Characterization of Hydrometeors in Sahelian Convective Systems with an X-Band Radar and Comparison with In Situ Measurements. Part I Sensitivity of Polarimetric Radar Particle Identification Retrieval and Case Study Evaluation

• Published in: Journal of applied meteorology and climatology Vol. 55; no. 2; pp. 231 - 249
• Main Authors: Cazenave, F., Gosset, M., Kacou, M., Alcoba, M., Fontaine, E., Duroure, C., Dolan, B.
• Format: Journal Article
• Language: English
• Published: Boston American Meteorological Society 01.02.2016
• Subjects: Aggregation; Air traffic control; Aircraft; Algorithms; Case studies; Clouds; Convection; Convective systems; Data acquisition; Datasets; Hydrometeor types; Hydrometeors; Identification; In situ measurement; Meteorology; Polarimetric radar; Polarimetry; Precipitation; Radar; Rain; Sampling; Squalls; Superhigh frequencies; Tornadoes; X-band; Niger; Africa
• ISSN: 1558-8424; 1558-8432
• DOI: 10.1175/JAMC-D-15-0013.1

The particle identification scheme developed by Dolan and Rutledge for X-band polarimetric radar is tested for the first time in Africa and compared with in situ measurements. The data were acquired during the Megha-Tropiques mission algorithm-validation campaign that occurred in Niger in 2010. The radar classification is compared with the in situ observations gathered by an instrumented aircraft for the 13 August 2010 squall-line case. An original approach has been developed for the radar–in situ comparison: it consists of simulating synthetic radar variables from the microphysical-probe information and comparing the two datasets in a common "radar space." The consistency between the two types of observation is good considering the differences in sampling illustrated in the paper. The time evolution of the hydrometeor types and their relative proportion in the convective and stratiform regions are analyzed. The farther away from the convection one looks, the more aggregation dominates, riming diminishes, and hydrometeors are less dense. Particle identification based on the polarimetric radar will be applied to a 5-yr African dataset in the future.