Trends in global tropospheric ozone inferred from a composite record of TOMS/OMI/MLS/OMPS satellite measurements and the MERRA-2 GMI simulation

Ziemke, J. R.; Oman, Luke D.; Strode, Sarah A.; Douglass, Anne R.; Olsen, Mark A.; McPeters, Richard D.; Bhartia, P. K.; Froidevaux, L.; Labow, G. J.; Witte, J. C.; Thompson, Anne M.; Haffner, D. P.; Kramarova, N. A.; Frith, S. M.; Huang, Liang‐Kang; Jaross, Glen; Seftor, C. J.; DeLand, M. T.; Taylor, Steven

doi:10.5194/acp-19-3257-2019

Cited by 145 publications

(132 citation statements)

References 45 publications

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“…The results presented here serve as a caution to calculating long-term O 3 trends with models driven by reanalysis meteorology for two reasons: (1) the obvious O 3 step changes associated with ATOVS in 1998 and including other, smaller observation system changes not discussed here and (2) the drift toward reduced biases compared to ozonesondes in the troposphere in more recent model simulation years. However, a recent paper by Ziemke et al (2019) found that tropospheric column O 3 trends in the M2 GMI Replay simulation examined here agree well with satellite measurements over the 1980-2016 period. The issues highlighted in this paper also will undoubtedly affect hindcast O 3 driven by other meteorological reanalyses, as well as other tracers and long-lived chemical species such as nitrous oxide (N 2 O).…”

Section: Discussionsupporting

confidence: 82%

The Effects of a 1998 Observing System Change on MERRA‐2‐Based Ozone Profile Simulations

Stauffer

Thompson²,

Oman³

et al. 2019

JGR Atmospheres

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Model simulations of ozone (O3) driven by meteorological reanalyses are useful for filling observational gaps and interpreting observed O3 variability and trends. However, the transport circulation of reanalysis products is impacted by changes to the observing system (the data assimilated into the reanalyses). We examine the impacts of these changes on simulated O3 from two models, Global Modeling Initiative (GMI) Chemistry Transport Model (GMI CTM) and Modern‐Era Retrospective Analysis for Research Applications version 2 (MERRA‐2) GMI Replay (M2 GMI Replay) simulation, using observations from global ozonesondes (>50,000 profiles) and satellites from 1980 to 2016. Both models are constrained by meteorology from the NASA MERRA‐2 reanalysis, and both use versions of NASA's GMI chemical mechanism. We focus on an observing system change affecting simulated O3 after 1998, associated with the assimilation of temperature and humidity data from new microwave profiling satellites. A large post‐1998 O3 increase, mainly confined to 15–20‐km altitude, of ~10 Dobson units (DU) in midlatitudes occurs in the GMI CTM, worsening the bias compared to observations. In contrast, an increase in M2 GMI Replay simulation O3 of ~10 DU is observed only near −60° latitude, reducing the bias compared to observations. The GMI CTM O3 high biases display a Quasi‐Biennial Oscillation (QBO)‐like periodicity that result from excessive transport from the tropical stratosphere to the midlatitude lower stratosphere during the QBO westerly phase. We quantify O3 discontinuities caused by MERRA‐2 observing system changes and demonstrate how the MERRA‐2 Global Modeling Initiative Replay simulation dampens the effects of these changes and QBO‐driven artifacts on simulated lower stratospheric and total O3. We caution against using simulations driven by a reanalysis to derive multidecadal O3 trends, especially prior to 1998.

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Section: Discussionsupporting

confidence: 82%

The Effects of a 1998 Observing System Change on MERRA‐2‐Based Ozone Profile Simulations

Stauffer

Thompson²,

Oman³

et al. 2019

JGR Atmospheres

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“…Parrish et al, 2014;Cooper et al, 2014;Gaudel et al, 2018;Fleming et al, 2018). Based on a combination of multiple ozone retrieval products, Ziemke et al (2019) have inferred positive trends in tropospheric ozone trends, particularly in the 2005-2016 time period.…”

Section: Introductionmentioning

confidence: 99%

An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2

et al. 2020

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Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent reanalyses (TCR-1 and TCR-2, Tropospheric Chemistry Reanalysis), have been intercompared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozonesonde observations over their predecessor versions (CAMS-iRean and TCR-1) for diurnal, synoptical, seasonal, and interannual variabilities. For instance, for the Northern Hemisphere (NH) mid-latitudes the tropospheric ozone columns (surface to 300 hPa) from the updated reanalyses show mean biases to within 0.8 DU (Dobson units, 3 % relative to the observed column) with respect to the ozone-sonde observations. The improved performance can likely be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterizations such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.Published by Copernicus Publications on behalf of the European Geosciences Union.

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“…We first evaluate model performance by comparing the simulated total column O3 with the version 8.6 merged total ozone datasets from the Solar Backscatter Ultraviolet (SBUV) (McPeters et al, 2013;Frith et al, 2014). The We then compare the tropospheric O3 column between model and values derived from a combination of measurements from 135 the Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) for January 2005 to December 2016 (Ziemke et al, 2019). The OMI/MLS tropospheric ozone column (TCO) is determined by subtracting the MLS stratospheric ozone column (SCO) from OMI total column ozone each day at each grid point from 60°S to 60°N.…”

Section: Model Evaluation With Satellite Observationsmentioning

confidence: 99%

“…The data set has included a +2 DU offset correction and a -0.5 DU/decade 140 drift correction following evaluation with ozonesondes, cloud slicing measurements, and the OMI row anomaly. More detailed description of this dataset is given in Ziemke et al (2019). We select the same definition of the tropopause pressure for the model simulation to calculate tropospheric column ozone in the model.…”

Section: Model Evaluation With Satellite Observationsmentioning

confidence: 99%

Stratospheric impact on the Northern Hemisphere winter and spring ozone interannual variability in the troposphere

Liu¹,

Rodríguez²,

Oman³

et al. 2019

Preprint

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Abstract. In this study we use O3 and stratospheric O3 tracer simulations from the high-resolution Goddard Earth Observing System, Version 5 (GEOS-5) Replay run (MERRA-2 GMI at 0.5° model resolution ~ 50 km) and observations from ozonesondes to investigate the interannual variation and vertical extent of the stratospheric ozone impact on tropospheric ozone. Our work focuses on the winter and spring seasons over North America and Europe. The model reproduces the observed interannual variation of tropospheric O3, except for the Pinatubo period from 1991 to 1995 over the region of North America. Ozonesonde data show a negative ozone anomaly in 1992–1994 following the Pinatubo eruption, with recovery thereafter. The simulated anomaly is only half the magnitude of that observed. Our analysis suggests that the simulated Stratosphere-troposphere exchange (STE) flux deduced from the analysis might be too strong over the North American (50° N–70° N) region after the Mt. Pinatubo eruption in the early 1990s, masking the impact of lower stratospheric O3 concentration on tropospheric O3. European ozonesonde measurements show a similar but weaker O3 depletion after the Mt. Pinatubo eruption, which is fully reproduced by the model. Analysis based on a stratospheric O3 tracer (StratO3) identifies differences in strength and vertical extent of stratospheric ozone influence on the tropospheric ozone interannual variation (IAV) between North America and Europe. Over North America, the StratO3 IAV has a significant impact on tropospheric O3 from the upper to lower troposphere and explains about 60 % and 66 % of simulated O3 IAV at 400 hPa, ~ 11 % and 34 % at 700 hPa in winter and spring respectively. Over Europe, the influence is limited to the middle to upper troposphere, and becomes much smaller at 700 hPa. The stronger and deeper stratospheric contributions in the tropospheric O3 IAV over North America shown by the model is likely related to ozonesondes' being closer to the polar vortex in winter with lower geopotential height, lower tropopause height, and stronger coupling to the Arctic Oscillation in the lower troposphere (LT) than over Europe.

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Trends in global tropospheric ozone inferred from a composite record of TOMS/OMI/MLS/OMPS satellite measurements and the MERRA-2 GMI simulation

Cited by 145 publications

References 45 publications

The Effects of a 1998 Observing System Change on MERRA‐2‐Based Ozone Profile Simulations

The Effects of a 1998 Observing System Change on MERRA‐2‐Based Ozone Profile Simulations

An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2

Stratospheric impact on the Northern Hemisphere winter and spring ozone interannual variability in the troposphere

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