Accounting for Transport Error in Inversions: An Urban Synthetic Data Experiment.

ABSTRACT: We present and discuss the use of a high-dimensional computational method for atmospheric inversions that incorporates the space-time structure of transport and dispersion errors. In urban environments, transport and dispersion errors are largely the result of our inability to capture the true underlying transport of greenhouse gas (GHG) emissions to observational sites. Motivated by the impact of transport model error on estimates of fluxes of GHGs using in situ tower-based mole-fraction observations, we specifically address the need to characterize transport error structures in high-resolution large-scale inversion models. We do this using parametric covariance functions combined with shrinkage-based regularization methods within an Ensemble Transform Kalman Filter inversion setup. We de

SUBMITTER: Ghosh S 

PROVIDER: S-EPMC8365727 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature