Preprints
https://doi.org/10.5194/amt-2022-226
https://doi.org/10.5194/amt-2022-226
04 Nov 2022
 | 04 Nov 2022
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

New plume comparison metrics for the inversion of passive gases emissions

Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet

Abstract. In the next few years, numerous satellites with high-resolution instruments dedicated to the imaging of atmospheric gaseous compounds will be launched, to finely monitor emissions of greenhouse gases and pollutants. Processing the resulting images of plumes from cities and industrial plants to infer the emissions of these sources can be challenging. In particular traditional atmospheric inversion techniques, relying on objective comparisons to simulations with atmospheric chemistry transport models may poorly fit the observed plume due to modelling errors rather than due to uncertainties in the emissions.

The present article discusses how these images can be properly compared to simulated concentrations to limit the weight of modelling errors due to the meteorology used to analyse the images. For such comparisons, the usual pixel-wise norm may not be a good option, because it is subject to the double penalty issue inherent to its local definition. This issue is characterised by a mutation of any position shift into significant amplitude discrepancies. To circumvent this issue, we propose to either provide an upstream correction of the position misfit between the observed and simulated plumes in the usual norm or to use a non-local metric based on the optimal transport theory, such as the Wasserstein distance.

All the metrics are evaluated using first a catalogue of analytical plumes and then more realistic plumes simulated with a mesoscale Eulerian atmospheric transport model, with an emphasis on the sensitivity of the metrics to position mismatch and the concentration values within the plumes. As expected, the metrics with the upstream correction are found to be less sensitive to position errors in both analytical and realistic conditions. Furthermore, in realistic cases, we evaluate the weight of changes in the norm and the direction of the four-dimensional wind fields in our metric values. This comparison highlights the link between differences in the synoptic-scale winds direction and position error. It is found that discrepancies between two plume images due to wind direction errors in the meteorological conditions are less penalised by our new metrics with the upstream correction than without, thus avoiding the double penalty issue.

Pierre J. Vanderbecken et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-226', Anonymous Referee #2, 09 Nov 2022
    • AC1: 'Reply on RC1', Pierre Vanderbecken, 07 Jan 2023
  • RC2: 'Comment on amt-2022-226', Anonymous Referee #1, 21 Nov 2022
    • AC2: 'Reply on RC2', Pierre Vanderbecken, 07 Jan 2023

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-226', Anonymous Referee #2, 09 Nov 2022
    • AC1: 'Reply on RC1', Pierre Vanderbecken, 07 Jan 2023
  • RC2: 'Comment on amt-2022-226', Anonymous Referee #1, 21 Nov 2022
    • AC2: 'Reply on RC2', Pierre Vanderbecken, 07 Jan 2023

Pierre J. Vanderbecken et al.

Data sets

Passive gas plume database for metrics comparison Pierre J. Vanderbecken https://doi.org/10.5281/zenodo.6958047

Pierre J. Vanderbecken et al.

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Short summary
Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties to limit their impact on the corrections made to emissions. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.