The application of Data Assimilation (DA) methods in Computational Fluid Dynamics (CFD) problems is a concept actively being explored to couple CFD with Experimental Fluid Dynamics data. Here, Particle Image Velocimetry (PIV) data are assimilated in an OpenFOAM based CFD solver to calculate the velocity and pressure fields of the turbulent flow past a surface mounted cube inside an atmospheric boundary layer for three planes belonging to the symmetry plane of the flow. At first, the SIMPLE algorithm is used to correct both pressure and velocity fields, with the PIV data used to formulate the initial and boundary conditions. The Reynolds stresses are calculated directly from the PIV data instead of using a turbulence model. Next, we use two implementations of the nudging method and two formulations of the Kalman Filter in order to assimilate the PIV data into the iterative SIMPLE procedure. A grid independence study is performed, and the performance of the different methods is assessed. The CFD predicted pressure field is in good agreement with pressure measurements on the cube surface. The results also show that the SIMPLE based correction step already leads to a significant reduction of both the mean and the variance of the continuity errors as well as the difference between the original PIV data and the resulting velocity fields. The application of the DA methods, particularly the KF, leads to minor further improvement of the results but does improve convergence of the CFD solver.