Weather radar signal processing techniques

The goal of signal processing is to extract the maximum amount of information from a signal. In the context of weather radars, this includes all the manipulations needed to transform the received weather signals (a.k.a. time-series data) into clean measurements of water content, wind velocity, and other meteorological variables.

Weather radar signal processing focuses on three main problems:

removal of artifacts (i.e., cleaning the weather signals from contaminating returns such as returns from the ground),
resolving measurement ambiguities (e.g., finding the correct location and magnitude of winds), and
improving the accuracy and precision of meteorological variables (i.e., providing the best estimate from the measured signals).

For more information about the weather radar signal processing projects that I'm currently working on, click on any of the following links:

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ARRC team receives second NSF award to investigate tonado debris

We recently received a second award from the National Science Foundation (NSF) for our research project "Understanding the Relationship Between Tornadoes and Debris Through Observed and Simulated Radar Data."

NEXRAD class at the Osher Lifelong Learning Institute

This fall, I had the honor and privilege to teach an OLLI class with my friend and colleague Jami Boettcher. "NEXRAD Weather Radar: How it Works and What Those Images Tell Us" kept us busy for 5 weeks this fall.

Paper makes the cover of IEEE journal

Our paper "Bootstrap Dual-Polarimetric Spectral Density Estimator" made the cover of the April 2017 issue of the IEEE Transactions on Geoscience and Remote Sensing journal.

JTECH Associate Editor

I have accepted to serve as an associate editor for the American Meteorological Society’s Journal of Atmospheric and Oceanic Technology.

Outstanding Service Award

I have been chosen as the winner of the 2016 OU College of Atmospheric and Geographic Sciences Dean’s Award for Outstanding Service.