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

Stauffer, Ryan M.; Thompson, A. M.; Oman, Luke D.; Strahan, S. E.

doi:10.1029/2019jd030257

Cited by 23 publications

(34 citation statements)

References 39 publications

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“…The negative ozone anomalies during the period of 1992-1996 are consistent with the chemical and dynamical perturbations following the 15 June 1991 eruption of Mt. Pinatubo (Hadjinicolaou et al, 1997;Stenchikov et al, 2002;Rozanov et al, 2002). The negative ozone anomaly in 2015-2016 is associated with stratospheric circulation changes caused by the unusually warm ENSO event coinciding with a disrupted quasi-biennial oscillation (QBO) during that period (Tweedy et al, 2017;Diallo et al, 2018).…”

Section: Winter and Spring Ozone Iav In The Lower Stratosphere And Trsupporting

confidence: 62%

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

et al. 2020

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Abstract. In this study we use ozone and stratospheric ozone tracer simulations from the high-resolution (0.5∘×0.5∘) Goddard Earth Observing System, Version 5 (GEOS-5), in a replay mode to study the impact of stratospheric ozone on tropospheric ozone interannual variability (IAV). We use these simulations in conjunction with ozonesonde measurements from 1990 to 2016 during the winter and spring seasons. The simulations include a stratospheric ozone tracer (StratO3) to aid in the evaluation of the impact of stratospheric ozone IAV on the IAV of tropospheric ozone at different altitudes and locations. The model is in good agreement with the observed interannual variation in tropospheric ozone, except for the post-Pinatubo period (1992–1994) 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 (50–70∘ N) region after the Mt. Pinatubo eruption in the early 1990s, masking the impact of lower stratospheric ozone concentration on tropospheric ozone. European ozonesonde measurements show a similar but weaker ozone depletion after the Mt. Pinatubo eruption, which is fully reproduced by the model. Analysis based on the stratospheric ozone tracer identifies differences in strength and vertical extent of stratospheric ozone impact on the tropospheric ozone interannual variation (IAV) between North America and Europe. Over North American stations, the StratO3 IAV has a significant impact on tropospheric ozone from the upper to lower troposphere and explains about 60 % and 66 % of the simulated ozone IAV at 400 hPa and ∼11 % and 34 % at 700 hPa in winter and spring, respectively. Over European stations, the influence is limited to the middle to upper troposphere and becomes much smaller at 700 hPa. The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), assimilated fields exhibit strong longitudinal variations over Northern Hemisphere (NH) mid-high latitudes, with lower tropopause height and lower geopotential height over North America than over Europe. These variations associated with the relevant variations in the location of tropospheric jet flows are responsible for the longitudinal differences in the stratospheric ozone impact, with stronger effects over North America than over Europe.

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Section: Winter and Spring Ozone Iav In The Lower Stratosphere And Trsupporting

confidence: 62%

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

et al. 2020

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“…We cannot expect agreement with observations for a climate simulation to be better, and thus both O3v1 and O3v2 can be considered a match. The large pre-OMI to post-OMI shift in UCI SDs may be caused by the ECMWF data assimilation shift in satellite systems (Wargan et al, 2017), as this has been documented for the MERRA-2 meteorological fields (Douglass et al, 2017;Stauffer et al, 2019). We present a Taylor diagram for the mean annual SCO cycle [1] and the SD/SCO [2] in Fig.…”

Section: Stratospheric Column Ozonementioning

confidence: 99%

Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model

et al. 2021

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Abstract. Stratospheric ozone affects climate directly as the predominant heat source in the stratosphere and indirectly through chemical reactions controlling other greenhouse gases. The U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) implemented a new ozone chemistry module that improves the simulation of the sharp tropopause gradients, replacing a version based partly on long-term average climatologies that poorly represented heating rates in the lowermost stratosphere. The new O3v2 module extends seamlessly into the troposphere and preserves the naturally sharp cross-tropopause gradient, with 20 %–40 % less ozone in this region. Additionally, O3v2 enables the diagnosis of stratosphere–troposphere exchange flux of ozone, a key budget term lacking in E3SMv1. Here, we evaluate key features in ozone abundance and other closely related quantities in atmosphere-only E3SMv1 simulations driven by observed sea surface temperatures (SSTs, years 1990–2014), comparing them with satellite observations of ozone and also with the University of California, Irvine chemistry transport model (UCI CTM) using the same stratospheric chemistry scheme but driven by European Centre forecast fields for the same period. In terms of stratospheric column ozone, O3v2 shows reduced mean bias and improved northern midlatitude variability, but it is not quite as good as the UCI CTM. As expected, SST-forced E3SMv1 simulations cannot synchronize with observed quasi-biennial oscillations (QBOs), but they do show the typical QBO pattern seen in column ozone. This new O3v2 E3SMv1 model mostly retains the same climate state and climate sensitivity as the previous version, and we recommend its use for other climate models that still use ozone climatologies.

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“…Models have likewise been relied upon to derive tropospheric OH abundance and its evolution. Stevenson et al (2006) found a large spread in τ CH 4 (6.3 to 12.5 years) from a suite of atmospheric chemistry models in an analysis performed more than a decade ago. A total of 7 years later, the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) generated both historical (Naik et al, 2013) and future (Voulgarakis et al, 2013) simulations from numerous chemistry-climate models, revealing still large discrepancies not only in present-day τ CH 4 (with values ranging from 7.1 to 14.0 years) but also in how τ CH 4 is expected to vary through the year 2100 given common emissions scenarios.…”

Section: Introductionmentioning

confidence: 97%

A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1

et al. 2020

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Abstract. The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH4), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (τCH4), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of τCH4 differences among 10 models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO1D), the mixing ratio of tropospheric ozone (O3), the abundance of nitrogen oxides (NOx≡NO+NO2), and details of the various chemical mechanisms that drive OH. Water vapour, carbon monoxide (CO), the ratio of NO:NOx, and formaldehyde (HCHO) explain moderate differences in τCH4, while isoprene, methane, the photolysis frequency of NO2 by visible light (JNO2), overhead ozone column, and temperature account for little to no model variation in τCH4. We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in τCH4 during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O3, JO1D, NOx, and H2O, with CO also causing substantial interannual variability in OH burden. 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 vapour on OH and τCH4, imparting an increasing and decreasing trend of about 0.5 % decade−1, respectively. The responses due to NOx, ozone column, and temperature are also in reasonably good agreement between the two studies.

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

Cited by 23 publications

References 39 publications

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

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

Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model

A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1

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