712 A simulation study of the ensemble-based data assimilation of satellite-borne lidar aerosol observations

Wednesday, 9 January 2013
Exhibit Hall 3 (Austin Convention Center)
Tsuyoshi Thomas Sekiyama, MRI, Tsukuba, Japan; and T. Y. Tanaka and T. Miyoshi

Handout (1.0 MB)

A four-dimensional ensemble-based data assimilation system was assessed by observing system simulation experiments (OSSEs), in which the CALIPSO satellite was emulated via simulated satellite-borne lidar aerosol observations. Its performance over a three-month period was validated according to the Method for Object-based Diagnostic Evaluation (MODE), using aerosol optical thickness (AOT) distributions in East Asia as the objects of analysis. Consequently, this data assimilation system demonstrated the ability to produce better analyses of sulfate and dust aerosols in comparison to a free-running simulation model. For example, the mean centroid distance (from the truth) over a three-month collection period of aerosol plumes was improved from 2.15 grids (≈ 600 km) to 1.45 grids (≈ 400 km) for sulfate aerosols and from 2.59 grids (≈ 750 km) to 1.14 grids (≈ 330 km) for dust aerosols; the mean area ratio (to the truth) over a three-month collection period of aerosol plumes was improved from 0.49 to 0.76 for sulfate aerosols and from 0.51 to 0.72 for dust aerosols. The satellite-borne lidar data assimilation successfully improved the aerosol plume analysis and the dust emission estimation in the OSSEs. These results present great possibilities for the beneficial use of lidar data, whose distribution is vertically/temporally dense but horizontally sparse, when coupled with a four-dimensional data assimilation system. The OSSE results strongly suggest that the use of real CALIPSO data will have a beneficial effect on obtaining more accurate sulfate and dust aerosol analyses. Furthermore, the use of the same OSSE technique will allow us to perform a prior assessment of the next-generation lidar satellite EarthCARE, which will be launched in 2015 by ESA and JAXA.
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