Evaluating the Information from Minor Trace Gas Measurements by the Tropospheric Emission Spectrometer (TES)

Author: Karen Cady-Pereira
Date: 
December 4, 2012
Type: 
Poster presentation
Venue: 
AGU Fall Meeting 2012
Citation: 

Karen E. Cady-Pereira; Mark W. Shephard; Daven K. Henze; Liye Zhu; Robert W. Pinder; Jesse O. Bash; John T. Walker; Dylan B. Millet; Kelley C. Wells; Gill-Ran Jeong; Ming Luo; Sreelekha Chaliyakunnel (2012) Evaluating the Information from Minor Trace Gas Measurements by the Tropospheric Emission Spectrometer (TES). AGU Fall Meeting, San Francisco, CA.

 The high spectral resolution and good SNR provided by the TES instrument allow for the detection and retrieval of numerous trace species. Advanced optimal estimation algorithms have been developed to retrieve three of these, ammonia, methanol and formic acid, from TES radiances. Ammonia is currently a standard TES operational product, while methanol and formic acid will be standard products in the next TES software update (V006). Given the highly reactive nature of ammonia, with its concurrent high spatial and temporal variability, the large uncertainty in global emissions of methanol, and the large biases between measured and modeled formic acid, the air quality community has a pressing need for global information on these species; there is great interest in using these new satellite derived products, but there is often no clear idea on the information they provide.
Here we will provide a short summary of the characteristics of the retrieved products, then present results from comparisons with in situ measurements. We will discuss the distinct characteristics of point and satellite measurements and illustrate how information from the latter is related to the former. We will compare global TES ammonia and methanol measurements with outcome from the GEOS-CHEM model. These comparisons have led us to examine a potential sampling bias driven by TES insensitivity in regions with low concentrations (less than 1 ppbv) or with low thermal contrast or thick clouds. We will present results from the application of inverse methods using TES ammonia and methanol to constrain model emissions, an area of research that has showcased the value provided by satellite data. Finally, we will demonstrate the potential of a sensor with TES characteristics on a geostationary platform to provide high quality data sufficient to evaluate models of the ammonia bi-directional exchange at the surface.