Remote Sensing · 2018 · 27 citations · 47 references
Environmental MonitoringEngineeringAir QualityEarth System ScienceConservative DownscalingEarth ScienceNo2 Column DensitiesOrganic GeochemistryAtmospheric ScienceMicrometeorologySpatial ResolutionAtmospheric SensingAtmosphere Of EarthGeographyRadiation MeasurementAstroinformaticsAir Pollution ClimatologyAtmospheric Impact AssessmentAtmospheric TransportAstrochemistryRemote SensingAtmospheric ProcessAir PollutionSatellite-detected Chemical Compositions
A conservative downscaling technique was applied when comparing nitrogen dioxide (NO2) column densities from space-borne observations and a fine-scale regional model. The conservative downscaling was designed to enhance the spatial resolution of satellite measurements by applying the fine-scale spatial structure from the model, with strict mass conservation at each satellite footprint pixel level. With the downscaling approach, NO2 column densities from the Ozone Monitoring Instrument (OMI; 13 × 24 km nadir footprint resolution) and the Global Ozone Monitoring Experiment-2 (GOME-2; 40 × 80 km) show excellent agreement with the Community Multiscale Air Quality (CMAQ; 4 × 4 km) NO2 column densities, with R = 0.96 for OMI and R = 0.97 for GOME-2. We further introduce an approach to reconstruct surface NO2 concentrations by combining satellite column densities and simulated surface-to-column ratios from the model. Compared with the Environmental Protection Agency’s (EPA) Air Quality System (AQS) surface observations, the reconstructed surface concentrations show a good agreement; R = 0.86 for both OMI and GOME-2. This study demonstrates that the conservative downscaling approach is a useful tool to compare coarse-scale satellites with fine-scale models or observations in urban areas for air quality and emissions studies. The reconstructed fine-scale surface concentration field could be used for future epidemiology and urbanization studies.
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The Kain–Fritsch Convective Parameterization: An Update
John S. Kain · Journal of Applied Meteorology · 2004 · 5K citations · Full text