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