Variational Stochastic Parameterisations and Their Applications to Primitive Equation Models

Abstract We present a numerical investigation into the stochastic parameterisations of Primitive Equations (PE) using Stochastic Advection by Lie Transport (SALT) and Forcing (SFLT) frameworks. These frameworks were chosen due to their structure-preserving introduction stochasticity, which decomposes transport velocity fluid momentum drift parts, respectively. In this paper, we develop new calibration methodology implement decomposition SFLT compare with Lagrangian path implemented for SALT. The resulting are then integrated numerically modification FESOM2 code. For certain choices parameters, show that SALT causes an increase in eddy kinetic energy field improvement spatial spectrum. also shows improvements these areas, though lesser extent. does, however, have drawback excessive downwards diffusion temperature.