Assessing Fine Scale Variability of Urban Pollution with Aircraft Data and the Implications For Satellite Validation and Model Evaluation

Abstract:

A frequent issue when quantitatively comparing local in-situ measurements of atmospheric composition to larger-scale averages is that the representativeness of the in-situ measurement at the coarser resolution needs to be assessed. This is a concern when comparing point measurements and satellite pixel data during validation exercises, given typical satellite spatial resolutions of several km, and similarly for comparison with model grid values during model evaluation studies. The spatial representativeness at a given time depends on the heterogeneity of trace gas emissions, prevailing meteorology and atmospheric transformations. The temporal representativeness for non-coincident observations depends on source diurnal variation and changing atmospheric mixing as occurs, for example, with the evolution of the planetary boundary layer during the day.

In this presentation, we consider several statistical measures of pollutant fine-scale variability, and use the uniquely comprehensive coverage of aircraft remote sensing observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument to investigate spatial and temporal representativeness of NO₂ point values to larger-scale averages over urban and surrounding areas. We concentrate particularly on data taken during the 2016 Korea-United States Air Quality (KORUS-AQ) Field Study in Seoul, South Korea, and also contrast with USA field campaign data. Finally, we make recommendations for assessing representativeness uncertainty of point measurements for satellite validation and model evaluation using the example of the recently launched Korean Geostationary Environment Monitoring Spectrometer (GEMS) satellite instrument, and discuss how the results can be used to inform spatiotemporal measurement requirements during satellite instrument design.