Nonlinear Processes in Geophysics

A new approach to understanding fluid mixing in process-study models of stratified fluids
Samuel George Hartharn-Evans, Marek Stastna, and Magda Carr
Nonlin. Processes Geophys., 31, 61–74, https://doi.org/10.5194/npg-31-61-2024, 2024
Across much of the ocean, and the world's lakes, less dense water (either because it is warm or fresh) overlays denser water, forming stratification. The mixing of these layers affects the distribution of heat, nutrients, plankton, sediment, and buoyancy, so it is crucial to understand. We use small-scale numerical experiments to better understand these processes, and here we propose a new analysis tool for understanding mixing within those models, looking at where two variables intersect.

Multifractal structure and Gutenberg-Richter parameter associated with volcanic emissions of high energy in Colima, México (years 2013–2015)
Marisol Monterrubio-Velasco, Xavier Lana, and Raúl Arámbula-Mendoza
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2024-2,2024
Preprint under review for NPG (discussion: final response, 2 comments)
Understanding volcanic activity is crucial for uncovering the fundamental physical mechanisms governing this natural phenomenon. In this study, we show the application of multifractal and statistical analysis, to investigate changes associated with volcanic activity. We aim to identify significant variations within the physical processes related to changes in volcanic activity. These methodologies offer the potential to identify pertinent changes preceding a high-energy explosion.

A Comparison of Two Nonlinear Data Assimilation Methods
Vivian A. Montiforte, Hans E. Ngodock, and Innocent Souopgui
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2024-3,2024
Preprint under review for NPG (discussion: open, 1 comment)
Advanced data assimilation methods are complex and computationally expensive. We compare two simpler methods, Diffusive Back and Forth Nudging and Concave-Convex Nonlinearity, that account for change over time with the potential of providing accurate results with a reduced computational cost. We evaluate the accuracy of the two methods by implementing them within simple chaotic models. We conclude that the length and frequency of observations impacts which method is better suited for a problem.

Sensitivity of the polar boundary layer to transient phenomena
Amandine Kaiser, Nikki Vercauteren, and Sebastian Krumscheid
Nonlin. Processes Geophys., 31, 45–60, https://doi.org/10.5194/npg-31-45-2024, 2024
Current numerical weather prediction models encounter challenges in accurately representing regimes in the stably stratified atmospheric boundary layer (SBL) and the transitions between them. Stochastic modeling approaches are a promising framework to analyze when transient small-scale phenomena can trigger regime transitions. Therefore, we conducted a sensitivity analysis of the SBL to transient phenomena by augmenting a surface energy balance model with meaningful randomizations.