Cirrus cloud properties derived from satellite radiances during FIRE
Patrick Minnis, Patrick W. Heck, David F. Young, Kuo‐Nan Liou, Y. Takano
Abstract
Patrick Minnis, Patrick W. Heck, David F. Young, Kuo‐Nan Liou, Y. Takano
Abstract
The sensitivity of the retrieved cloud properties to the cloud radiative transfer model is explored using satellite data taken during the First ISCCP Regional Experiment (FIRE). Several different scattering phase functions are used to create a set of models which relate cloud optical depth to bidirectional reflectance. These models are employed in the analysis of data taken nearly simultaneously from two different satellites over regions containing cirrus clouds. The interpretation of the reflectances using the various models is evaluated through intercomparisons of the results from both satellites and through comparisons with lidar data. The preliminary results indicate that, compared to water-droplet scattering models, ice-crystal scattering models provide a more precise and physically consistent interpretation of visible and infrared radiances for determining cirrus cloud properties.
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The sensitivity of the retrieved cloud properties to the cloud radiative transfer model is explored using satellite data taken during the First ISCCP Regional Experiment (FIRE). Several different scattering phase functions are used to create a set of models which relate cloud optical depth to bidirectional reflectance. These models are employed in the analysis of data taken nearly simultaneously from two different satellites over regions containing cirrus clouds. The interpretation of the reflectances using the various models is evaluated through intercomparisons of the results from both satellites and through comparisons with lidar data. The preliminary results indicate that, compared to water-droplet scattering models, ice-crystal scattering models provide a more precise and physically consistent interpretation of visible and infrared radiances for determining cirrus cloud properties.
Key concepts: Cirrus, Remote sensing, Radiative transfer, Satellite, Lidar, Cloud computing, Environmental science, International Satellite Cloud Climatology Project