arXiv subjects

Amandine Kaiser

Publications and source records attributed to Amandine Kaiser.

4 recordsLinked to original sources

arXiv2026

Demographic Patterns in Cybersecurity Culture: Insights from a Global Organisation Supporting Safety-Critical and Critical Infrastructure Sectors

This study investigates demographic differences in cybersecurity culture in a large global organisation supporting safety critical and critical infrastructure sectors to target CSC improvement. A global survey was administered to all internal and external employees of a total of 21148 employees, with 6502 responses. The questionnaire evaluates nine CSC dimensions such as Password Management, Governance, Email Use. Anonymous survey responses were analysed using Kruskal-Wallis tests and Dunns post hoc comparisons to identify differences across demographic variables including employment, recruitment paths, managerial role, gender, age, tenure, and work base. CSC was broadly consistent across the organisation, with statistically significant but small to moderate demographic effects. CSC variations were observed across employment, age, recruitment paths, and line managerial role. In general, fulltime, internal, permanent, older employees, Merge and Acquisition recruits, and line managers consistently scored higher across multiple CSC dimensions. Parttime, younger, external employees, and those with 6 to 20 years of tenure in general scored lower. These patterns highlight higher-scoring groups that may act as CSC carriers and lower-scoring groups that may benefit from tailored improvement measures, enabling organisational learning. Our study offers a practical, scalable way to assess CSC, generating meaningful insights despite industrial constraints. It enables organisations to benchmark maturity, identify gaps, and prioritise targeted improvements using workforce diversity as a guide.

cs.CY↗

arXiv2024

Capturing the Variability of the Nocturnal Boundary Layer through Localized Perturbation Modeling

A single-column model is used to investigate regime transitions within the stable atmospheric boundary layer, focusing on the role of small-scale fluctuations in wind and temperature dynamics and of turbulence intermittency as triggers for these transitions. Previous studies revealed abrupt near-surface temperature inversion transitions within a limited wind speed range. However, representing these transitions in numerical weather prediction (NWP) and climate models is a known difficulty. To shed light on boundary layer processes that explain these abrupt transitions, the Ekman layer height and its correlation with regime shifts are analyzed. A sensitivity study is performed with several types of perturbations of the wind and temperature tendencies, as well as with the inclusion of intermittent turbulent mixing through a stochastic stability function, to quantify the effect of small fluctuations of the dynamics on regime transitions. The combined results for all tested perturbation types indicate that small-scale phenomena can drive persistent regime transitions from very to weakly stable regimes, but for the opposite direction, no evidence of persistent regime transitions was found. The inclusion of intermittency prevents the model from getting trapped in the very stable regime, thus preventing the so-called "runaway cooling", an issue for commonly used short-tail stability functions. The findings suggest that using stochastic parameterizations of boundary layer processes, either through stochastically perturbed tendencies or parameters, is an effective approach to represent sharp transitions in the boundary layer regimes and is, therefore, a promising avenue to improve the representation of stable boundary layers in NWP and climate models.

physics.ao-ph↗

arXiv2020

Detecting regime transitions of the nocturnal and Polar near-surface temperature inversion

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 non-stationary field data. The presented metric aims at detecting 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.

physics.ao-ph↗

arXiv2019

Statistical investigations of flow structures in different regimes of the stable boundary layer

A combination of methods originating from non-stationary timeseries analysis is applied to two datasets of near surface turbulence in order to gain insights on the non-stationary enhancement mechanism of intermittent turbulence in the stable atmospheric boundary layer (SBL). We identify regimes of SBL turbulence for which the range of timescales of turbulence and submeso motions, and hence their scale separation (or lack of separation) differs. Ubiquitous flow structures, or events, are extracted from the turbulence data in each flow regime. We relate flow regimes characterised by very stable stratification but different scales activity to a signature of flow structures thought to be submeso motions.

physics.ao-ph↗