Abstract Korea will launch the Geostationary Environment Monitoring Spectrometer (GEMS) instrument in 2018 onboard the Geostationary Korean Multi-Purpose Satellite to monitor tropospheric gas concentrations with high temporal and spatial resolutions.… Click to show full abstract
Abstract Korea will launch the Geostationary Environment Monitoring Spectrometer (GEMS) instrument in 2018 onboard the Geostationary Korean Multi-Purpose Satellite to monitor tropospheric gas concentrations with high temporal and spatial resolutions. The purpose of this study is to examine the performance of total column ozone (TCO) measurements from ground-based Pandora and Brewer instruments that will be used for validation of the GEMS ozone product. Satellite measurements can be used to detect erroneous outliers at a particular ground station, which deviate significantly from co-located satellite measurements relative to other stations. This is possible because a single satellite retrieval algorithm is used to process the entire satellite dataset, and instrument characteristics typically change slowly over the life of the satellite. Thus, the short-term stability (months) of satellite measurements can be used to estimate the performance of the ground-based measurement network as well as to identify potential problems at individual stations. As a reference for satellite ozone measurements, we have selected TCO data derived from OMI-TOMS V8.5 algorithm, because it is a robust algorithm that has been well studied to identify its various error sources. We validated ground-based Brewer and Pandora TCO measurements using OMI-TOMS TCO data collected over South Korea from March 2012 to December 2014. The Brewer TCO measurements at Pohang showed significant deviation from overall seasonal variation during the study period. In addition, in the presence of clouds, Pandora TCO measurements are unusually ∼7% higher than OMI-TOMS TCO data. To filter out these cloud-contaminated data, we applied a Kalman filter to the Pandora measurements. The diurnal variation in the Kalman-filtered Pandora data agrees well with the Brewer data, and the correlation of Kalman-filtered Pandora data with OMI-TOMS TCO is significantly improved from 0.89 to 0.99 at Seoul and from 0.93 to 0.99 at Busan.
               
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