Extending Micro-Pulse DIAL (MPD) Water Vapor Estimation Capability for Increased and Enhanced Weather Applications by Leveraging Advanced Signal Processing Techniques

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

The accurate measurement of water vapor in the lower atmosphere is one of the keys to unlocking improved forecasts of cloud, precipitation, and severe weather. Through NSF funding, researchers have developed a network of lidars that can run unattended and provide research-quality water vapor measurements. This project will enhance the capability of those lidars to provide measurements in space and time by using advanced signal processing techniques that are already in use in the medical imaging community. Beyond the potential to improve forecasting, the project could allow for a change in how future instruments are constructed, lowering the cost and allowing for more coverage. This also represents the first NSF award for an early-career scientist. The research plan is to apply a new signal processing technique to the micro-pulse differential absorption lidar (MPD) network to increase the capability of the instrument to retrieve water vapor measurements. The Poisson Total Variation (PTV) technique is used as a signal processor framework for lidar applications and can be conceptualized as an approach where the spatial and temporal resolutions of the observations are systematically and optimally adjusted based on the signal-to-noise ratio. The PTV is based on well-established signal processing techniques that have been used in medical imaging. The short-term objective of the project is to further validate the preliminary PTV techniques and improve it where necessary by processing several MPD datasets that have coincident radiosonde water vapor retrievals. The long-term objective is to refine the technique to be more computationally efficient and integrate it to the MPD testbed data processing system. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.