NP
Nonlinear Processes in Geosciences

NPG Paper of the Month

NPG Paper of the Month: “Inferring the instability of a dynamical system from the skill of data assimilation exercises”

April 25, 2022
NPG Paper of the Month: “Inferring the instability of a dynamical system from the skill of data assimilation exercises”
Scatter plots of the largest Lyapunov exponent (left) and Kolmogorov-Sinai entropy (right) against the skill of DA measured as the RMSE of the analysis. The experiments are done with model configurations displaying fully developed chaos (main panels) and with weakly chaotic configurations (insets). In all cases a strong observational constraint is applied: we measure the entire state vector at each time step. The theoretical error upper bound are also displayed (red markers).

The NPG paper of the month was awarded to “Inferring the instability of a dynamical system from the skill of data assimilation exercises” by Yumeng Chen, Alberto Carrassi, and Valerio Lucarini. Geophysical systems are usually described by a set of dynamical equations that are often non-linear and chaotic (Ghil and Lucarini, 2020). Errors about the initial state can grow, shrink, or sta ...[Read More]

NPG Paper of the Month: “Comparing estimation techniques for temporal scaling in palaeoclimate time series”

December 14, 2021

The NPG paper of the month of July was awarded to Comparing estimation techniques for temporal scaling in palaeoclimate time series by Raphaël Hébert, Kira Rehfeld and Thomas Laepple (https://doi.org/10.5194/npg-28-311-2021). Raphaël Hébert is currently a post-doctoral researcher at the Alfred-Wegener-Institut in Potsdam (Germany) in the Earth System Diagnostics group of Thomas Laepple, where he a ...[Read More]

NPG Paper of the Month: “Recurrence analysis of extreme event-like data”

July 1, 2021
NPG Paper of the Month: “Recurrence analysis of extreme event-like data”
Top panels: time series of a periodic (left), stochastic (middle), and chaotic system (right). Bottom panels: the corresponding recurrence plots of respective systems.

The May 2021 NPG Paper of the Month award goes Abhirup Banerjee and his co-authors for their paper “Recurrence analysis of extreme event-like data“. Abhirup is pursuing a doctoral degree in Theoretical Physics at University of Potsdam. He is working at Potsdam Institute of Climate Impact Research as a guest researcher as part of the DFG funded NatRiskChange project. In this project, he ...[Read More]

NPG Paper of the Month: “Ordering of trajectories reveals hierarchical finite-time coherent sets in Lagrangian particle data: detecting Agulhas rings in the South Atlantic Ocean”

March 16, 2021
NPG Paper of the Month: “Ordering of trajectories reveals hierarchical finite-time coherent sets in Lagrangian particle data: detecting Agulhas rings in the South Atlantic Ocean”
Result of the OPTICS algorithm applied to the trajectories modelled in the Bickley Jet model flow. (a), (d) and (g) show the reachability plot with different DBSCAN clustering results, indicated by the black horizontal line. The corresponding clustering results of each choice of DBSCAN parameter is shown on the right of the reachability plots for different times. Grey particles correspond to noise. Axis units in the centre and right column are in 1000 km.

The February 2021 NPG Paper of the Month award goes David Wichmann and his co-authors for their paper “Ordering of trajectories reveals hierarchical finite-time coherent sets in Lagrangian particle data: detecting Agulhas rings in the South Atlantic Ocean“. Understanding the transport of tracers and particulates is an important topic in oceanography and in fluid dynamics in general. Th ...[Read More]