Distributed input observers to integrate satellite data with 3-D atmospheric models

Abstract

Chemical transport models (CTMs) simulate the concentration of gas pollutants and particulate matter in the atmosphere. Most CTMs include significant model mismatch from the true atmosphere due to uncertainty in the inputs like meteorology and emission fields, extrapolation and simplification of experimentally-derived relationships for the process dynamics, and possibly un-accounted for atmospheric processes. In this paper we estimate uncertain parameters by utilizing daily satellite measurements of aerosol optical depth, related to particulate matter. A passivity-based input observer (PBIO) projects the high-dimensional CTM to a set of inventory variables. The passive system, in which the input and output is based on the inventories, is stable with proportional feedback. We integrate distributed PBIOs with a 3D CTM to estimate time-varying sea spray emission scaling factors across the Southern Ocean band. We find the measurement error decreases from 305% to 55% by utilizing distributed PBIOs.