Abstract: Abstract Many natural systems undergo critical transitions, i.e., sudden shifts from one dynamical regime to another. In the climate system, the atmospheric boundary layer can experience sudden transitions between fully turbulent states and quiescent, quasi-laminar states. Such rapid transitions are observed in polar regions or at night when the atmospheric boundary layer is stably stratified, and they have important consequences in the strength of mixing with the higher levels of the atmosphere. To analyze the stable boundary layer, many approaches rely on the identification of regimes that are commonly denoted as weakly and very stable regimes. Detecting transitions between the regimes is crucial for modeling purposes. In this work a combination of methods from dynamical systems and statistical modeling is applied to study these regime transitions and to develop an early warning signal that can be applied to nonstationary field data. The presented metric aims to detect nearing transitions by statistically quantifying the deviation from the dynamics expected when the system is close to a stable equilibrium. An idealized stochastic model of near-surface inversions is used to evaluate the potential of the metric as an indicator of regime transitions. In this stochastic system, small-scale perturbations can be amplified due to the nonlinearity, resulting in transitions between two possible equilibria of the temperature inversion. The simulations show such noise-induced regime transitions, successfully identified by the indicator. The indicator is further applied to time series data from nocturnal and polar meteorological measurements.

Abstract: Abstract. Current Volcanic Reconstructions Based On Ice Core Analysis Have Significantly Improved Over The Past Few Decades By Incorporating Multiple-core Analyses With A High Temporal Resolution From Different Parts Of The Polar Regions Into A Composite Common Volcanic Eruption Record. Regional Patterns Of Volcanic Deposition Are Based On Composite Records, Built From Cores Taken At Both Poles. However, In Many Cases Only A Single Record At A Given Site Is Used For These Reconstructions. This Assumes That Transport And Regional Meteorological Patterns Are The Only Source Of The Dispersion Of The Volcanic Products. Here We Evaluate The Local-scale Variability Of A Sulfate Profile In A Low-accumulation Site (Dome C, Antarctica), In Order To Assess The Representativeness Of One Core For Such A Reconstruction. We Evaluate The Variability With Depth, Statistical Occurrence, And Sulfate Flux Deposition Variability Of Volcanic Eruptions Detected In Five Ice Cores, Drilled 1 M Apart From Each Other. Local-scale Variability, Essentially Attributed To Snow Drift And Surface Roughness At Dome C, Can Lead To A Non-exhaustive Record Of Volcanic Events When A Single Core Is Used As The Site Reference, With A Bulk Probability Of 30 % Of Missing Volcanic Events And Close To 65 % Uncertainty On One Volcanic Flux Measurement (Based On The Standard Deviation Obtained From A Five-core Comparison). Averaging N Records Reduces The Uncertainty Of The Deposited Flux Mean Significantly (By A Factor 1? ? N); In The Case Of Five Cores, The Uncertainty Of The Mean Flux Can Therefore Be Reduced To 29 %.