[Eoas-seminar] REMINDER: Meteorology MS Defense for Jiangmei Li, Tuesday, March 5, 2019, 3:30 PM, LOV353
eoas-seminar at lists.fsu.edu
eoas-seminar at lists.fsu.edu
Tue Mar 5 08:25:30 EST 2019
M.S. Meteorology Candidate
Title: Classification of rain clouds based on the relationship between microwave emission and scattering signals
Major Professor: Guosheng Liu
Date: March 5, 2019 Time: 3:30 - 5:00 PM
Location: Werner A. Baum Seminar Room (353 Love Building)
(Please join us for refreshments served outside room 353 Love @ 3:00 PM)
In this thesis, we introduce a new approach to classify rain clouds based on the relationship between the emission signal and scattering signal derived from microwave brightness temperature data. Two parameters are used as indicators of emission signal and scattering signal respectively: one is the polarization difference (D) at 19 GHz, and the other one is the polarization-corrected temperature (PCT) at high-frequencies channels. D is related to the emission of liquid hydrometeors, and PCT mainly reflects the brightness temperature depression due to the scattering by ice particles. Both D and PCT decrease with increasing precipitation rate. Therefore, certain combinations of D and PCT can be regarded as the representatives of cloud hydrometeor structures. Based on the D-PCT relationship investigated in this study, we classified the observed rain clouds into five categories-non-precipitating, light-precipitating, liquid-dominant precipitating, well-mix precipitating, and ice-dominant precipitating cloud.
We verified the results of the classification of different precipitation cases over tropical regions. For both the hurricane and front cases, the results show that the distributions of categorized cloud pixels can reflect the horizontal structure of the weather systems. The monthly gridded mean frequencies of categorized precipitating clouds are used to analyze the relationship between the seasonal and interannual cycles of tropical precipitation and clouds' hydrometeor components. Moreover, the results indicated that in an annual cycle or an ENSO cycle, when the local precipitation frequencies increase, the occurrence frequencies of all kinds of rain clouds will increase. However, among those precipitating systems, the proportions of ice-dominant and well-mixed clouds increases while that of water-dominant clouds decrease as the local precipitation increases. Anomalies of the opposite sign tend to accompany the decreasing precipitations situations. Overall, the classification method proves to be useful to extract objective information from observed emission and scattering signals.
Florida State University
Academic Program Specialist
Department of Earth, Ocean, & Atmospheric Science
1017 Academic Way, 410 Love Building (Meteorology)
Tallahassee, FL 32306
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