Translator Disclaimer
31 January 2001 Accuracy of low-spatial-resolution cloud property retrieval considering horizontal cloud inhomogeneities
Author Affiliations +
In low spatial resolution remote sensing the plane parallel albedo bias caused by sub-pixel cloud inhomogeneities leads to underestimation of cloud properties. RF Cahalan et al. Have suggested the effective thickness approximation as a method of correcting this bias, assuming a single parameter fractal cloud model.. The magnitude of the reduction factor applied to the optical depth in this method is dependent on the cloud fractal parameter, determined from spatial liquid water distribution. We present here a study using in situ aircraft liquid water measurements in northern Tasmania, Australia, to first locally determine the cloud fractal parameter in local conditions, and then to test the satellite retrieval of cloud properties using these results. Four categories of cloud with different fractal parameters are identified and the retrieval method showed encouraging results, with further testing and refinement required.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kurt S. Fienberg and Manuel Nunez "Accuracy of low-spatial-resolution cloud property retrieval considering horizontal cloud inhomogeneities", Proc. SPIE 4168, Remote Sensing of Clouds and the Atmosphere V, (31 January 2001);

Back to Top