The 2nd CFD Challenge Predicting Patient-Specific Hemodynamics at Rest and Stress through an Aortic Coarctation provides patient-specific flow and pressure data. In this work, a multiscale 0D-3D strategy is tested to match the given data. The 3D outlet boundary conditions for the supra-aortic vessels are represented by three-element Windkessel models. In order to estimate the Windkessel parameters at these outlets, a 0D lumped parameter model for the full aorta is considered. The parameters in such a 0D model are estimated by a sequential estimation method, the unscented Kalman filter. The filtering approach estimates the parameters such that the results of the 0D model closely match the measured data: flow waveforms in the ascending and diaphragmatic aorta, mean flow rates in the supra-aortic vessels, and the pressure waveform in the ascending aorta. Information from the 3D model is taken into account in the full 0D model. This process is repeated for the two separate cases of rest and stress conditions to estimate separate sets of parameters for the two physiological states. Results such as the pressure gradient across the coarctation, comparison with target values and more detailed time or spatial variations are presented. Modelling choices and assumptions about how the data are interpreted are then discussed.