  A baroclinic model for the atmospheric jet at middle-latitudes is used as a
stochastic generator of time series of the total energy of the system.
Statistical inference of extreme values is applied to yearly maxima sequences
of the time series, in the rigorous setting provided by extreme value theory.
In particular, the Generalized Extreme Value (GEV) family of distributions is
used here. Several physically realistic values of the parameter $T_E$,
descriptive of the forced equator-to-pole temperature gradient and responsible
for setting the average baroclinicity in the atmospheric model, are examined.
The location and scale GEV parameters are found to have a piecewise smooth,
monotonically increasing dependence on $T_E$. This is in agreement with the
similar dependence on $T_E$ observed in the same system when other dynamically
and physically relevant observables are considered. The GEV shape parameter
also increases with $T_E$ but is always negative, as \textit{a priori} required
by the boundedness of the total energy of the system. The sensitivity of the
statistical inference process is studied with respect to the selection
procedure of the maxima: the roles of both the length of maxima sequences and
of the length of data blocks over which the maxima are computed are critically
analyzed. Issues related to model sensitivity are also explored by varying the
resolution of the system.
