Abstract
The space borne measurements provide global view of atmospheric aerosol distribution. The Ozone Monitoring Instrument (OMI) on board NASAs Earth Observing System (EOS) Aura satellite is a Dutch-Finnish nadir-viewing solar backscatter spectrometer measuring in the ultraviolet and visible wavelengths. OMI measures several trace gases and aerosols that are important in many air quality and climate studies. The OMI aerosol measurements are used, for example, for detecting volcanic ash plumes, wild fires and transportation of desert dust. We present a methodology for improving the uncertainty quantification in the aerosols retrieval algorithm. We have used the OMI measurements in this feasibility study. Our focus is on the uncertainties originating from the pre-calculated aerosol models. These models are never complete descriptions of the reality. This aerosol model uncertainty is estimated using Gaussian processes with computational tools from spatial statistics. Our approach is based on smooth systematic differences between the observed and modelled reflectances. When acknowledging this model inadequacy in the estimation of aerosol optical thickness (AOT), the uncertainty estimates are more realistic. We present here a real world example of applying the methodology.
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