  We present the application of a micro/macro parareal algorithm for a 1-D
energy balance climate model with discontinuous and non-monotone coefficients
and forcing terms. The micro/macro parareal method uses a coarse propagator,
based on a (macroscopic) 0-D approximation of the underlying (microscopic) 1-D
model. We compare the performance of the method using different versions of the
macro model, as well as different numerical schemes for the micro propagator,
namely an explicit Euler method with constant stepsize and an adaptive library
routine. We study convergence of the method and the theoretical gain in
computational time in a realization on parallel processors. We show that, in
this example and for all settings, the micro/macro parareal method converges in
fewer iterations than the number of used parareal subintervals, and that a
theoretical gain in performance of up to 10 is possible.
