Stochastic Parameterization Using Compressed Sensing: Application to the Lorenz-96 Atmospheric Model
Published in Tellus A: Dynamic Meteorology and Oceanography, 2022
Recommended citation: Mukherjee, A., Aydogdu, Y., Ravichandran, T. and Namachchivaya, N.S. (2022). "Stochastic Parameterization Using Compressed Sensing: Application to the Lorenz-96 Atmospheric Model." Tellus A: Dynamic Meteorology and Oceanography. 74(2022), pp.300–317. http://doi.org/10.16993/tellusa.42
This paper deals with the parameterization of the Lorenz-96 model with two time-scale simplified ordinary differential equations describing advection, damping and forcing. We apply compressed sensing to parameterize the unresolved variables in terms of resolved variables.