source:CCSS Meeting #35: Scaling, Complexity and High Level Laws in Weather, Macroweather and the Climate – Current affairs – Universiteit Utrecht
CCSS Meeting #35: Scaling, Complexity and High Level Laws in Weather, Macroweather and the Climate
On Monday 28th September we will be holding our CCSS Meeting #35 on Zoom.
We will continue to use our virtual Centre for Complex Systems Studies external link environment on Microsoft Teams to post upcoming events. You are also welcome to use the environment to meet and engage with other complexity researchers, alongside staying up-to-date on our online activities.
This lecture is an online discussion organised under our new Scaling in Complex Systems lecture series.
For the foreseeable future, lectures will remain predominantly online.
This Series: Scaling in Complex Systems
This academic year, we are introducing two series of lectures at the CCSS. Under our ‘Scaling in Complex Systems’ series, we shall hear from researchers investigating mechanisms of scaling, such as self-organized criticality, preferential processes, multiplicative processes and sample space reducing processes.
Shaun Lovejoy external linkis Professor of Physics at McGill University, where he also earned his PhD. He has been on the faculty of McGill since 1985. He received his B.A. and M.S. in theoretical physics from Trinity College, Cambridge. Shaun has greatly contributed to the field of nonlinear geophysics, with some important advancements including multifractal cascades, generalized (anisotropic) scale invariance and (causal) space-time multifractal modeling of geofields. In 2013, Lovejoy showed that the conventional weather – climate dichotomy underestimated atmospheric variability, and argued for the replacement of the dichotomy by the trichotomy of weather – macroweather – climate. In 2016, he was named Fessenden professor at McGill University. In 2019 he was awarded the EGU’s Richardson medal.
Macroscopic bodies are complex, involving huge numbers of molecules, yet for most purposes, the micro-details are irrelevant. Weather models are based on thermodynamics and continuum mechanics and are successful because they retain only the relevant variables: they don’t even acknowledge the existence of atoms. Similarly, the number of atmospheric degrees of the atmosphere – the weather “details” – is ≈ 1027. Starting with Richardson in the 1920’s, this has motivated the development of turbulence laws that ignore irrelevant aspects of the jumble of vortices. These laws are based on the physical principle of scaling; for realism, they have been generalized to anisotropic (especially stratified) multifractal processes. In the last decades, such processes have been identified in numerous geo and other complex systems.
Beyond about 10 days – the deterministic predictability limit, the macroweather regime – standard weather models become stochastic and to tame this complexity, new high level laws are needed. I describe several (high level) macroweather and climate models based on energy balance and scaling. I argue that they already make optimal monthly and seasonal forecasts as well as improved multidecadal climate projections.
There will be 45-min lecture from the speaker, followed by a 45-min Question & Answer session.
To attend the lecture, please click this link external link at 15:30 on Monday 28th September 2020.S
28 September 2020 15:30 – 17:00
Location Link to Webiner external link
More information CCSS Environment on Microsoft Teams