NASA NTRS · 20210003454
There are many compounds for which OH abstraction rate constants may be required.
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DeMore, W.. 1997-07-14. Estimation Method for OH Abstraction Rate Constants. https://ntrs.nasa.gov/citations/20210003454
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Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG). Its 100-year global warming potential (GWP) is 25 times larger than that for carbon dioxide. The 100-yr integrated GWP of CH4 is sensitive to changes in OH levels. Methane's atmospheric growth rate was estimated to be more than 10 ppb yr(exp -1) in 1998 but less than zero in 2001, 2004 and 2005 (Kirschke et al., 2013). Since 2006, the CH4 is increasing again. This phenomena is yet not well understood. Oxidation of CH4 by OH is the main loss process, thus affecting the oxidizing capacity of the atmosphere and contributing to the global ozone background. Current models typically use an annual cycle of offline OH fields to simulate CH4. The implemented OH fields in these models are typically tuned so that simulated CH4 growth rates match that measured. For future and climate simulations, the OH tuning technique may not be suitable. In addition, running full chemistry, multi-decadal CH4 simulations is a serious challenge and currently, due to computational intensity, almost impossible.
During the last few years, tremendous progress has been made to develop an efficient parameterization module using agile machine learning techniques. The aim of this module is to provide dynamic response of the tropospheric hydroxyl radical (OH) to its major drivers, including trace gases, aerosols, clouds, and meteorology. This module, named ECCOH (pronounced “echo”) and implemented in NASA’s GEOS-5 global model, offers an unrealized opportunity to unravel the convoluted response of OH to its underlying drivers while approaching the accuracy of full-chemistry without incurring excessive computational costs, making it suitable for climate models. However, the accurate representation of OH in ECCOH poses challenges due to the lack of representation of some of its critical inputs such as the abundance of NO 2 and HCHO concentrations. As such, we leverage the well-characterized satellite observations of NO2 and HCHO columns from Aura OMI to enhance their representation in ECCOH using an optimal interpolation method for the time period of 2005 - present. We show how the inclusion of OMI information can affect the spatiotemporal variability and long-term trends of OH, CO, and CH 4 across the globe. Additionally, we underscore the necessity of obtaining high-fidelity information regarding tropospheric ozone from the southern hemisphere from space, a region currently lacking full verification in models, posing a challenge to get a reasonable amount of chemical sink for CH 4 .