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”
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”
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]
NPG Paper of the Month: “A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective”
Illustration of the transport of a chemical specy by a heterogeneous wind field over a 1D domain (a) and the numerical simulation from a simple discretization scheme (b). The loss of variance due to the spurious numerical diffusion involves an increase of the model-error variance (c) which is coupled with the anisotropy (the correlation length-scale in 1D domain, in panel d).
The January 2021 NPG Paper of the Month award goes to Olivier Pannekoucke and his co-authors for the paper “A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective“. In geophysics, forecasting is based on solving the equations of physics with the help of a computer. To calculate a forecast we need an initial conditi ...[Read More]