DISCOVER-AQ Science Objectives
DISCOVER-AQ, a NASA Earth Venture program funded mission, stands for Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality.
Near-surface pollution is one of the most challenging problems for Earth observations from space. However, with an improved ability to monitor pollution from satellites from DISCOVER-AQ, scientists could make better air quality forecasts, more accurately determine the sources of pollutants in the air and more closely determine the fluctuations in emissions levels. In short, the more accurate data scientists have at hand, the better society is able to deal effectively with lingering pollution problems.
DISCOVER-AQ will make three major contributions to atmospheric science:
1. Relate column observations to surface conditions for aerosols and key trace gases O3, NO2, and CH2O. Researchers will ask, How well do column and surface observations correlate?; What additional variables (e.g., boundary layer depth, humidity, surface type) appear to influence these correlations?; and On what spatial scale is information about these variables needed (e.g., 5 km, 10 km, 100 km) to interpret column measurements?
Expected outcome: Improved understanding of the extent to which column observations (as observed from space) can be used to diagnose surface conditions.
2. Characterize differences in diurnal variation of surface and column observations for key trace gases and aerosols. Researchers will ask, 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?; and Do column and surface conditions tend to correlate better for certain times of day?
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.
3. Examine horizontal scales of variability affecting satellites and model calculations. Researchers will ask, 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?; and How do these fine-scale gradients influence model calculations and assimilation of satellite observations?
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.