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SUMMARY:Statistical physics for climate sciences: applications to wave tur
 bulence\, extreme heat waves\, and extremes of renewable energy production
  - Freddy Bouchet\, Laboratoire de Météorologie Dynamique
DTSTART:20250626T120000Z
DTEND:20250626T130000Z
UID:TALK233731@talks.cam.ac.uk
CONTACT:9780
DESCRIPTION:Climate changes impacts and the need for its mitigation and ad
 aptation will change deeply many aspects of our society. Physicists can co
 ntribute decisively to this endeavor. Indeed\, the theoretical aspects of 
 climate science are a new and highly multidisciplinary field\, with contri
 butions from statistical physics\, mathematics\, data and computer science
 s\, as well as hydrodynamics and turbulence. Research In this field are pe
 rformed at the forefront of many contemporary subjects connected to statis
 tical physics: effective dynamics\, inference of stochastic processes\, an
 d inference of causality relations\, and of their connection with machine 
 learning\, large deviation theory\, to cite just of few examples.\n\nIn th
 is talk I will discuss several examples where statistical physics and larg
 e deviation theory can be useful to solve fundamental problems for the dyn
 amics of the climate system. The first example will be a theoretical contr
 ibution to the kinetic theory of wave turbulence. Wave turbulence plays an
  important role for atmosphere/ocean physical exchanges and for mixing of 
 the ocean interior. I will explain how large deviation theory allows to ex
 tend this classical theory to compute effects of typical and rare spontane
 ous fluctuations. I will explain how this can be used for stochastic param
 eterization for wave energy propagation.\n\nA large part of the talk will 
 be dedicated to extreme heat waves. Extreme events or transitions between 
 climate attractors are of primarily importance for understanding the impac
 t of climate change. Recent extreme heat waves\, with huge impact\, are st
 riking examples. However\, they cannot be studied with conventional approa
 ches\, because they are too rare and realistic models are too complex. We 
 will discuss several new algorithms and theoretical approaches\, based on 
 large deviation theory\, rare event simulations\, and machine learning for
  stochastic processes\, which we have specifically designed for the predic
 tion of extreme heat waves. Using the best available climate models\, our 
 approach sheds new light on the fluid mechanics processes which lead to th
 ese events. We will describe quasi-stationary patterns of turbulent Rossby
  waves that lead to global teleconnection patterns in connection with heat
  waves and analyze their dynamics. \n\nAt the end of the talk\, I will bri
 efly outline current projects where we use the same tools to study extreme
 s of renewable energy production and their connection with climate dynamic
 s. Those rare events are key for the future of the European electricity sy
 stem
LOCATION:MR13\,  Centre for Mathematical Sciences\, Wilberforce Road\, Cam
 bridge
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