A Machine Learning Examination of Methane Lifetime Differences Among Model Simulations for CCMI-1
Abstract
Advances in methods using machine learning enable us to systematically quantify the factors that cause variations in tropospheric hydroxyl radical (OH) abundances and methane lifetime (τCH4). We apply these methods to investigate both the differences in OH among models and the temporal variations in OH between 1980 and 2015. The analysis is performed on simulations conducted as part of the Chemistry-Climate Model Initiative Phase 1 (CCMI-1). Specifically, we focus on the REF-C1SD simulation, a historical run from 1980 through 2010 using specified dynamics (SD) such that meteorological fields are historically accurate. Examination of the factors driving differences in τCH4 among ten models identifies the photolysis frequency of O3 to O(1D) (JO1D), local O3 mixing ratio, the abundance of NOx (=NO+NO2), and chemical mechanisms as the largest contributors, overall. Water vapor, CO, the partitioning of NOx, and formaldehyde explain moderate differences in τCH4, while CH4, isoprene, the flux of visible light (JNO2), overhead O3 column, and temperature account for little-to-no model variation in τCH4. Application of the machine learning technique to temporal variations in OH quantifies the factors imparting an overall trend of about -2% decade-1 in τCH4 within eight CCMI simulations from 1980 to 2010. The significant contributors to that trend, in order of importance, are tropospheric O3, JO1D, NOx, and H2O, with CO also causing substantial interannual variability in OH burden despite having little long-term trend. Finally, the identified trends in τCH4 are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapor on OH and τCH4, imparting an increasing and decreasing trend, respectively, of about 0.5% decade-1. The responses due to NOx, O3 column, and temperature are also in reasonably good agreement between the two studies, though a discrepancy in the CH4 response highlights a need for further examination of the CH4 feedback on OH abundance.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.A32H..01N
- Keywords:
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- 0317 Chemical kinetic and photochemical properties;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0365 Troposphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3305 Climate change and variability;
- ATMOSPHERIC PROCESSES;
- 1610 Atmosphere;
- GLOBAL CHANGE