Shweta Haran
M.S. FinalAug 09, 2022, 3:30 pm - 5:30 pm
Teams
ADVANCED PROCESSING OF DUAL POLARIZATION WEATHER RADAR SIGNALS
Abstract: This research focuses on the processing of radar data in the spectral domain and analysis of micro-physical properties of hail and rain in severe convective and stratiform storms. This research also discusses the optimization of a parametric time domain method to separate cloud and drizzle data.
The microphysical and kinematic properties of hydrometeors present in a precipitation event can be studied using spectral domain processing and analysis of the radar moments. This study along with polarimetric information is called spectral polarimetry. For this study, the observations made by CSU-CHIVO (Colorado State University - C-band Hydrometeorological Instrument for Volumetric Observation) radar during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations) campaign is utilized. Features such as the slope in differential reflectivity, spectrum width, and spectral copolar correlation are studied which gives a better understanding of the storm microphysics. In this thesis, microphysical properties of different types of hydrometeors such as hail, rain, and large drops are studied using convective and stratiform storm observations.
A parametric time-domain method (PTDM) is utilized for the separation of cloud and drizzle data. To reduce the time latency present in processing the data, the processing code is optimized by deploying on a high-performance computer (HPC). The processing code is tested on an HPC and automated to handle errors in processing. The run time is reduced by approximately 50%, hence increasing the data processing efficiency. This study shows that optimization of the run time using an HPC is an efficient method. Data processing using an HPC can be used to deploy similar time-consuming algorithms, hence increasing the efficiency and performance.
The microphysical and kinematic properties of hydrometeors present in a precipitation event can be studied using spectral domain processing and analysis of the radar moments. This study along with polarimetric information is called spectral polarimetry. For this study, the observations made by CSU-CHIVO (Colorado State University - C-band Hydrometeorological Instrument for Volumetric Observation) radar during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations) campaign is utilized. Features such as the slope in differential reflectivity, spectrum width, and spectral copolar correlation are studied which gives a better understanding of the storm microphysics. In this thesis, microphysical properties of different types of hydrometeors such as hail, rain, and large drops are studied using convective and stratiform storm observations.
A parametric time-domain method (PTDM) is utilized for the separation of cloud and drizzle data. To reduce the time latency present in processing the data, the processing code is optimized by deploying on a high-performance computer (HPC). The processing code is tested on an HPC and automated to handle errors in processing. The run time is reduced by approximately 50%, hence increasing the data processing efficiency. This study shows that optimization of the run time using an HPC is an efficient method. Data processing using an HPC can be used to deploy similar time-consuming algorithms, hence increasing the efficiency and performance.
Adviser: Dr. V. Chandrasekar
Co-Adviser: N/A
Non-ECE Member: Dr. Thomas Siller, Civil Engineering
Member 3: Dr. Haonan Chen, Electrical and Computer Engineering
Addional Members: N/A
Co-Adviser: N/A
Non-ECE Member: Dr. Thomas Siller, Civil Engineering
Member 3: Dr. Haonan Chen, Electrical and Computer Engineering
Addional Members: N/A
Publications:
N/A
N/A
Program of Study:
ECE512
ECE514
ECE516
ECE513
CS445
ECE581C1
ECE569
ECE699
ECE512
ECE514
ECE516
ECE513
CS445
ECE581C1
ECE569
ECE699