Preprints
https://doi.org/10.5194/gmd-2021-173
https://doi.org/10.5194/gmd-2021-173
Submitted as: development and technical paper
 | 
20 Jul 2021
Submitted as: development and technical paper |  | 20 Jul 2021
Status: this preprint was under review for the journal GMD but the revision was not accepted.

An improved carbon greenhouse gas simulation in GEOS-Chem version 12.1.1

Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones

Abstract. Understanding greenhouse gas–climate processes and feedbacks is a fundamental step in understanding climate variability and its links to greenhouse gas fluxes. Chemical transport models are the primary tool for linking greenhouse gas fluxes to their atmospheric abundances. Hence accurate simulations of greenhouse gases are essential. Here, we present a new simulation in the GEOS-Chem chemical transport model that couples the two main greenhouse gases: carbon dioxide (CO2) and methane (CH4), along with the indirect effects of carbon monoxide (CO), based on their chemistry. Our updates include the online calculation of the chemical production of CO from CH4 and the online production of CO2 from CO, both of which were handled offline in the previous versions of these simulations. We discuss differences between the offline (uncoupled) and online (coupled) calculation of the chemical terms and perform a sensitivity simulation to identify the impact of OH on the results. We compare our results with surface measurements from the NOAA Global Greenhouse Gas Reference Network (NOAA GGGRN), total column measurements from the Total Carbon Column Observing Network (TCCON) and aircraft measurements from the Atmospheric Tomography Mission (ATom). Relative to the standard uncoupled simulation, our coupled results show better agreement with measurements. We use the remaining measurement-model differences to identify sources and sinks that are over or underestimated in the model. We find underestimated OH fields when calculating the CH4 loss and CO production from CH4. Biomass burning emissions and secondary production are underestimated for CO in the Southern Hemisphere and we find enhanced anthropogenic sources in the Northern Hemisphere. We also find significantly stronger chemical production of CO2 in tropical land regions, especially in the Amazon. The model-measurement differences also highlight biases in the calculation of CH4 in the stratosphere and in vertical mixing that impacts all three gases.

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Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-173', Anonymous Referee #1, 01 Sep 2021
    • AC1: 'Reply on RC1', Beata Bukosa, 22 Oct 2021
  • RC2: 'Comment on gmd-2021-173', Anonymous Referee #2, 08 Sep 2021
    • AC2: 'Reply on RC2', Beata Bukosa, 22 Oct 2021
  • RC3: 'Comment on gmd-2021-173', Anonymous Referee #3, 13 Sep 2021
    • AC3: 'Reply on RC3', Beata Bukosa, 22 Oct 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-173', Anonymous Referee #1, 01 Sep 2021
    • AC1: 'Reply on RC1', Beata Bukosa, 22 Oct 2021
  • RC2: 'Comment on gmd-2021-173', Anonymous Referee #2, 08 Sep 2021
    • AC2: 'Reply on RC2', Beata Bukosa, 22 Oct 2021
  • RC3: 'Comment on gmd-2021-173', Anonymous Referee #3, 13 Sep 2021
    • AC3: 'Reply on RC3', Beata Bukosa, 22 Oct 2021
Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones
Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones

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Short summary
Human activities led to rising levels of greenhouse gases (carbon dioxide (CO2), methane (CH4), carbon monoxide (CO)) in the atmosphere, threatening our future. We use models and measurements to predict and understand the climatological impact of these gases. Here, we describe a new simulation in the GEOS-Chem model that uses a more accurate method to simulate CO2, CH4 and CO, through their chemical dependence. Relative to the original simulations our results agree better with measurements.