A new Bayesian method was recently introduced for developing coarse-grain (CG) force fields for molecular dynamics. The CG models designed for dissipative particle dynamics (DPD) are optimized based on trajectory matching. Here we extend this method to improve transferability across thermodynamic conditions. We demonstrate the capability of the method by developing a CG model of n-pentane from constant-NPT atomistic simulations of bulk liquid phases and we apply the CG-DPD model to the calculation of the surface tension of the liquid-vapor interface over a large range of temperatures. The coexisting densities, vapor pressures, and surface tensions calculated with different CG and atomistic models are compared to experiments. Depending on the database used for the development of the potentials, it is possible to build a CG model which performs very well in the reproduction of the surface tension on the orthobaric curve.