MS Thesis Defense: Joshua Finch

ADVISOR: Dr. Belay Demoz

TITLE: Characterizing aerosol, cloud, and dust vertical structure using ceilometer lidar: Implications for Boundary layer dynamics and air quality

ABSTRACT: Ceilometers are widely deployed for cloud-base detection but also provide continuous, vertically resolved observations of aerosols and atmospheric structure that have broader applications in air-quality monitoring and hazardous weather analysis. NOAA has been using ceilometers for decades for cloud ceiling studies but in a limited sense. This study investigates the capability of ceilometer-derived backscatter to characterize aerosol loading, assess cloud-base detection performance, and examine dust storm evolution within the atmospheric boundary layer. Aerosol analyses were conducted using a Lufft CHM15k ceilometer, PurpleAir PM₂.₅ observations, and surface meteorological data collected in Baltimore, Maryland. Statistical comparisons were performed to evaluate the relationship between attenuated backscatter and surface PM₂.₅ under clear, non-precipitation days . Results demonstrate a positive relationship between ceilometer backscatter and PM₂.₅, with the strongest correlations generally occurring within the lower boundary layer and varying with season and relative humidity. Cloud-base observations from the ceilometer were also compared with NOAA's Automated Surface Observing System (ASOS) reports to evaluate potential operational detection gaps, showing that the ceilometer frequently detected elevated cloud layers not reported by ASOS. In addition, case studies using observations from Phoenix, Arizona, demonstrate the ability of ceilometers to continuously monitor the vertical structure and evolution of dust storms, capturing dust lofting, transport, and boundary-layer mixing associated with convective outflow. Collectively, these results demonstrate that ceilometers provide valuable information beyond routine cloud-base measurements and can complement existing surface observing networks by improving characterization of aerosol distributions, cloud occurrence, and hazardous weather processes.

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