Remote Sensing Cloud Properties from High Spectral Resolution Infrared Observations

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Abstract
A technique for estimating cloud radiative properties (i.e., spectral emissivity and reflectivity) in the infrared is developed based on observations at a spectral resolution of approximately 0.5 cm−1. The algorithm makes use of spectral radiance observations and theoretical calculations of the infrared spectra for clear and cloudy conditions along with lidar-determined cloud-base and cloud-top pressure. An advantage of the high spectral resolution observations is that the absorption effects of atmospheric gases are minimized by analyzing between gaseous absorption lines. The technique is applicable to both ground-based and aircraft-based platforms and derives the effective particle size and associated cloud water content required to satisfy, theoretically, the observed cloud infrared spectra. The algorithm is tested using theoretical simulations and applied to observations made with the University of Wisconsin's ground-based and NASA ER-2 aircraft High-Resolution Infrared Spectrometer instruments.

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