Articles | Volume 14, issue 12
Atmos. Chem. Phys., 14, 6261–6271, 2014
https://doi.org/10.5194/acp-14-6261-2014
Atmos. Chem. Phys., 14, 6261–6271, 2014
https://doi.org/10.5194/acp-14-6261-2014

Research article 25 Jun 2014

Research article | 25 Jun 2014

Monitoring high-ozone events in the US Intermountain West using TEMPO geostationary satellite observations

P. Zoogman1,*, D. J. Jacob2,1, K. Chance3, X. Liu3, M. Lin4, A. Fiore5, and K. Travis2 P. Zoogman et al.
  • 1Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
  • 2School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
  • 3Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  • 4Atmospheric and Ocean Sciences, Princeton University, Princeton, NJ, USA
  • 5Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA
  • *currenty at: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA

Abstract. High-ozone events, approaching or exceeding the National Ambient Air Quality Standard (NAAQS), are frequently observed in the US Intermountain West in association with subsiding air from the free troposphere. Monitoring and attribution of these events is problematic because of the sparsity of the current network of surface measurements and lack of vertical information. We present an Observing System Simulation Experiment (OSSE) to evaluate the ability of the future geostationary satellite instrument Tropospheric Emissions: Monitoring of Pollution (TEMPO), scheduled for launch in 2018–2019, to monitor and attribute high-ozone events in the Intermountain West through data assimilation. TEMPO will observe ozone in the ultraviolet (UV) and visible (Vis) bands to provide sensitivity in the lower troposphere. Our OSSE uses ozone data from the GFDL AM3 chemistry-climate model (CCM) as the "true" atmosphere and samples it for April–June 2010 with the current surface network (CASTNet –Clean Air Status and Trends Network– sites), a configuration designed to represent TEMPO, and a low Earth orbit (LEO) IR (infrared) satellite instrument. These synthetic data are then assimilated into the GEOS-Chem chemical transport model (CTM) using a Kalman filter. Error correlation length scales (500 km in horizontal, 1.7 km in vertical) extend the range of influence of observations. We show that assimilation of surface data alone does not adequately detect high-ozone events in the Intermountain West. Assimilation of TEMPO data greatly improves the monitoring capability, with little information added from the LEO instrument. The vertical information from TEMPO further enables the attribution of NAAQS exceedances to background ozone. This is illustrated with the case of a stratospheric intrusion.

Download
Altmetrics
Final-revised paper
Preprint