01 Feb 2022
01 Feb 2022
Status: this preprint is currently under review for the journal ACP.

Investigating the Global OH Radical Distribution Using Steady-State Approximations and Satellite Data

Matilda A. Pimlott1, Richard J. Pope1,2, Brian J. Kerridge3,4, Barry G. Latter3,4, Diane S. Knappett3,4, Dwayne E. Heard5, Lucy J. Ventress3,4, Richard Siddans3,4, Wuhu Feng1,6, and Martyn P. Chipperfield1,2 Matilda A. Pimlott et al.
  • 1School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
  • 2National Centre for Earth Observation, University of Leeds, Leeds, LS2 9JT,UK
  • 3Remote Sensing Group, STFC Rutherford Appleton Laboratory, Chilton, Oxfordshire, OX11 0QX, UK
  • 4National Centre for Earth Observation, STFC Rutherford Appleton Laboratory, Chilton, Oxfordshire, OX11 0QX, UK
  • 5School of Chemistry, University of Leeds, Leeds, LS2 9JT, UK
  • 6National Centre for Atmospheric Science, University of Leeds, Leeds, LS2 9PH, UK

Abstract. We present a novel approach to derive indirect global information on the hydroxyl radical (OH), one of the most important atmospheric oxidants, using state-of-art satellite trace gas observations (key sinks and sources of OH) and a steady-state approximation (SSA). This is a timely study as OH observations are predominantly from spatially sparse field and infrequent aircraft campaigns, so there is a requirement for further approaches to infer spatial and temporal information on OH and its interactions with important climate (e.g. methane, CH4) and air quality (e.g. nitrogen dioxide, NO2) trace gases. Due to the short lifetime of OH (~1.0 s), SSAs of varying complexities can be used to model its concentration and offer a tool to examine the OH budget in different regions of the atmosphere. Here, we use the well-evaluated TOMCAT three-dimensional chemistry transport model to identify atmospheric regions where different complexities of the SSAs are representative of OH. In the case of a simplified SSA (S-SSA), where we have observations of ozone (O3), carbon monoxide (CO), CH4 and water vapour (H2O) from the Infrared Atmospheric Sounding Interferometer (IASI) on-board ESA’s MetOp-A satellite, it is most representative of OH between 600 and 700 hPa (though suitable between 400–800 hPa) within ~20 % of TOMCAT modelled OH. The same S-SSA is applied to aircraft measurements from the Atmospheric Tomography Mission (ATom) and compares well with the observed OH concentrations within ~30 % yielding a correlation of 0.78. We apply the S-SSA to IASI data spanning 2008–2017 to explore the global long-term inter-annual variability of OH. Relative to the 10-year mean, we find that global annual mean OH anomalies ranged from −3.1 % to +4.4 %, with the largest spread in the tropics between −7.0 % and +7.7 %. Investigation of the individual terms in the S-SSA over this time period suggests that O3 and CO were the key drivers of variability in the production and loss of OH. For example, large enhancement in the OH sink during the positive 2015/2016 ENSO event was due to large scale CO emissions from drought induced wildfires in South East Asia). The methodology described here could be further developed as a constraint on the tropospheric OH distribution as further satellite data becomes available in the future.

Matilda A. Pimlott et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-79', Anonymous Referee #1, 22 Feb 2022
  • RC2: 'Comment on acp-2022-79', Anonymous Referee #2, 23 Mar 2022
  • AC1: 'Author Comment on acp-2022-79', Matilda Pimlott, 13 May 2022

Matilda A. Pimlott et al.

Matilda A. Pimlott et al.


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Short summary
We present a new method to derive global information of the hydroxyl radical (OH), an important atmospheric oxidant. OH controls the lifetime of trace gases important to air quality and climate. We use satellite observations of ozone, carbon monoxide, methane and water vapour in a simple expression to derive OH around 3–4 km altitude. The derived OH compares well to model and aircraft OH data. We then apply the method to 10 years of satellite data to study the inter-annual variability of OH.