The hydroxyl radical, OH, controls the lifetime of methane (CH4), ozone-depleting substances, and numerous other gases relevant to climate and air quality. Current global OH constraints rely on budget closure of long-lived gases such as methyl chloroform (MCF). Though powerful, these methods are sensitive to uncertainties in emissions and provide limited spatiotemporal information. Furthermore, budget closure is becoming less viable as the abundance of MCF and similar compounds declines. There is a clear need for new constraints on OH, especially those that can bridge the scale-gap between globally-integrated and process-level information. Reducing systematic bias in OH is crucial for understanding long-term trends of CH4 and other gases, simulating tropospheric O3 production, and projecting future atmospheric composition. We will develop new constraints on the spatial and temporal variability of near-global tropospheric OH concentrations ([OH]) and production rates (POH). The foundation of this work is the strong steady-state relationship between OH and formaldehyde (HCHO). Recently, our group has synthesized observations from the Atmospheric Tomography (ATom) mission with OMI HCHO column retrievals to estimate tropospheric column [OH] over the remote troposphere. We will extend these products across the full OMI satellite record to elucidate the spatial and temporal variability of global remote OH. This research entails three linked objectives: Evaluation of HCHO retrievals in remote environments. We will inter-compare and validate multiple HCHO retrievals with a specific focus on remote ocean regions. Our goal is to identify and minimize systematic biases and robustly characterize uncertainties, thereby increasing confidence in satellite HCHO observations in remote environments. Refinement of HCHO scaling factors. We will utilize multiscale model analyses to quantify drivers of the relationship between HCHO and oxidizing capacity, focusing on the influence of variability in CO, reactive VOC, and NOx. Furthermore, we will develop a method to constrain these dependencies with additional satellite observations. This effort will improve the spatial and temporal representativeness of [OH] and POH estimates. Interpretation of a long-term OH dataset. We will produce robust near-global estimates of monthly, gridded tropospheric column [OH] and POH across the OMI record (Oct. 2004 �?? present). Datasets will be validated against MCF-based global estimates and ATom observations. We will use this data to explore regional drivers of intra- and inter-annual variability in oxidizing capacity, focusing on anthropogenic and natural (e.g. lightning) perturbations. We will also make this dataset available to the community for further analyses and global model evaluation. The NOAA AC4 FY19 solicitation specifically notes a focus on �??large-scale atmospheric processes that control trace gas removal rates,�?� and our work is directly relevant to this topic across multiple scales. Constraining global OH is crucial, for example, for understanding long-term CH4 trends. This work is complementary to ongoing efforts within NOAA�??s GMD and ties in with NOAA�??s long-term climate research goals, specifically the development of �??climate intelligence�?� with regard to changing atmospheric composition and its impacts.