The 2017 Lewis Fry Richardson Medal is awarded to Edward Ott for pioneering contributions in the theory of chaos with applications to the motion of tracers in fluids, kinematic dynamos, and data assimilation for weather forecasting.
Edward Ott is one of world’s leading experts in the theory of chaos in nonlinear dynamical systems which he has applied to many areas, introducing new ideas and concepts. Ott’s early research was concerned with plasma physics, but his interests gradually broadened to more diverse applications of the theory of chaos. One of his major contributions, together with C. Grebogi and J. A. Yorke, is the development of an approach for controlling chaos. Ott’s work has led to new insights in geosciences in connection with kinematic dynamos, Lagrangian chaos and numerical weather prediction. In the first topic, which addresses aspects of the origin of magnetic fields of the Earth, other planets, stars and galaxies, he was the first to show that, in the limit of high magnetic Reynolds number, three-dimensional chaotic flows lead to dynamo action in which magnetic fields have fractal properties (connecting directly with L. F. Richardson’s achievements). Lagrangian chaos, or chaotic advection, in which the distance between nearby fluid elements increases exponentially in time, commonly occurs in fluid flows. Ott studied the fractal structure (invoking Richardson again) of the distribution of a passive scalar in Lagrangian chaos even in flows of arbitrary time-dependence, introducing – with co-authors – the novel concept of snapshot attractors (which is nowadays becoming widely used under the name of pullback attractors). This aspect has major consequences for the prediction of the dispersion of pollutants. Concerning numerical weather prediction (a field that was all but created from scratch by L. F. Richardson), Ott has studied the problem of assimilation of observations. Although originating from immediate practical necessities, this question is intrinsically related to fundamental aspects of the stability and predictability of atmospheric flows. By using the original concept of ‘local low dimensionality’, Ott and his colleagues have formulated a method for ensemble Kalman filter assimilation. In this method, an ensemble of forecasts is combined with observations to estimate the states of the ensemble members and their variances in many local regions. These local estimates are then combined together to re-initialise the global states in a new ensemble. Called the Local Ensemble Transform Kalman Filter, this highly original approach is widely used in operational weather prediction. Ott is the author or co-author of over 450 articles in refereed scientific journals, and has been the PhD advisor of 50 students. According to the ISI citation counts, he is one of the world’s most highly cited researchers in the field of chaos and nonlinear dynamics. His textbook Chaos in Dynamical Systems (Cambridge University Press), has received more than 5000 Google Scholar citations, and has been very influential and widely used as a basis for courses in the field. Many of the works of Ott in the field of geosciences are strongly aligned with the works of Lewis Fry Richardson, making this award particularly appropriate.