Models severely overestimate surface ozone in the Southeast US during summertime which has implications for the design of air quality regulations. We use a model (GEOS-Chem) to interpret ozone observations from a suite of observations taken during August–September 2013. The model is unbiased relative to observations below 1 km but is biased high at the surface. We attribute this bias to model representation error, an underestimate in low-cloud, and insufficient treatment of vertical mixing.
Models severely overestimate surface ozone in the Southeast US during summertime which has...
Resolving ozone vertical gradients in air quality models
Katherine R. Travis1,Daniel J. Jacob1,2,Christoph A. Keller3,4,Shi Kuang5,Jintai Lin6,Michael J. Newchurch7,and Anne M. Thompson8Katherine R. Travis et al.Katherine R. Travis1,Daniel J. Jacob1,2,Christoph A. Keller3,4,Shi Kuang5,Jintai Lin6,Michael J. Newchurch7,and Anne M. Thompson8
1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
2Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
3Universities Space Research Association, Columbia, MD, USA
4NASA Goddard Space Flight Center, Greenbelt, MD, USA
5Earth System Science Center, University of Alabama in Huntsville, Huntsville, AL 35805, USA
6Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
7Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, AL 35805, USA
8Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
2Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
3Universities Space Research Association, Columbia, MD, USA
4NASA Goddard Space Flight Center, Greenbelt, MD, USA
5Earth System Science Center, University of Alabama in Huntsville, Huntsville, AL 35805, USA
6Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
7Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, AL 35805, USA
8Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Received: 27 Jun 2017 – Accepted for review: 31 Jul 2017 – Discussion started: 01 Aug 2017
Abstract. Models severely overestimate surface ozone in the Southeast US during summertime and this overestimation has implications for the design of air quality regulations. We use the GEOS-Chem model to interpret ozone observations from aircraft (SEAC4RS), ozonesondes (SEACIONS), and surface sites (CASTNET) in August–September 2013. After correcting for a 30–50 % NOx emission overestimate in the US EPA National Emission Inventory, we find that the model is unbiased relative to aircraft observations below 1 km. However, surface observations of maximum daily 8-h average (MDA8) ozone are still biased high in the model (averaging 48 ± 9 ppb) compared to observations (40 ± 9 ppb). The low tail in the observations (MDA8 ozone < 25 ppb) is associated with rain and is not captured by the model. The model bias decreases by 3 ppb when accounting for the subgrid vertical gradient between the lowest model level (centered 60 m above ground) and the measurement altitude (10 m). The model underestimates low cloud cover, but this underestimate is insufficient to explain the remaining surface ozone bias because the response of model ozone to cloud cover is weaker than observed. Midday ozonesondes at Huntsville, Alabama show mean decreases in ozone from 1 km to the surface of 4 ppb under clear-sky and 7 ppb under low cloud, whereas the model decreases by only 1 ppb under both conditions. By contrast, potential temperature below 1 km is well-mixed in both the observations and the model. The observations thus imply a strong asymmetry between top-down and bottom-up mixing that is missing from GEOS-Chem and appears to be insufficiently represented in current air quality models. A sensitivity simulation reducing top-down eddy diffusion and removing top-down non-local vertical transport of ozone can reproduce the observed ozone gradients in the mixed layer.
Models severely overestimate surface ozone in the Southeast US during summertime which has implications for the design of air quality regulations. We use a model (GEOS-Chem) to interpret ozone observations from a suite of observations taken during August–September 2013. The model is unbiased relative to observations below 1 km but is biased high at the surface. We attribute this bias to model representation error, an underestimate in low-cloud, and insufficient treatment of vertical mixing.
Models severely overestimate surface ozone in the Southeast US during summertime which has...
- Printer-friendly version
- Supplement
