IPRT polarized radiative transfer model intercomparison project – Phase A. (October 2015) - Emde, Claudia; Barlakas, Vasileios; Cornet, Céline; Evans, Frank; Korkin, Sergey; Ota, Yoshifumi; Labonnote, Laurent C.; Lyapustin, Alexei; Macke, Andreas; Mayer, Bernhard; Wendisch, Manfred
Abstract: The polarization state of electromagnetic radiation scattered by atmospheric particles such as aerosols, cloud droplets, or ice crystals contains much more information about the optical and microphysical properties than the total intensity alone. For this reason an increasing number of polarimetric observations are performed from space, from the ground and from aircraft. Polarized radiative transfer models are required to interpret and analyse these measurements and to develop retrieval algorithms exploiting polarimetric observations. In the last years a large number of new codes have been developed, mostly for specific applications. Benchmark results are available for specific cases, but not for more sophisticated scenarios including polarized surface reflection and multi-layer atmospheres. The International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to fill this gap. This paper presents the results of the first phase A of the IPRT project which includes ten test cases, from simple setups with only one layer and Rayleigh scattering to rather sophisticated setups with a cloud embedded in a standard atmosphere above an ocean surface. All scenarios in the first phase A of the intercomparison project are for a one-dimensional plane–parallel model geometry. The commonly established benchmark results are available at the IPRT website (http://www.meteo.physik.uni-muenchen.de/iprt ). Abstract : Highlights: Intercomparison of polarized radiative transfer codes. Simple and complex cases with multiple scattering in clouds and surface reflection. Comparison of various methodologies (Monte Carlo, Discrete Ordinate, etc.) Large benchmark dataset for model developers.