Clouds, convection, and ozone

Convection affects the ozone distribution by lifting clean surface air to the middle and upper troposphere, reducing ozone concentrations aloft. However, convection over polluted regions lifts ozone precursors and thus contributes to ozone formation. I compare chemistry climate model output to observations from OMI/MLS to understand the link between clouds, convection, and ozone.

  • Strode, S. A., A. R. Douglass, J. R. Ziemke, M. Manyin, J. E. Nielsen and L. D. Oman, L. D. (2017), A model and satellite-based analysis of the tropospheric ozone distribution in clear versus convectively cloudy conditions. Journal of Geophysical Research: Atmospheres, 122, doi:10.1002/2017JD27015.
  • Ziemke, J. R., S. A. Strode, A. R. Douglass, J. Joiner, A. Vasilkov, L. D. Oman, J. Liu, S. E. Strahan, P. K. Bhartia, and D. P. Haffner (2017), A cloud-ozone data product from Aura OMI and MLS satellite measurements, Atmos. Meas. Tech., 10, 4067-4078, doi:10.5194/amt-10-4067-2017.

Trace gas variability and trends

Changes in emissions and meteorology can drive long-term trends and year-to-year variability in pollutant concentrations. I use global chemical transport and chemistry-climate models to analyze observed trends and variability in order to understand the drivers of pollutant trends and variability.

  • Strode, S.A., J.R. Ziemke, L.D. Oman, L.N. Lamsal, M.A. Olsen, J. Liu (2019), Global changes in the diurnal cycle of surface ozone, Atmos. Environ., 199, 323-333, doi:10.1016/j.atmosenv.2018.11.028.
  • Ziemke, J.R., L.D. Oman, S.A. Strode, A.R. Douglass, et al. (2019), Trends in global tropospheric ozone inferred from a composite record of TOMS/OMI/MLS/OMPS satellite measurements and the MERRA-2 GMI simulation , Atmos. Chem. Phys., 19, 3257-3269, doi:10.5194/acp-19-3257-2019.
  • Strode, S. A., H. M. Worden, M. Damon, A. R. Douglass, B. N. Duncan, L. K. Emmons, J. -F. Lamarque, M. Manyin, L. D. Oman, J. M. Rodriguez, S. E. Strahan, and S. Tilmes (2016), Interpreting space-based trends in carbon monoxide with multiple models Atmos. Chem. Phys., 16, 7285-7294, doi:10.5194/acp-16-7285-2016.
  • Strode, S. A., J. M. Rodriguez, J. A. Logan, O. R. Cooper, J. C. Witte, L. N. Lamsal, M. Damon, B. Van Aartsen, S.D. Steenrod, and S.E. Strahan (2015), Trends and Variability in Surface Ozone over the United States, J. Geophys. Res. Atmos., 120, doi:10.1002/2014JD022784.
  • Strode, S. A., and S. Pawson (2013), Detection of carbon monoxide trends in the presence of Interannual variability, J. Geophys. Res. Atmos., 118, 12,257–12,273, doi:10.1002/2013JD020258.
  • Reidmiller, D. R., D. A. Jaffe, D. Chand, S. A. Strode, P. C. Swartzendruber, G. M. Wolfe, and J. A. Thornton (2009), Interannual variability of long-range transport as seen at the Mt. Bachelor Observatory, Atmos. Chem. Phys., 9, 557-572, doi:10.5194/acp-9-557-2009.

Long-range transport of pollutants

Atmospheric transport across long distances allows pollutant emissions in one region to impact concentrations in another. I use global models to analyze the transport of pollutants including carbon monoxide and mercury. The goal of this research is to quantify the contribution of different sources to the concentrations at receptor regions.

  • Strode, S. A., J. Liu, L. Lait, R. Commane, B. Daube, S. Wofsy, A. Conaty, P. Newman, and M. Prather (2018), Forecasting carbon monoxide on a global scale for the ATom-1 aircraft mission: insights from airborne and satellite observations and modeling, Atmos. Chem. Phys., 18, 10955-10971, doi:10.5194/acp-18-10955-2018.
  • Strode, S. A., L. E. Ott, S. Pawson, and T. W. Bowyer (2012), Emission and transport of cesium-137 from boreal biomass burning in the summer of 2010, J. Geophys. Res., 117, D09302, doi:10.1029/2011JD017382.
  • Strode, S. A., L. Jaeglé, D. A. Jaffe, P. C. Swartzendruber , N. E. Selin, C. Holmes, and R. M. Yantosca, Trans-Pacific transport of mercury (2008), J. Geophys. Res., 113(D15305), doi:10.1029/2007JD009428.

Chemistry and Climate

Methane (CH4) is an important greenhouse gas and ozone precursor. Its lifetime in the troposphere depends on concentrations of the hydroxyl radical (OH), while the primary sinks for OH are carbon monoxide (CO) and CH4. Simulating the CO-CH4-OH system is one of the challenges for chemistry climate models. I am interested in quantifying the sources of uncertainty in simulations of CO and CH4.

  • Nicely, J.M., T.P. Canty, M. Manyin, L.D. Oman, R.J. Salawitch, S.D. Steenrod, S.E. Strahan and S.A. Strode (2018), Changes in global tropospheric OH expected as a result of climate change over the last several decades, Journal of Geophysical Research: Atmospheres, 123, 10,774–10,795, doi:10.1029/2018JD028388.
  • Elshorbany, Y. F., B. N. Duncan, S. A. Strode, J. S. Wang, and J. Kouatchou (2016), The description and validation of the computationally Efficient CH4–CO–OH (ECCOHv1. 01) chemistry module for 3-D model applications, Geosci. Model Devel., 9, 2, 799-822, doi:10.5194/gmd-9-799-2016.
  • Strode, S. A., B. N. Duncan, E. A. Yegorova, J. Kouatchou, J. R. Ziemke, and A. R. Douglass (2015), Implications of carbon monoxide bias for methane lifetime and atmospheric composition in chemistry climate models, Atmos. Chem. Phys., 15, 11789-11805, doi:10.5194/acp-15-11789-2015.