Science Objective 1: Relate column observations to surface conditions for aerosols and key trace gases O3, NO2, and CH2O
Expected outcome: Improved understanding of the extent to which column observations (as observed from space) can be used to diagnose surface conditions
- How well do column and surface observations correlate?
- What additional variables (e.g., boundary layer depth, humidity, surface type) appear to influence these correlations?
- On what spatial scale is information about these variables needed (e.g., 5 km, 10 km, 100 km) to interpret column measurements?
Science Objective 2: Characterize differences in diurnal variation of surface and column observations for key trace gases and aerosols
Expected Outcome: Improved understanding of diurnal variability as it influences the interpretation of satellite observations from both
LEO and GEO perspectives and improved knowledge of the factors controlling diurnal variability for testing and improving models
- How do column and surface observations differ in their diurnal variation?
- How do emissions, boundary layer mixing, synoptic transport, and chemistry interact to affect these differences?
- Do column and surface conditions tend to correlate better for certain times of day?
Image caption: Diurnal variation in column integrated and surface NO2 are expected to exhibit important differences as shown in this
simulation by EPA’s CMAQ model for Houston, Texas.
Credit: J. Fishman and D. Byun.
Science Objective 3: Examine horizontal scales of variability affecting satellites and model calculations
Expected outcome: Improved interpretation of satellite observations in regions of steep gradients,
improved representation of urban plumes in models, and more effective assimilation of satellite data by models
- How do different meteorological and chemical conditions cause variation in the spatial scales for urban plumes?
- What are typical gradients in key variables at scales finer than current satellite and model resolutions?
- How do these fine-scale gradients influence model calculations and assimilation of satellite observations?
Image caption: Example calculations of HOx radicals and O3 production for a range of NOx abundances.
Precise location of the peak and general behavior vary with radical source strength.
Greatest sensitivity tends to fall near 1000 pptv of NOx which is considered a threshold for polluted conditions.
Credit: J. Crawford, NASA Langley Photochemical Box Model.