An Overview of Ozone and Precursor Temporal and Spatial Variability in DISCOVER-AQ Study Regions
Monday, 15 December 2014: 1:40 PM
One of the major goals of the NASA Earth Venture - 1 DISCOVER-AQ project is to better quantify the spatial and temporal variability of pollutant gases in the lower troposphere, as this information is required for the design of new atmospheric chemistry satellite instruments. This objective has been addressed through a series of four field experiments (Baltimore-Washington, San Joaquin Valley, Houston, and Denver). DISCOVER-AQ observations that lend themselves to this analysis include in-situ measurements of trace gases by the NASA P-3B aircraft (spiral profiles and constant altitude flight legs), trace gas columns from the surface-based network of Pandora UV/Vis spectrometers, trace gas columns from the Airborne Compact Atmospheric Mapper (ACAM) on board the NASA King Air, and in-situ tethered balloon observations. We make use of the P-3B observations to assess spatial variability and evaluate regional model simulations through the use of structure functions, which yield the mean difference in column abundance or mixing ratio between observation points at specified distances apart over a designated length of time. Agreement between the observations and model output indicates that the model can be used to derive more comprehensive variability analyses than are possible with the aircraft data. Subsequently, the structure function approach can be used to compute the mean difference over various time intervals to yield temporal variability estimates. The continuous Pandora data also allow for comprehensive temporal variability estimates for the tropospheric column, as does the frequent tethered balloon profiling at fixed sites for the lower portion of the boundary layer. Additionally, the fine-resolution pixels of the ACAM data allow further detailed spatial analysis. A second DISCOVER-AQ objective is to assess the relationship between column observations and surface air quality. We examine the temporal variability of these measurements over the daytime hours, and the strength of the relationship between sites through correlation analyses.