The Predictive Power of Combining Chemical and Dynamical Variables for Explaining the OH Distribution and Spatiotemporal Variability

Abstract The hydroxyl radical (OH) is chemically coupled to other atmospheric constituents including water vapor, NO x , ozone, CO, and methane that provide the sources and sinks of OH. These species have longer lifetimes than OH itself and consequently undergo atmospheric transport, allowing dynamics to indirectly affect OH. We investigated whether a combination of meteorological variables and idealized tracers can predict the OH distributions for 40°S–40°N simulated by multiple models. We find that they can explain 70% or more of the variance in July spatial anomalies in OH with the zonal mean removed at 400 hPa, and 59% or more for tropospheric column OH (tcolOH). We find two constituents observed from space, water vapor and NO 2 , can together serve as proxies for much of the 40°S–40°N spatial variability in OH at 400 hPa, especially over the ocean. Multiple linear regression (MLR) on water vapor and NO 2 columns versus tcolOH results in r 2 > 0.5 for the interannual variability in January tcolOH over more than half of the 40°S–40°N domain in most models. These results highlight the value of satellite observations of water vapor and NO 2 for constraining simulated OH variability. However, the relative sensitivity of OH to each of these two variables differs between models. Consequently, understanding individual models' relative sensitivities can help maximize the value of these observational constraints. The results of our proof‐of‐concept study are encouraging and justify additional research to fully explore the potential of other satellite‐observable variables for the development of process‐based diagnostics and constraining the spatiotemporal variations of tropospheric OH.