The impact of internal climate variability on OH trends between 2005 and 2014

• Published in: Environmental research letters Vol. 19; no. 6; pp. 64032 - 64041
• Main Authors: Zhu, Qindan, Fiore, Arlene M, Correa, Gus, Lamarque, Jean-Francois, Worden, Helen
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.06.2024
• Subjects: Air pollution; Air quality; chemistry-climate interaction; Climate models; Climate variability; Greenhouse gases; hydroxyl radical; Hydroxyl radicals; Initial conditions; machine learning; Meteorological parameters; methane; Neural networks; Oxidants; Oxidizing agents; Satellite observation; satellite observations; Trends; South America
• DOI: 10.1088/1748-9326/ad4b47
• ISSN: 1748-9326

The hydroxyl radical (OH) lies at the nexus of climate and air quality as the primary oxidant for both reactive greenhouse gases and many hazardous air pollutants. To better understand the role of climate variability on spatiotemporal patterns of OH, we utilize a 13-member ensemble of the Community Earth System Model version 2-Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6), a fully coupled chemistry-climate model, spanning the years 1950–2014. Ensemble members vary only in their initial conditions of the climate state in 1950. We focus on the final decade of the simulation, 2005–2014, when prior studies disagree on the signs of the global OH trends. The ensemble mean global airmass-weighted mean tropospheric column OH ( Ω TOH ), which is an estimate of the forced signal, increases by 0.06%/year between 2005 and 2014 while regional Ω TOH trends range from −0.56%/year over Southern Europe to +0.64%/year over South America. We show that ten-year Ω TOH trends are strongly affected by internal climate variability, as the spread of Ω TOH trends across the ensemble varies between 0.23%/year in Asia and 1.53%/year in South America. We train a fully connected neural network to emulate the Ω TOH simulated by the CESM2-WACCM6 model and combine it with satellite observations to interpret the role of OH chemical proxies. While the OH chemical proxies are subject to internal variability, the impact of internal variability on Ω TOH trends is primarily due to the meteorological parameters except for South America. Forced trends in global mean Ω TOH do not unambiguously emerge from trends driven by internal variability over the 2005–2014 period. The observation-constrained Ω TOH presents opposite trends due to climate variability, resulting in varying conclusions on the attribution of OH to CH 4 trends.