A Look at Amazon Basin Seasonal Dynamics with the Biophysical ...

MICROPHYSICAL CHARACTERISTICS OF A SQUALL LINE IN THEAMAZON REGIONMarcel Ricardo Rocco and Augusto José Pereira FilhoUniversidade de São Paulo, São Paulo – USP / IAG / DCARua do Matão, 1226, São Paulo, SP, Brazil, 05508-900e-mail: marcelri@model.iag.usp.brABSTRACTA hydrometeor classification is performed for a squall line that passed through the WETAMC and TRMM LBA experiment area in 26 January 1999. Polarimetric measurementsfrom a S-band dual Doppler weather radar were used in conjunction with a classificationprocedure developed by Straka et al. (2000). This method is based on extensiveobservational and modeling studies of polarimetric hydrometeors signatures. Hydrometeortypes are classified according to arbitrary boundaries or thresholds in a multidimensionalpolarimetric space. The hydrometeors are divided in the following groups: rain, hail, rainwethail mixtures, small graupel, snow crystals and aggregate. Preliminary results areconsistent with expected vertical microphysical structures; warm and could types belowand above the bright band, respectively. In the end, this classification showed to be veryrestrictive. A fuzzy classification algorithm that builds upon this foundation will bediscussed in a forthcoming paper, because the fuzzy logic-based method makes use of asmooth transition in polarimetric observable boundaries among precipitation types insteadof simple thresholds. Finally, this study will support a different number of scientific andoperational studies that needs a better understanding to deduce hydrometeor types frompolarimetric data. These include: determination of Z-R relations, evaluation of interactionsbetween microphysics and kinematics in severe storms and mesoscale systems, estimationof latent heating budgets, initialization of hydrometeor types and amounts in storm-scaleand mesoscale numerical models, determination of detrainment rates in hybrid cumulusparameterization schemes, improvement and verification of microphysical parameterizationin cloud and mesoscale models, and verification of quantitative precipitation models,among others.