Improving Retrievals of Cirrus Cloud Particle Size Coupling Lidar and Three-Channel Radiometric Techniques

Chiriaco, M.; Chepfer, H.; Noel, V.; Delaval, A.; Haeffelin, M.; Dubuisson, P.; Yang, P.
July 2004
Monthly Weather Review;Jul2004, Vol. 132 Issue 7, p1684
Academic Journal
This study is intended to illustrate the potential advantage of combining lidar measurements and the split-window technique based on the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands for inferring the microphysical properties of cirrus clouds. The lidar returns are employed to detect cirrus clouds. The optical properties of nonspherical ice crystals computed from the state-of-the-art scattering computational methods are used for the present forward radiative transfer simulation that fully accounts for both gaseous absorption and multiple scattering processes in the atmosphere. A combination of the radiances at the three infrared (IR) bands with lidar backscatter returns cannot uniquely specify the effective size of ice crystals because of its dependence on the particle aspect ratios. To avoid the shortcoming associated with a potential multivalued retrieval, lidar depolarization observation is used to constrain the specification of the particle aspect ratio in the retrieval implementation based on a precalculated lookup library. The present methodology for inferring the microphysical properties of cirrus clouds is implemented for nine cases by using the measurements from a 532-nm lidar located at the Palaiseau, France, ground-based site and the infrared spectral bands from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra platform. It is shown that the three IR wavelengths are quite complementary in constraining the retrieval of the particle size, leading to a significant advance in comparison with two-channel techniques, whereas the aspect ratio constraint due to lidar depolarization reduces the uncertainty of retrieved particle size by more than 20% for 70% of the cases and more than 65% for 40% of the cloud cases.


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