Trends and Interannual Variability of the Hydroxyl Radical in the Remote Tropics During Boreal Autumn Inferred From Satellite Proxy Data

Daniel C. Anderson,Bryan N. Duncan, Junhua Liu,Julie M. Nicely, Sarah A. Strode,Melanie B. Follette-Cook, Amir H. Souri, Jerry R. Ziemke, Gonzalo Gonzalez-Abad,Zolal Ayazpour

GEOPHYSICAL RESEARCH LETTERS(2024)

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摘要
Despite its importance for the global oxidative capacity, spatially resolved trends and variability of the hydroxyl radical (OH) are poorly constrained. We demonstrate the utility of a tropospheric column OH (TCOH) product, created from machine learning and satellite proxy data, in determining the spatial variability in trends of tropical OH over the oceans during September through November. While OH increases domain-wide by 2.1%/decade from 2005-2019, we find significant spatial heterogeneity in regional trends, with decreases in some areas of 2.5%/decade. Our analysis of the trends in the proxy data indicate anthropogenic-driven changes in emissions of OH drivers as well as increasing temperatures cause these trends. This OH product is potentially a significant advance in constraining OH spatial variability and serves as a useful complement to existing tools in understanding the atmospheric oxidative capacity. Comprehensive observations of TCOH are required to assess the fidelity of this method. Hydroxyl is a chemical that removes many gases from the atmosphere, including methane, an important greenhouse gas. To understand recent trends in methane, we must also understand recent trends in hydroxyl. Because of various limitations, we unfortunately do not have long-term, direct observations of hydroxyl. To address this problem, we have developed a machine learning model that uses satellite observations of variables relevant to hydroxyl chemistry and variability to calculate hydroxyl. We demonstrate that this product can be used to understand trends and variability of hydroxyl over the tropical oceans. While, on average, hydroxyl increases from 2005-2019, we show that this is not a universal trend and that hydroxyl actually decreases in multiple regions over the same time period. Using satellite observations of various chemicals, we demonstrate that changes in emissions due to human activity and increases in temperature cause many of these trends. This product is potentially a significant advance in understanding changes in hydroxyl and could be a useful complement to more traditional methods in understanding atmospheric methane. Satellite proxies can constrain the spatial distribution of trends and variability of the hydroxyl radical in the tropics Changes in biomass burning, temperature, and other emissions lead to large spatial heterogeneity in hydroxyl radical trends More direct observations of the hydroxyl radical and its drivers are needed to further validate the fidelity of our methodology
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hydroxyl,machine learning,trends and variability,ENSO
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