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DESCRIPTION:Atmospheric and Oceanic Sciences Departmental Seminar Series\n
 \npresents\n\nWeather\, Macroweather\, Climate: reuniting Richardson's str
 ands\n\na talk by\n\nShaun Lovejoy\n	Professor\, \n	Department of Physics\,
 \n	şÚÁĎÉç\n\nA hundred years ago\, Lewis Fry Richardson made the
  first numerical weather forecast\, founding the field of numerical weathe
 r prediction (NWP). Based on deterministic continuum mechanics\, today it 
 is not only ubiquitous in daily weather forecasts\, but has been extended 
 to seasonal predictions through to multidecadal climate projections\n\nBut
  Richardson also pioneered the development of high level turbulent laws. I
 n 1926 he proposed the “Richardson 4/3 law” of turbulent diffusion\, a law
  that wasn’t vindicated until 2013. Whereas NWP attempts to account for ev
 ery whirl\, cloud\, eddy\, structure\, the 4/3 law exploits the idea of sc
 aling to statistically account for the collective outcome of billions upon
  billions of structures jointly acting from millimetres up to the size of 
 the planet.\n\nThe idea that high-level statistical laws could explain the
  actions of myriads of vortices\, cells and structures was shared by succe
 ssive generations of turbulence scientists. Unfortunately\, they faced mon
 umental mathematical difficulties largely connected to turbulent intermitt
 ency: the fact that most of the activity (e.g. energy flux) is inside tiny
 \, violently active regions\, themselves buried in a hierarchy of structur
 es within structures. The application of turbulence theory to the atmosphe
 re\, encounters an additional obstacle: stratification that depends on sca
 le.\n\nThe 1980’s marked a turning point when Richardson’s deterministic a
 nd statistical strands parted company\, the unity of the atmospheric scien
 ces was broken. On the one hand\, computers revolutionized NWP\, on the ot
 her hand\, the nonlinear revolution promised to tame chaos itself\, includ
 ing turbulent chaos with its fractal structures within structures.\n\nIn t
 his talk\, I summarize four decades of work attempting to understand atmos
 pheric variability that occurs over an astonishing range of scales: from m
 illimetres to the size of the planet\, from milliseconds to billions of ye
 ars. The variability is so large that standard ways of dealing with it are
  utterly inadequate: in 2015\, it was found that classical approaches had 
 underestimated the variability by the astronomical factor of a quadrillion
 . The new understanding allows us to finally reunite Richardson’s strands.
 \n\nFor example\, I show that the deterministic weather models respect the
  stochastic scaling laws very well. I explain “macroweather” and how it si
 ts in between the weather and climate\, finally settling the question: “Wh
 at is Climate”? I answer the question “how big is a cloud?” and show that 
 Mars is our statistical twin and why this shouldn’t surprise us. I explain
  how the multifractal butterfly effect gives rise to events that are so ex
 treme that they have been called “black swans”.\n\nBy using data from the 
 real world – not model – climate\, and with the help of the Fractional Ene
 rgy Balance Equation (FEBE)\, I explain how the emergent scaling laws can 
 make accurate monthly to decadal (macroweather) forecasts by exploiting an
  unsuspected but huge memory in the atmosphere-ocean system itself. I show
  how the FEBE can help to significantly reduce the large uncertainties in 
 our current climate projections to 2050 and 2100.\n\nMonday Dec 02/ 3:30 P
 M/ Burnside Hall/ Room 934\n
DTSTART:20191202T203000Z
DTEND:20191202T220000Z
LOCATION:Room 934
SUMMARY:Weather\, Macroweather\, Climate: reuniting Richardson's strands
URL:/meteo/channels/event/weather-macroweather-climate
 -reuniting-richardsons-strands-302737
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