CANADIAN ASSOCIATION OF PHYSICISTS LECTURE
Atmospheric Complexity or
Scale by Scale Simplicity
Shaun Lovejoy
Department of Physics
McGill University
Wednesday, January 30, 2008
4:00 pm - 5:00 pm
BISHOP WILLIAMS HALL (J 200)
In 1922, Lewis Fry Richardson published the now celebrated book “Weather forecasting by numerical process” in which he daringly proposed that the weather could be forecast by brute force numerical integration of coupled nonlinear partial differential equations. But the father of numerical weather predication was Janus-faced: his book contains a famous footnote in which he proposed that the complex nonlinear atmospheric dynamics cascaded scale after scale from planetary down to small viscous scales: he is also the grandfather of modern cascade models.
The idea of scale by scale simplicity embodied in cascades is in tune with the history of science that shows that once the fundamentals are correctly grasped, that messy complexity generally gives way to simplicity and that simplicity points the way to the future. But are cascades correct? Over the last five years, profiting from a “golden age” of atmospheric data and models of unprecedented quality and quantity, my colleagues and I have used state of the art satellite, lidar and “drop sonde” data to decisively show that over the entire range of meteorologically significant scales that the atmosphere accurately follows the predictions of cascade models. So which Richardson is right? The father of numerical weather prediction or the grandfather of cascades?
The answer may be both. This is possible because cascade models are specifically designed as phenomenological models of the equations. It turns out that typical numerical models do indeed catch a glimpse of the cascade: today’s models apparently capture the first factor of ~30 in scale of a cascade which starts near planetary scales and apparently continues down to millimetres (a factor of ~1010). Yet even if the GCM's are consistent with cascades, in time they will receive competition from a new potentially more powerful class of cascade models which directly exploit the scale-by-scale cascade simplicity allowing them to handle a far larger ranges of scale than is currently possible.
This lecture will also be of interest to students in the ESG program.
