2022
DOI: 10.1088/2752-5295/ac9cc2
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Understanding recent tropospheric ozone trends in the context of large internal variability: a new perspective from chemistry-climate model ensembles

Abstract: Observational records of meteorological and chemical variables are imprinted by an unknown combination of anthropogenic activity, natural forcings, and internal variability. With a 15-member initial-condition ensemble generated from the CESM2-WACCM6 chemistry-climate model for 1950-2014, we extract signals of anthropogenic (‘forced’) change from the noise of internally arising climate variability on observed tropospheric ozone trends. Positive trends in free tropospheric ozone measured at long-term surface ob… Show more

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Cited by 13 publications
(33 citation statements)
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“…For seasonal trends, the largest difference in trends is found in JJA, followed by MAM, and similar trends are only found in SON. This finding adds to the growing body of evidence that surface trends are frequently disconnected from the general increases observed in the free troposphere (Cooper et al., 2020), as assessed by IPCC (Gulev et al., 2021), and also reproduced by a recent chemistry‐climate model simulation (Fiore et al., 2022).…”
Section: Result: Rural Surface Ozone Trendssupporting
confidence: 67%
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“…For seasonal trends, the largest difference in trends is found in JJA, followed by MAM, and similar trends are only found in SON. This finding adds to the growing body of evidence that surface trends are frequently disconnected from the general increases observed in the free troposphere (Cooper et al., 2020), as assessed by IPCC (Gulev et al., 2021), and also reproduced by a recent chemistry‐climate model simulation (Fiore et al., 2022).…”
Section: Result: Rural Surface Ozone Trendssupporting
confidence: 67%
“…Results from a further sensitivity analysis are presented in Figure S12 in Supporting Information to investigate the percentile trend estimates and uncertainties based on different starting years (1995, 1998, 2000, and 2005) and ending years (2019 and 2021). The year 1998 is selected as it represents a well‐known enhanced ozone episode that was observed across the Northern Hemisphere, and has been recently attributed to extreme biomass burning (Fiore et al., 2022). In general, the big picture remains similar, except that, (a) the lower percentile trends above California are shifted from positive over 1995–2021 toward negative over 2005–2021 (as discussed above, lower percentile trends in California are heavily affected by the pandemic years); and (b) if the estimates are based on the starting year in 1998 with unusually high ozone, its impact can be observed mainly on the reduction of trends at the higher percentiles above WNA, but the sensitivity is weak at the lower percentiles.…”
Section: Results: Trend Detection Of Free Tropospheric Ozone Based On...mentioning
confidence: 99%
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“…This suggests that a perspective focused on risk and robust decision making (Sutton 2019, Mankin et al 2020, Reed et al 2022 is more pertinent to users of climate model information than the focus on a 'best-estimate' . This is increasingly being recognized by application communities dependent on climate science, such as climate-related health impacts (Garcia-Menendez et al 2017, Fiore et al 2022 or water resource management (Harding et al 2012, Chegwidden et al 2019, Smith et al 2022. A current example is the scoping of new guidelines for the management of the Colorado River in the Western U.S.…”
Section: Implications For Societymentioning
confidence: 99%
“…These ensemble members have different initial conditions for all Earth system model components (ocean, atmosphere, etc.). Additional ensemble members are generated from each of these three initial conditions by slightly perturbing the atmosphere initial conditions (more details about the ensemble can be found in Fiore et al [37]; our current ensemble is 12 members). These ensemble members represent 12 different possibilities for trends in atmospheric composition and meteorological variables from 1950 to 2014, with each ensemble member representing a climate system state that could have arisen under the same forcing scenario.…”
Section: Model Simulationsmentioning
confidence: 99%