<p>Modelling the near-wake region becomes more important as turbines are positioned with a relatively smaller spacing due to site restrictions, leading to significant power losses and increased fatigue loading. These effects can be mitigated by actively steering the wake away from the downstream turbine. This paper presents an approach to analytically estimate the wake deficit within the near-wake region by modifying the curled wake model. This is done by incorporating a new initial condition at the rotor using an azimuth-dependent Gaussian profile, an adjusted turbulence model in the near-wake region and the far-wake region and an iterative process to determine the velocity field, while considering the relation of the pressure gradient and accounting the conservation of mass. Comparison with high-fidelity simulations for a single turbine case shows a good correlation of the wake profile for both a non-misaligned and a misaligned case. Validation is performed using field lidar data, where the wake is captured within the near-wake region. The model shows a good correlation with the measurement data. The performance of the modified curled wake model is further analysed within a five-turbine array, where the determined power output shows a significant improvement in comparison to other existing models. The implemented modification indicates a better representation of the near-wake region and will improve the calculation of the optimum misalignment angles for closely spaced turbines. This will aid the process of developing more accurate control-oriented wake steering models.</p>