Roberto Buizza (European Centre for Medium-Range Weather Forecasts): “Signals and noise, hawk-moths and butterflies: Weather prediction in a world of uncertainties”

Abstract: Ensemble-based, probabilistic systems provide (at least up to now) the most effective way to predict the weather taking into account all relevant sources of uncertainty, to extract predictable signals from sometimes noisy single forecasts. They help us living and dealing with both the butterfly effect (sensitive dependence to initial condition errors; see Lorenz 1963 J. Atm. Sci.) and the hawk-moth effect (sensitive dependence to model approximations; see e.g. Frigg et al 2014 Phy. Of Sci.), and issue skilful predictions despite the chaotic nature of the atmosphere.

In the first part of my talk I will discuss lessons learned in weather prediction, where in the past 25 years we have witnessed a paradigm shift from a single-forecast to a probabilistic approach, whereby a range of possible weather scenarii are predicted using an ensemble. To ensure the reliability of these probabilistic predictions, we have been designing these ensembles to simulate all relevant sources of forecast uncertainties, linked to uncertainties in the initial conditions (the knowledge of the current state of the system) and the model approximations.

I will then discuss how we are applying a similar approach to generate an ensemble of coupled ocean-land-atmosphere reanalyses (i.e. 3-dimensional states of the Earth system) of the past century, to have a less-uncertain estimate of the past climate. Finally, I will conclude the seminar by suggesting some possible links between butterflies, hawk-moths and reliable signals, and economics and forward guidance.

Biography: Roberto Buizza has a first degree (‘Laurea’) in Physics from the University of Milano, a PhD in Mathematics from the University of London and an MBA from London Business School. He joined the Research Department of the European Centre for Medium-Range Weather Forecasts (ECMWF) in 1991, after having worked four years at the Centre for Thermonuclear Research of the Electricity Board of Italy (CRTN/ENEL, in Milano). In January 2016 he was appointed ECMWF Lead Scientist, after having worked for 5 years as Head of the Predictability Division. His main areas of research and expertise are coupled ocean-land-atmosphere modelling, predictability, ensemble prediction, uncertainty simulation, verification and application of probabilistic weather predictions (e.g. in hydrology, energy and finance), and reanalysis.

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