Abstract

Abstract. The hydroxyl radical (OH) is the main tropospheric oxidant and the main sink for atmospheric methane. The global abundance of OH has been monitored for the past decades using atmospheric methyl chloroform (CH3CCl3) as a proxy. This method is becoming ineffective as atmospheric CH3CCl3 concentrations decline. Here we propose that satellite observations of atmospheric methane in the short-wave infrared (SWIR) and thermal infrared (TIR) can provide an alternative method for monitoring global OH concentrations. The premise is that the atmospheric signature of the methane sink from oxidation by OH is distinct from that of methane emissions. We evaluate this method in an observing system simulation experiment (OSSE) framework using synthetic SWIR and TIR satellite observations representative of the TROPOMI and CrIS instruments, respectively. The synthetic observations are interpreted with a Bayesian inverse analysis, optimizing both gridded methane emissions and global OH concentrations. The optimization is done analytically to provide complete error accounting, including error correlations between posterior emissions and OH concentrations. The potential bias caused by prior errors in the 3-D seasonal OH distribution is examined using OH fields from 12 different models in the ACCMIP archive. We find that the satellite observations of methane have the potential to constrain the global tropospheric OH concentration with a precision better than 1 % and an accuracy of about 3 % for SWIR and 7 % for TIR. The inversion can successfully separate the effects of perturbations to methane emissions and to OH concentrations. Interhemispheric differences in OH concentrations can also be successfully retrieved. Error estimates may be overoptimistic because we assume in this OSSE that errors are strictly random and have no systematic component. The availability of TROPOMI and CrIS data will soon provide an opportunity to test the method with actual observations.

Highlights

  • The hydroxyl radical (OH) is the main oxidant in the troposphere, responsible for the oxidation of a wide range of gases including nitrogen oxides (NOx ≡ NO + NO2), sulfur dioxide (SO2), carbon monoxide (CO), methane, and other volatile organic compounds (VOCs)

  • The expected availability in the coming years of new high-density satellite data from TROPOMI in the short-wave infrared (SWIR) (Hu et al, 2018) and CrIS in the thermal infrared (TIR) (Gambacorta et al, 2016) motivates the assessment of the potential of these data to provide a continuous means for monitoring global tropospheric OH concentrations

  • We considered short-wave infrared (SWIR) TROPOMI and thermal infrared (TIR) CrIS as target satellite instruments for this application, since methane retrievals from these instruments are expected to be available in the www.atmos-chem-phys.net/18/15959/2018/

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Summary

Introduction

The hydroxyl radical (OH) is the main oxidant in the troposphere, responsible for the oxidation of a wide range of gases including nitrogen oxides (NOx ≡ NO + NO2), sulfur dioxide (SO2), carbon monoxide (CO), methane, and other volatile organic compounds (VOCs). A number of studies have used SWIR observations from the SCIAMACHY and GOSAT satellite instruments to infer methane emissions through inverse analyses Most of these studies have assumed OH to be known (Bergamaschi et al, 2009, 2013; Spahni et al, 2011; Fraser et al, 2013, 2014; Monteil et al, 2013; Houweling et al, 2014; Alexe et al, 2015; Pandey et al, 2015; Turner et al, 2015), while a few have optimized methane emissions together with OH concentrations using methyl chloroform measurements (Cressot et al, 2014, 2016). The expected availability in the coming years of new high-density satellite data from TROPOMI in the SWIR (Hu et al, 2018) and CrIS in the TIR (Gambacorta et al, 2016) motivates the assessment of the potential of these data to provide a continuous means for monitoring global tropospheric OH concentrations

Observing system simulation experiment
Model simulation
Synthetic observations
Inversion
Joint optimization of global τCOHH4 and methane emission rates
Impact of errors in prior OH distributions
Findings
Conclusions
Full Text
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