MPLNET lidar data assimilation in the ECMWF MACC-II Aerosol system: evaluation of model performances at NCU lidar station

Simone Lolli; Ellsworth J. Welton; Angela Benedetti; Luke Jones; Martin Suttie; Sheng-Hsiang Wang

doi:10.1117/12.2068201

20 October 2014 MPLNET lidar data assimilation in the ECMWF MACC-II Aerosol system: evaluation of model performances at NCU lidar station

Simone Lolli, Ellsworth J. Welton, Angela Benedetti, Luke Jones, Martin Suttie, Sheng-Hsiang Wang

Author Affiliations +

Proceedings Volume 9246, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing X; 92460I (2014) https://doi.org/10.1117/12.2068201
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands

Abstract

Atmospheric profiles of the optical aerosol properties through the retrieved backscattering or extinction coefficients by lidar measurements can improve drastically the MACC-II aerosol model performances on vertical dimension. Currently the MODIS Aerosol Optical Depth data (both from Terra and Aqua) are assimilated into the model. Being a columnintegrated quantity, these data do not modify the model aerosol vertical profile, especially if the aerosols are not interactive with the meteorology. Since 1999, the MPLNET lidar network provides continuously lidar data measurements from worldwide permanent stations (currently 21), deployed from the Arctic to the Antarctic regions and in tropical and equatorial zones. The purpose of this study is to show the first preliminary results of the intercomparison of MPLNET lidar data against the ECWMF MACC-II aerosol model, for a selected MPLNET permanent observational site at National Central University of Taiwan. Assessing the model performances it is the first step for future near-real time lidar data assimilation into MACC-II aerosol model forecast.

Citation Download Citation

Simone Lolli, Ellsworth J. Welton, Angela Benedetti, Luke Jones, Martin Suttie, and Sheng-Hsiang Wang "MPLNET lidar data assimilation in the ECMWF MACC-II Aerosol system: evaluation of model performances at NCU lidar station", Proc. SPIE 9246, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing X, 92460I (20 October 2014); https://doi.org/10.1117/12.2068201

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