Quantifying the loss of information in source attribution problems using the adjoint method in global models of atmospheric chemical transport
Mauricio Santillana

TL;DR
This paper investigates how effectively global atmospheric models can identify pollution sources over time, revealing a critical 2-day window beyond which source reconstruction becomes unreliable due to numerical diffusion.
Contribution
It introduces a quantitative method using the adjoint approach to assess the loss of information in source attribution within global chemical transport models.
Findings
Reconstruction accuracy drops significantly after 2 days.
Estimated effective length scale of 1700 km for source detection.
Method applicable to other regional and global models.
Abstract
It is of crucial importance to be able to identify the location of atmospheric pollution sources in our planet. Global models of atmospheric transport in combination with diverse Earth observing systems are a natural choice to achieve this goal. It is shown that the ability to successfully reconstruct the location and magnitude of an instantaneous source in global chemical transport models (CTMs) decreases rapidly as a function of the time interval between the pollution release and the observation time. A simple way to quantitatively characterize this phenomenon is proposed based on the effective -undesired- numerical diffusion present in current Eulerian CTMs and verified using idealized numerical experiments. The approach presented consists of using the adjoint-based optimization method in a state-of-the-art CTM, GEOS-Chem, to reconstruct the location and magnitude of a realistic…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAtmospheric and Environmental Gas Dynamics · Atmospheric chemistry and aerosols · Atmospheric Ozone and Climate
