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Proceedings Paper

Cloud image retrieval and characterization using ground-based dual-wavelength radar at millimeter wavelengths
Author(s): Nivia Colon-Diaz; Sandra L. Cruz-Pol; Stephen M. Sekelsky
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Paper Abstract

Characterization of the microphysical properties of non-precipitating stratus clouds including their suspended-water droplet size distribution and the cloud's liquid water content are estimated in this work. The dual wavelength ratio, DWR, and the differential extinction, DE, were computed at two millimeter frequencies, 33 GHz and 95 GHz, using UMass Cloud Profiling Radar System (CPRS) to estimate the drop size distribution. Data from radiosonde observations (Raob) is used as input in a recently calibrated model for estimation of the gaseous attenuation at Ka.-band and Liebe's model at W-band. Integrated specific humidity from a radiometer is used to constrain the radiosonde specific humidity. The radar reflectivity is corrected to take into account the effect of the wind speed, the difference of beamwidth at both frequencies and the difference in sampled range cells. Radar reflectivity and ancillary data are combined to obtain the differential extinction and the estimated cloud's liquid water density. Profiles of the processed data, such as DE, the DWR and the cloud's liquid water density are presented. Cloud's water density and radar reflectivity were used for the size distribution estimation of the suspended water droplets and the median drop diameter.

Paper Details

Date Published: 18 April 2003
PDF: 10 pages
Proc. SPIE 4882, Remote Sensing of Clouds and the Atmosphere VII, (18 April 2003); doi: 10.1117/12.463031
Show Author Affiliations
Nivia Colon-Diaz, Univ. de Puerto Rico/Mayaguez (United States)
Sandra L. Cruz-Pol, Univ. of Puerto Rico/Mayaguez (United States)
Stephen M. Sekelsky, Univ. of Massachusetts/Amherst (United States)


Published in SPIE Proceedings Vol. 4882:
Remote Sensing of Clouds and the Atmosphere VII
Klaus P. Schaefer; Olga Lado-Bordowsky; Adolfo Comeron; Richard H. Picard, Editor(s)

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