Recorded presentation10.6
Simulating the measurement with 3D Monte Carlo radiative transfer
Tobias Zinner, Ludwig-Maximilians-Universitaet, Munich, Germany; and C. Emde, R. Buras, L. Bugliaro, F. Faure, and B. Mayer
Exact 3D Monte Carlo radiative transfer methods based on realistic cloud data offer an interesting test bed for the development of new retrieval methods as well as the validation of existing or prospective algorithms. Ralistic - with respect to microphysical and optical properties as well as spatial distribution - cloud data sets form the basis for full 3D forward radiative transfer solutions for a given sensor measurement characteristic. Applying a retrieval to such a simulated data set provides the possibility to compare the retrieved information with the one given in the first place. The 3D Monte Carlo radiative transfer code libRadtran/MYSTIC was recently extended to provide such simulations for different passive and active remote sensing instruments. Polarized radiative transfer as well as a lidar simulation mode were added. Based on cloud data sets from cloud and weather models examples will be shown for sensor setups ranging from future space-borne lidar sensors (EarthCARE, HSRL), over existing air-borne polarisation sensors in preparation of future satellite systems (Glory, APS), to new validation studies for presumably well known satellites like Meteosat/SEVIRI or MODIS.
Session 10, Remote Sensing II: Active and Multi-Instrument/Platform
Thursday, 1 July 2010, 10:30 AM-12:00 PM, Pacific Northwest Ballroom
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