadal predictions in order to maximize the predictive capabilities of currently available decadal forecast systems. The multi-model perspective did also allow a more robust assessment of the impact of the initialization strategy on the quality of decadal predictions, providing hints of an improved forecast skill under full-value (with respect to anomaly) initialization in the near-term range, over the Indo-Pacific equatorial region. Finally, the consistency across the different model predictions was assessed. Specifically, different systems reveal a general agreement in predicting the near-term evolution of surface temperatures, displaying positive correlations between different decadal hindcasts over most of the global domain.
Read the integral version of the paper:
A. Bellucci, R. Haarsma, S. Gualdi, P. J. Athanasiadis, M. Caian, C. Cassou,E. Fernandez, A. Germe, J. Jungclaus, J. Kröger, D. Matei, W. Müller, H. Pohlmann, D. Salas y Melia, E. Sanchez, D. Smith, L. Terray, K. Wyser,S. Yang
An assessment of a multi-model ensemble of decadal climate predictions
2014, Climate Dynamics, DOI 10.1007/s00382-014-2164-y