Extended Abstract (64K)11A.3
Assimilation of SBUV/2 ozone retrievals with the Local Ensemble Transform Kalman Filter
David D. Kuhl, University of Maryland, College Park, MD; and I. Szunyogh and R. B. Pierce
We present results on the assimilation of ozone concentration observations from the Solar Backscatter Ultraviolet (SBUV/2) instrument using the Local Ensemble Transform Kalman Filter (LETKF) data assimilation technique. The SBUV/2 instrument, which is flown on the NOAA 16 and 17 satellites, provides observations of the global ozone concentration in the total atmospheric column, as well as, vertical profiles derived from the ratio of the observed backscattered Earth spectral radiance to the incoming solar spectral irradiance. The model we use for the assimilation of the SBUV/2 observations is the 2004 operational version of the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) model at a reducedT62/L28 resolution. We assimilate the ozone observations multivariately with the other meteorological observations. Thus, the assimilation of ozone observations affects the analysis of the meteorological parameters through the flow-dependent background error covariance matrix of the LETKF. The analysis-forecast system is first evaluated based on identical twin experiments. In particular, we compare the strategies of assimilating the total column ozone versus assimilating vertical ozone profiles. Then we show assimilation results with observations of the real atmosphere at different vertical resolutions of the model, increasing the number of model levels from 28 to 64.
Session 11A, Advanced Methods for Data Assimilation—III
Wednesday, 14 January 2009, 4:00 PM-5:30 PM, Room 130
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