סמינר מיוחד בחוג לגיאופיזיקה: The Atmosphere as a Dynamical System: new insights into predictability and weather extremes

Abstract: 

Atmospheric flows are characterized by chaotic dynamics and recurring large-scale patterns. These two characteristics point to the existence of an atmospheric attractor defined by Lorenz as: “the collection of all states that the system can assume or approach again and again, as opposed to those that it will ultimately avoid”. This dynamical systems perspective has immediate applications to the study of large-scale atmospheric patterns and extreme weather events. I will first explain how we can compute measures of the stability (stickiness) and complexity (dimension) of instantaneous atmospheric fields. Next, I will apply this approach to reanalysis data in the Euro-Atlantic sector. The extreme values of the two dynamical systems metrics correspond to specific large-scale atmospheric patterns. They can also be used to identify "maximum predictability" states of the atmosphere, where the flow at positive lags of up to one week is particularly stable and with a small number of degrees of freedom. This provides a novel predictability pathway for extreme weather occurrences associated with these states. Finally, there is a significant correlation between the time series of stability and complexity of an atmospheric field and the mean spread at lead times of over two weeks of an operational ensemble weather forecast initialised from that field.

מארגן הסמינר: פרופ' איל חפץ