Preprints
https://doi.org/10.5194/acp-2022-215
https://doi.org/10.5194/acp-2022-215
 
29 Mar 2022
29 Mar 2022
Status: this preprint is currently under review for the journal ACP.

Modelling atmospheric carbonyl sulfide using gross primary productivity to constrain vegetative uptake

Michael P. Cartwright1,2, Richard J. Pope3,4, Jeremy J. Harrison1,2, Martyn P. Chipperfield3,4, Chris Wilson3,4, Wuhu Feng3,5, David P. Moore1,2, and Parvadha Suntharalingam6 Michael P. Cartwright et al.
  • 1School of Physics and Astronomy, Space Park Leicester, University of Leicester, Leicester, UK
  • 2National Centre for Earth Observation, Space Park Leicester, University of Leicester, Leicester, UK
  • 3School of Earth and Environment, University of Leeds, Leeds, UK
  • 4National Centre for Earth Observation, University of Leeds, Leeds, UK
  • 5National Centre for Atmospheric Science, University of Leeds, Leeds, UK
  • 6School of Environmental Sciences, University of East Anglia, Norwich, UK

Abstract. We use the TOMCAT 3-D chemical transport model with a balanced flux inventory to simulate the global distribution of atmospheric carbonyl sulfide (OCS). This is compared with limb-sounding satellite observations made by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) and surface flask measurements made worldwide at 14 National Oceanic and Atmospheric Administration – Earth System Research Laboratory (NOAA-ESRL) sites. By scaling gross primary productivity (GPP) output from the Joint UK Land Environment Simulator (JULES), we provide a new estimation of global OCS vegetative uptake. This is calculated by scaling GPP according to a leaf relative uptake (LRU) term, yielding a global yearly atmospheric uptake of approximately 629 Gg S, which is toward the lower estimates from recent studies. To compensate for this larger vegetative sink, we scale oceanic emissions of OCS up to an annual mean of 689 Gg S, focused over the tropical ocean region. We combine our OCS fluxes to derive a new inventory which was used in a TOMCAT simulation from 2004–2018 to allow and investigate the annual distribution and seasonality of OCS as well as long term comparisons with available measurements. The simulation matches satellite and surface observations to within their uncertainties in most instances. When compared to co-located ACE-FTS OCS profiles between 5 km and 30 km, the simulation remains within 5 % of the measurements throughout the majority of this region and lies within the standard deviation of these measurements. At the surface, the model captures background concentrations at most of the surface sites to within the maximum and minimum of the seasonal measurements. Compared to a control TOMCAT simulation using the existing Kettle et al. (2002) benchmark flux inventory, errors in the surface comparisons are reduced by as much as 57 %. Our new inventory reduces the average difference in the modelled seasonal amplitude compared to the surface measurements from ±40 % to ±34 %. Other key improvements include better representation of OCS seasonality at North Hemisphere continental sites, as well as a better match in background concentration at tropical Hawaiin sites.

Michael P. Cartwright et al.

Status: open (until 21 Jul 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-215', Anonymous Referee #1, 21 May 2022 reply

Michael P. Cartwright et al.

Data sets

Carbonyl Sulfide (OCS) TOMCAT Model Data Michael Peter Cartwright https://doi.org/10.5281/zenodo.6368542

Michael P. Cartwright et al.

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Short summary
A 3-D chemical transport model, TOMCAT, is used to simulate global atmospheric carbonyl sulfide (OCS) distribution. We test the validity of using gross primary productivity to estimate OCS vegetative uptake and show that the array of emissions used offers an improvement on a control set of emissions. Model simulations also compare adequately with surface and atmospheric observations, suitably capturing seasonality of OCS and background concentration.
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