Impact of 4DVAR Assimilation of AIRS Total Column Ozone Observations on the Simulation of Hurricane Earl

The Atmospheric Infrared Sounder（AIRS） provides twice-daily global observations of brightness temperature, which can be used to retrieve the total column ozone with high spatial and temporal resolution.In order to apply the AIRS ozone data to numerical prediction of tropical cyclones, a four-dimensional variational（4DVAR） assimilation scheme on selected model levels is adopted and implemented in the mesoscale non-hydrostatic model MM5. Based on the correlation between total column ozone and potential vorticity（PV）, the observation operator of each level is established and five levels with highest correlation coefficients are selected for the 4DVAR assimilation of the AIRS total column ozone observations. The results from the numerical experiments using the proposed assimilation scheme for Hurricane Earl show that the ozone data assimilation affects the PV distributions with more mesoscale information at high levels first and then influences those at middle and low levels through the so-called asymmetric penetration of PV anomalies.With the AIRS ozone data being assimilated, the warm core of Hurricane Earl is intensified, resulting in the improvement of other fields near the hurricane center. The track prediction is improved mainly due to adjustment of the steering flows in the assimilation experiment.

Quality control of AIRS total column ozone data within tropical cyclones

The Atmospheric Infrared Sounder （AIRS） provides infrared radiance observations twice daily, which can be used to retrieve total column ozone with high spatial resolution. However, it was found that almost all of the ozone data within typhoons and hurricanes were flagged to be of bad quality by the AIRS original quality control （QC） scheme. This determination was based on the ratio of total precipitable water （TPW） error divided by TPW value, where TPW was an AIRS retrieval product. It was found that the difficulty in finding total column ozone data that could pass AIRS QC was related to the low TPW employed in the AIRS QC algorithm. In this paper, a new two-step QC scheme for AIRS total column ozone is developed. A new ratio is defined which replaces the AIRS TPW with the zonal mean TPW retrieved from the Advanced Microwave Sounding Unit. outliers when the new The first QC step is to remove ratio exceeds 33%. Linear regression models between total column ozone and mean potential vorticity are subsequently developed with daily updates, which are required for future applications of the proposed total ozone QC algorithm to vortex initialization and assimilation of AIRS data. In the second QC step, observations that significantly deviate from the models are further removed using a biweighting algorithm. Numerical results for two typhoon cases and two hurricane cases show that a large amount of good quality AIRS total ozone data is kept within Tropical Cyclones after implementing the proposed QC algorithm.