Research topic:

We aim to advance the modelling and parameterization of dynamical processes in meteorology, particularly by exploiting the optimal fusion of extensive observational datasets with computational modelling. We have a particular interest in processes occurring in the atmospheric boundary layer and how those affect the weather and climate system. This includes studying energy and mass exchange processes across scales in the atmosphere, as well as understanding near-surface dynamical processes. We also study how the atmosphere organizes in different flow regimes with distinct dynamical characteristics, what leads to regime transitions, and how different flow regimes impact exchange processes.

Projects:

• Stochastic modelling of turbulence in the atmospheric boundary layer
• Data-driven, low-dimensional climate models
• Cultural evolution in changing climate: Human and Earth system coupled research (HESCOR)
• BMBF project WarmWorld – TurbO-Arctic

Some recent publications:

• V. Boyko and N.Vercauteren (2024). Simulating the unsteady stable boundary layer with a stochastic stability equation. Journal of Geophysical Research: Atmosphere, https://doi.org/10.1029/2023JD039370

• A. Kaiser, N. Vercauteren, S. Krumscheid (2024). Capturing the Variability of the Nocturnal Boundary Layer through Localized Perturbation Modeling. Nonlinear Processes in Geophysics, https://doi.org/10.5194/npg-31-45-2024

• A Harikrishnan, M Rodal, R Klein, D Margerit, N Vercauteren (2023). On the motion of hairpin filaments in the atmospheric boundary layer. Physics of Fluids, https://doi.org/10.1063/5.0151078

• V. Boyko and N. Vercauteren (2023). Stochastic stability equation for unsteady turbulence in the stable boundary layer. Quarterly Journal of the Royal Meteorological Society, https://doi.org/10.1002/qj.4498

• F. Gucci, L. Giovannini, I. Stiperski, D. Zardi, N. Vercauteren (2022). Sources of anisotropy in the Reynolds stress tensor in the stable boundary layer over snow. Quarterly Journal of the Royal Meteorological Society, https://doi.org/10.1002/qj.4407

• A. Viennet, N. Vercauteren, M. Engel, D. Faranda (2022). Guidelines for data-driven approaches to study critical transitions in multiscale systems: the case of Lyapunov vectors. Chaos, https://doi.org/10.1063/5.0093804

• M. Rodal, S. Krumscheid, G. Madan, J. H. LaCasce, N. Vercauteren (2022). Dynamical stability indicator based on autoregressive moving average models: critical transitions and the Atlantic meridional overturning circulation. Chaos, https://doi.org/10.1063/5.0089694

• V. Boyko, S. Krumscheid and N. Vercauteren. Statistical learning of nonlinear stochastic differential equations from non-stationary timeseries using variational clustering. Journal of Multiscale modelling and simulations, https://doi.org/10.1137/21M1403989

• M. Calaf, N. Vercauteren, G. Katul, M. Giometto, T.J. Morrison, F. Margairaz, V. Boyko and E.R. Pardyjak (2022). Boundary layer processes hindering contemporary numerical weather prediction models Boundary-Layer Meteorology, https://doi.org/10.1007/s10546-022-00742-5