The High Order Conservative Method for the Parameters Estimation in a PM2.5 Transport Adjoint Model

Abstract

We propose to apply Piecewise Parabolic Method (PPM), a high order and conservative interpolation, for the parameters estimation in a PM2.5 transport adjoint model. Numerical experiments are taken to show the accuracy of PPM in space and its ability to increase the well-posedness of the inverse problem. Based on the obtained results, the PPM provides better interpolation quality by employing much fewer independent points. Meanwhile, this method is still well-behaved in the case of insufficient observations. In twin experiments, two prescribed parameters, including the initial condition (IC) and the source and sink (SS), are successfully estimated by the PPM with lower interpolation errors than the Cressman interpolation. In practical experiments, simulation results show good agreement with the observations of the period when the 21th APEC summit took place.