INCLIDA

Initialization of global decadal climate forecast: a new challenge for multi-scale data assimilation

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 Obiettivo del progetto (Objective)

'Decadal prediction has emerged nowadays as a main concern in the climate science community. Improving the forecast on the time scales of 10-30 years is expected to carry tremendous value for the society, supporting plans for infrastructure upgrades, financial decisions or energy policies. Decadal predictions are in between the seasonal forecast (6-12 months) and the climate prediction (on the scale of a century) and share a number of physical and dynamical features of both. The decadal time range is at the confluence of forecasting, such as that performed in seasonal prediction, having a marked predictable signal in the initial state and the long term climate prediction driven mainly from external forcing and fully independent from the initial state. Refined observing networks for the ocean component are now available (see e.g. the ARGO project at www-argo.ucsd.edu, or SMOS mission of ESA) and contribute also to promising future improvements in forecast quality. Data assimilation is the field of geosciences that study the problem of state estimation of evolving, possibly chaotic, dynamical system on the base of incomplete, inhomogeneous and noisy observations. Data assimilation is regarded nowadays with strong interest from the climate science community, because of the potential to improve decadal prediction by introducing adequate initialization process for the whole climate system, making the best use of the current observations. Several fundamental unresolved questions need to be addressed to adapt existing data assimilation algorithms as well as to develop new strategies for the Earth system models used in decadal prediction. Testing different data assimilation approaches and contributing to the current open debate on how to improve initialized decadal prediction are the main motivations of the proposed research. The project ultimate goal is the implementation of a state-of-the-art data assimilation technique for the initialization of the IC3 EC-Earth model.'

Introduzione (Teaser)

As part of the ongoing melding of climate prediction and climate simulation research, EU-funded scientists explored the possibility of making skilful predictions based on annual to multi-annual timescales.

Descrizione progetto (Article)

Decadal climate predictions use the state of the world's oceans and their influence on the atmosphere to predict how global climate will evolve over the next few years. It is a relatively new area driven by supercomputing, increased sophistication of models and the availability of higher-quality observations of the climate system. Because this is a brand new way of doing predictions, it is necessary to have confidence in the skills of these models.

In the EU-funded INCLIDA project, decadal predictions were tested with an advanced initialisation method that has proven successful in weather forecasting. Weather predictions rely on the accuracy of the initial state as the influence of the external forcing is almost imperceptible. Decadal climate predictions, start from initial conditions that are distant from today's climate and thus fail to 'predict' the year-to-year variability and most of the decadal variability.

The method employed by the INCLIDA scientists to initialise the dynamic system of the Earth's atmosphere is known as data assimilation. It estimates the initial state of a model, given a set of sparse observations. Specifically, the extended Kalman filter uses statistics from an ensemble of predictions to estimate the relationship between the observations and all variables for their correction. This method proved to be computationally intensive as it requires integrations of the model.

The INCLIDA scientists combined EC-Earth, a state-of-the-art global Earth system model that consists of an atmosphere, ocean, sea ice and land model with the extended Kalman filter and other initial state estimation algorithms. To test the skills of the new approach proposed, they performed retrospective decadal predictions over the last century. Starting from 1 January of 1960, the EC-Earth model demonstrated decadal predictability until 31 December 2012 that is close to the model's limit of predictability.

The results are described in two scientific papers published in international peer-reviewed journal. Although encouraging, they are based on the synthetic solution taken from the same model at different times. As the model and its predictions are far from perfect, the INCLIDA scientists' efforts are hoped to spark research among modellers to improve their calculations.