EPJ Web of Conferences
Volume 119, 2016The 27th International Laser Radar Conference (ILRC 27)
|Number of page(s)||4|
|Section||Poster Session (Lidar Cloud Studies)|
|Published online||07 June 2016|
Evaluation of Retrieval Algorithms for Ice Microphysics Using CALIPSO/CloudSat and Earthcare
1 Research Institute for Applied Mechanics, Kyushu University, Kasuga, Fukuoka 816-8580, Japan
2 Meteological Research Institute, Japan Meteorological Agency, Tsukuba, Ibaraki 305-0052, Japan
3 V.E. Zuev Institute of Atmospheric Optics, Rus. Acad. Sci., Tomsk 634021, Russia
* Email: email@example.com
Published online: 7 June 2016
We developed lidar-radar algorithms that can be applied to Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar and CloudSat data to retrieve ice microphysics. The algorithms were the extended version of previously reported algorithm  and can treat both of nadir pointing of CALIPSO lidar period and 3°-off-nadir pointing one. We used the scattering data bank produced by the physical optics methods  and created lidar look-up tables of quasi-horizontally oriented ice plates (Q2D-plate) for nadir- and off-nadir lidar pointing periods. Then LUTs were implemented in the ice retrieval algorithms.
We performed several sensitivity studies to evaluate uncertainties in the retrieved ice microphysics due to ice particle orientation and shape. It was found that the implementation of orientation of horizontally oriented ice plate model in the algorithm drastically improved the retrieval results in both for nadir- and off-nadir lidar pointing periods. Differences in the retrieved microphysics between only randomly oriented ice model (3D-ice) and mixture of 3D-ice and Q2Dplate model were large especially in off-nadir period, e.g., 100% in effective radius and one order in ice water content, respectively. And differences in the retrieved ice microphysics among different mixture models were smaller than about 50% for effective radius in nadir period.
© Owned by the authors, published by EDP Sciences, 2016
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