Data-driven approaches to study the dynamical stability of the stably stratified boundary layer

Abstract

Many experimental or natural systems undergo critical transitions, i.e. sudden shifts from one dynamical regime to another. For example in the climate system, the lower atmospheric layer, namely the atmospheric boundary layer, can experience sudden transitions between fully turbulent states and stable, quasi-laminar states. Such rapid transition are observed in Polar regions and at night, and have important consequences in the level of mixing with the higher levels of the atmosphere. To analyse the stable boundary layer many approaches rely on the identification of regimes, i.e. weakly and very stable regimes. Therefore, it is crucial to detect the transitions between the regimes. In this master thesis a combination of methods from dynamical systems and statistical modelling are applied to study these regime transitions. The analysis is based on an indicator for the dynamical stability (i.e. the resilience to pertubations) and a conceptual model for regime transitions of near-surface temperature inversion at night as well as in Arctic conditions. A focus lies on bifurcation points in the dynamics, points in which the stability of the system changes drastically. The performance of the stability indicator is assessed by applying it to simulated and observation data, provided from nighttime and Polar meteorological measurements.