Evaluating Observable Proxies for Variability in Atmospheric Oxidation

Atmospheric oxidation by the hydroxyl radical (OH) is a key removal process for many air pollutants and reactive greenhouse gases. Chemistry-climate models used to simulate atmospheric composition disagree on the sign of the OH response to historical and future changes in anthropogenic emissions. Developing a set of observable proxies that reliably characterize variability in OH across different atmospheric regions and time would provide much needed constraints on the models used to study interactions between atmospheric composition and the climate system. Our overarching goal is to construct a global seasonal climatology of OH sensitivity to key observable quantities that drive OH variability within broad atmospheric regions.

As an initial step towards this goal, we use observations during the Atmospheric Tomography (ATom) field campaign as a testbed to assess the feasibility of two proxies that earlier theoretical and modeling work has indicated should reflect local variability in OH. The first proxy is formaldehyde (HCHO), which reflects spatial and temporal variability in OH when HCHO is primarily produced from the oxidation of volatile organic carbon species (e.g., methane) and lost via photolysis. Analysis of the ATom measurements indicates that these conditions occur widely throughout the remote free troposphere. The second proxy is based on a set of variables controlling OH steady-state chemistry: the rate of ozone photolysis to produce O(¹D) (J_O3), the concentrations of water vapor (H₂O) and NO_x (NO_x = NO + NO₂), which together reflect major sources of OH, as well as carbon monoxide (CO), the major OH sink. A correlation analysis versus OH serves to demonstrate the conditions under which each proxy reflects spatial and temporal variability in OH. We then apply these observed relationships to evaluate global atmospheric chemistry models that archived high frequency three-dimensional chemical species during the first of the ATom field seasons (ATom-1, August 2016).

As a second step to constructing a seasonal climatology for OH variability, we turn to the NASA MERRA-2 GMI full chemistry replay simulation (driven by MERRA-2 meteorology and available at ~50km horizontal resolution from 1980-2016) to systematically examine relationships between OH and factors that can be constrained by satellite and suborbital observations (e.g. H₂O, NO₂, O₃, CO), including the two proxies described above. In our model analysis, we are also able to consider variables that cannot be observed (e.g. reaction rates) but are useful for interpretation of these relationships. Taken together, our analysis of observations and models provides a foundation for prioritizing observing strategies with the highest potential for constraining OH variability, and by extension, the chemistry-climate models used to infer its changes in space and time.