NP
Nonlinear Processes in Geosciences

NPG Paper of the Month

NPG Paper of the Month: “A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective”

March 11, 2021
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]

NPG Paper of the Month: “Statistical postprocessing of ensemble forecasts for
 severe weather at Deutscher Wetterdienst”

December 23, 2020
NPG Paper of the Month: “Statistical postprocessing of ensemble forecasts for
 severe weather at Deutscher Wetterdienst”
Probabilities of wind gusts higher than 14 m/s on
a regular 1 km grid over Germany; 13 h forecast lied time from Ensemble-MOS for COSMO-DE-EPS from 29 October 2018. Licence: Statistical postprocessing of ensemble forecasts for severe weather at Deutscher Wetterdienst.

The October 2020 NPG Paper of the Month award goes to Reinhold Hess for the paper “Statistical postprocessing of ensemble forecasts for 
severe weather at Deutscher Wetterdienst“. Ensemble Forecasting rose with the understanding of the limited predictability of weather. In a perfect ensemble system, the obtained ensemble of forecasts expresses the distribution of possible weather scena ...[Read More]

NPG Paper of the Month: “Applications of matrix factorization methods to climate data”

December 7, 2020
NPG Paper of the Month: “Applications of matrix factorization methods to climate data”
Spatial patterns of geopotential height anomalies corresponding to thek-means centroids (first column), archetypes (secondcolumn), convex coding basis vectors. License: https://doi.org/10.5194/npg-27-453-2020

The September 2020 NPG Paper of the Month award goes to Dylan Harries and Terence J. O’Kane for their paper “Applications of matrix factorization methods to climate data” (https://doi.org/10.5194/npg-27-453-2020). Dylan is a postdoctoral fellow within the Oceans and Atmosphere business unit of CSIRO (Australia). His current research focuses on methods for learning reduced-order models from d ...[Read More]

NPG Paper of the Month: “Beyond univariate calibration: verifying spatial structure in ensembles of forecast fields”

October 2, 2020
NPG Paper of the Month: “Beyond univariate calibration: verifying spatial structure in ensembles of forecast fields”
Example binary exceedance verification field and a subset of ensemble fields with representative FTE histogram for threshold τ=0 found using 5000 samples. Dark blue regions indicate threshold exceedance. All verification fields have correlation length a0=2 and ensemble fields have correlation length aM=1,2,3 in rows A, B, and C, respectively. FTE histograms are density histograms with dotted line y=1 and corresponding β-score (left) and β-bias (right) annotated. License: https://doi.org/10.5194/npg-27-411-2020.

The August 2020 NPG Paper of the Month award goes to Josh Jacobson and colleagues for their paper “Beyond univariate calibration: verifying spatial structure in ensembles of forecast fields” (https://doi.org/10.5194/npg-27-411-2020). The ability to know the future has long been sought after and coveted. Yet, in contrast to prophecies and crystal balls, modern methods of prediction are ...[Read More]