Convective Transport of Carbon Monoxide: An intercomparison of remote sensing observations and cloud-modeling simulations 1. Introduction The pollution generated by man impacts many of the Earth’s natural processes. One of those processes is the Earth’s atmospheric radiation balance. Gases emitted into the atmosphere experience different chemical reactions and reaction rates at different altitudes. Therefore, understanding the transport mechanisms between the surface and the free atmosphere is important for understanding the chemical composition of the atmosphere. One of the most efficient transporters of surface boundary layer air to the free troposphere is deep convection (Park 2001). Cotton et al. (1995) estimated that the entire boundary layer is vented nearly 90 times annually by clouds and cloud systems. Satellite measurements of atmospheric trace-gases generally return little information from cloudy regions. Therefore transport by convective clouds is often not ‘seen’. Nonetheless, transport by convection is critical for identifying and modeling long-range transport of all surface-based species. Our goal is to identify how well the TES instrument quantifies the convective transport of pollution in comparison to model simulations, and determine if any correlation exists on which to develop a parameterization scheme to improve current observations. –Parameterization based upon cloud optical depth and typical mass flux, or between radar reflectivity and mass flux 2.Data Sources The Tropospheric Emission Spectrometer (TES) instrument onboard the AURA spacecraft resolves infrared radiances of atmospheric variables including CO and ozone. –Level 2 NADIR data available for both global scans and step & stare scans –5 x 8 km footprint every 120 km (GS), 40 km (S&S) –Carbon Monoxide resolved at the 4.7 μm wavelength 25 vertical levels with greatest degrees of freedom at 500 hPa Background CO prior to convection from a chemical transport model such as MOZART or GEOS-Chem Post convection chemical profiles from the 2-D Goddard Cumulus Ensemble model 3. Method Locating intersection scenarios between a TES scan and convection is the first step toward determining how well TES observes convective transport and creating parameterizations. 3-continued… Outline regions of thunderstorms, and identify any back- trajectories from the DC-8 or C-130 that intercepted the area. Run the 2-D Goddard Cumulus Ensemble cloud model to generate mass fluxes of CO resulting from the storm event –The background CO field will be the TES a priori –Atmospheric conditions will be from soundings local to the storm locations, or from the GEOS model Analyze the TES data for each storm case to see if any enhancement in the CO field was measured –Identify averaging kernels to see where the greatest atmospheric sensitivity is located for each storm case Use the TES forward model code with output from the cloud model to determine what TES would have measured. Draw conclusions about the strengths and weaknesses in the current cloud-scheme for deep convection. Determine if any parameterization is feasible. 4. Storm Cases Case 1: March 9, 2006 at 0834Z over Oklahoma City, OK Case 2: March 13, 2006 at 0803Z over Chicago, IL Case 3: August 25, 2006 at 1932Z over St. Louis, MO 1.Department of Meteorology, Florida State University 2.NASA Goddard Space Flight Center,Greenbelt, MD 3.Jet Propulsion Laboratory, Pasadena, CA References Cotton, W.R. et al, 1995: Cloud Venting - A review and some new global annual estimates. Earth-Sci. Reviews, 39, Luo, Ming et al, 2006: Comparison of carbon monoxide measurements by TES and MOPITT – the influence of a priori data and instrument characteristics on nadir atmospheric species retrievals. J. Geophys. Res. SUBMITTED Park, R.J et al, 2001: Regional air pollution and its radiative forcing: Studies with a single- column chemical and radiation transport model. J. Geophys. Res., 106, 28,751 – 28,770. Jeremy Halland 1, Henry Fuelberg 1, Ken Pickering 2 and Ming Luo 3 INTEX-B Data Review Meeting, Virginia Beach, VA March 6, 2007