  In this paper we propose a continuous data assimilation (downscaling)
algorithm for the B\'enard convection in porous media using only coarse mesh
measurements of the temperature. In this algorithm, we incorporate the
observables as a feedback (nudging) term in the evolution equation of the
temperature. We show that under an appropriate choice of the nudging parameter
and the size of the mesh, and under the assumption that the observed data is
error free, the solution of the proposed algorithm converges at an exponential
rate, asymptotically in time, to the unique exact unknown reference solution of
the original system, associated with the observed (finite dimensional
projection of) temperature data. Moreover, we note that in the case where the
observational measurements are not error free, one can estimate the error
between the solution of the algorithm and the exact reference solution of the
system in terms of the error in the measurements.
