  This paper presents a method for the numerical treatment of
reaction-convection-diffusion problems with parameter-dependent coefficients
that are arbitrary rough and possibly varying at a very fine scale. The
presented technique combines the reduced basis (RB) framework with the recently
proposed super-localized orthogonal decomposition (SLOD). More specifically,
the RB is used for accelerating the typically costly SLOD basis computation,
while the SLOD is employed for an efficient compression of the problem's
solution operator requiring coarse solves only. The combined advantages of both
methods allow one to tackle the challenges arising from parametric
heterogeneous coefficients. Given a value of the parameter vector, the method
outputs a corresponding compressed solution operator which can be used to
efficiently treat multiple, possibly non-affine, right-hand sides at the same
time, requiring only one coarse solve per right-hand side.
