A Study on Quality Control for AIRS Total Ozone Data within Typhoon Sinlaku(2008)

Total column ozone data contains useful meteorological information and was shown to be helpful to numerical weather forecasts of mesoscale storm systems and hurricanes when assimilated (Jiang et al, 2003; Wu and Zou, 2008). AIRS provides twice daily its observations at any specific areas (except for polar areas). Total column ozone data can be retrieved from AIRS infrared multi-channel radiance observations. However, about 30% AIRS ozone data are flagged as of bad quality and most of them are located in regions where errors of precipitable water are more than 35% or cloud fraction is greater than 90% . In this study, a quality control scheme is proposed using a regression model which links total column ozone to model's mean potential vorticity (MPV), which is developed using data from previous days. Outliers are identified using a biweight algorithm. Results from this QC method is compared with AIRS traditionally quality flags for typhoon Sinlaku (2008). Results suggest that criteria for setting AIRS traditionally quality flags for the total column ozone data could be loosened to allow more data to be used for typhoon study. The detail results will be presented at the conference.