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: “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).
