arXiv subjects

Stephan Pfahl

Publications and source records attributed to Stephan Pfahl.

3 recordsLinked to original sources

arXiv2026

Modelling convective cell occurrence in proximity to cold fronts using extreme gradient boosting

Machine learning is emerging as a valuable tool for convection-related applications such as post-processing numerical weather prediction output, improving understanding of convective storm climatology and potentially improving existing convective parameterization schemes. In a rapidly developing field, it is vital to assess the strengths and limitations of machine learning approaches across different applications. Here, a probabilistic model is developed using a convective cell dataset as ground truth and predictors primarily from ERA5. The model's ability to reproduce the convective cell climatology at different regions relative to cold fronts (i.e. post-frontal and pre-frontal) is assessed during the warm-season in Germany. The optimal number of features (predictors) is selected using a feature elimination strategy. Overall, the optimised model exhibits high skill in reproducing the spatial and temporal cell frequency at different regions relative to the front. While the highest cell frequency is correctly identified near the surface front, the model underestimates the actual cell count in this region. Feature importance analysis shows that the model depends most heavily on CAPE to make its predictions. Additionally, the time of day predictor is key for accurately capturing the diurnal cycle of convective cells on both sides of the cold front. The study highlights both the advantages and the limitations of data-driven models, offering valuable insights for future data-driven climate and weather prediction models.

physics.ao-ph↗

arXiv2026

Noise-induced enhancement of regime lifetimes -- A data-driven approach using deterministic trajectories

We investigate the lifetime of dynamical regimes under the impact of noise motivated by low-dimensional models of the atmosphere. One may expect that the inclusion of noise tends to make the system leave prescribed regions of the state space faster. However, for relevant systems with complexities ranging from phenomenological toy models to reduced models of atmospheric dynamics, this intuition has proven misleading. As long as the noise is sufficiently small, the noisy system stays in regimes of interest on average longer than its deterministic counterpart, an effect we call ``stochastic inertia''. This phenomenon has been observed through extensive numerical simulations for different noise levels. We propose a numerical technique for testing the occurrence of stochastic inertia, constructing, for any fixed noise level, a Markov chain on the set of points given by a sufficiently long trajectory of the system without noise. The method is shown to correctly predict the presence of stochastic inertia in simple systems, and its utility is demonstrated on a paradigm model of atmospheric dynamics.

math.NA↗

arXiv2021

QG-DL: Dynamics of a diabatic layer in the quasi-geostrophic framework

Quasi-geostrophic (QG) theory describes the dynamics of synoptic scale flows in the trophosphere that are balanced with respect to both acoustic and internal gravity waves. Within this framework, effects of (turbulent) friction near the ground are usually represented by Ekman Layer theory. The troposphere covers roughly the lowest ten kilometers of the atmosphere while Ekman layer heights are typically just a few hundred meters. However, this two-layer asymptotic theory does not explicitly account for substantial changes of the potential temperature stratification due to diabatic heating associated with cloud formation or with radiative and turbulent heat fluxes, which, in the middle latitudes, can be particularly important in about the lowest three kilometers. To address this deficiency, this paper extends the classical QG-Ekman layer model by introducing an intermediate, dynamically and thermodynamically active layer, called the "diabatic layer" (DL) from here on. The flow in this layer is also in acoustic, hydrostatic, and geostrophic balance but, in contrast to QG flow, variations of potential temperature are not restricted to small deviations from a stable and time independent background stratification. Instead, within the diabatic layer, diabatic processes are allowed to affect the leading-order stratification. As a consequence, the diabatic layer modifies the pressure field at the top of the Ekman layer, and with it the intensity of Ekman pumping seen by the quasi-geostrophic bulk flow. The result is the proposed extended quasi-geostrophic three-layer QG-DL-Ekman model for mid-latitude (dry and moist) dynamics.

physics.ao-ph↗