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Jaime C. Compton, Ruben Delgado, Timothy A. Berkoff, and Raymond M. Hoff


This article explores the application of the covariance wavelet transform (CWT) to lidar and, for the first time to the authors' knowledge, wind profiler data to examine the possibility of accurate and continuous planetary boundary layer (PBL) height measurements on short temporal resolution (1- and 15-min averages, respectively). Determining the mixing in the PBL was one goal of a study of the spatial and diurnal variations of the PBL height over Maryland for July 2011, during NASA's Earth Venture mission DISCOVER-AQ. The PBL heights derived from ground-based lidars [at University of Maryland, Baltimore County (UMBC); 39.25°N, 76.70°W], a 915-MHz wind profiler, and radiosondes (at Beltsville, Maryland; 38.92°N, 77.02°W) were compared. Results from the comparison show an R 2 = 0.89, 0.92, and 0.94 correlation between the radiosonde PBL heights and two lidars and wind profiler PBL heights, respectively. Accurate determination of the PBL height by applying the CWT to lidar and wind profilers will allow for improved air quality forecasting and understanding of regional pollution dynamics.

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Vanessa Caicedo, Ruben Delgado, Ricardo Sakai, Travis Knepp, David Williams, Kevin Cavender, Barry Lefer, and James Szykman


A unique automated planetary boundary layer (PBL) retrieval algorithm is proposed as a common cross-platform method for use with commercially available ceilometers for implementation under the redesigned U.S. Environmental Protection Agency Photochemical Assessment Monitoring Stations program. This algorithm addresses instrument signal quality and screens for precipitation and cloud layers before the implementation of the retrieval method using the Haar wavelet covariance transform. Layer attribution for the PBL height is supported with the use of continuation and time-tracking parameters, and uncertainties are calculated for individual PBL height retrievals. Commercial ceilometer retrievals are tested against radiosonde PBL height and cloud-base height during morning and late-afternoon transition times, critical to air quality model prediction and when retrieval algorithms struggle to identify PBL heights. A total of 58 radiosonde profiles were used, and retrievals for nocturnal stable layers, residual layers, and mixing layers were assessed. Overall good agreement was found for all comparisons, with one system showing limitations for the cases of nighttime surface stable layers and daytime mixing layer. It is recommended that nighttime shallow stable-layer retrievals be performed with a recommended minimum height or with additional verification. Retrievals of residual-layer heights and mixing-layer comparisons revealed overall good correlations with radiosonde heights (square of correlation coefficients r 2 ranging from 0.89 to 0.96, and bias ranging from approximately −131 to +63 m for the residual layer and r 2 from 0.88 to 0.97 and bias from −119 to +101 m for the mixing layer).

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Amy K. Huff, Shobha Kondragunta, Hai Zhang, Istvan Laszlo, Mi Zhou, Vanessa Caicedo, Ruben Delgado, and Robert Levy


Aerosol optical depth (AOD) retrieved from the GOES-16 Advanced Baseline Imager (ABI) was used to track a smoke plume from a prescribed fire in northeastern Virginia on March 8, 2020. Weather and atmospheric conditions created a favorable environment to transport the plume through the Washington, DC and Baltimore, Maryland metro areas in the afternoon and concentrate smoke near the surface, degrading air quality for several hours. ABI AOD with 5-min temporal resolution and 2-km spatial resolution definitively identified the timing and geographic extent of the plume during daylight hours. Comparison to AERONET AOD indicates that ABI AOD captured the relative change in AOD due to passage of the smoke, with a mean absolute error of 0.047. Ground-based measurements of fine particulate matter (PM2.5) confirm deteriorations in air quality coincident with the progression of the smoke. Ceilometer aerosol backscatter profiles verify plume transport timing and indicate that smoke aerosols were well mixed in a shallow boundary layer. This event illustrates the advantages of using multiple datasets to analyze the impacts of aerosols on ambient air quality. Given the quickly evolving nature of the event over several hours, ABI AOD provided information for the public and decision-makers that was not available from any other source, including polar-orbiting satellite sensors. This study suggests that PM2.5 concentrations estimated from ABI AOD can be used to fill in the gaps in nationwide regulatory PM2.5 monitor networks and may be a valuable addition to EPA’s PM2.5 Nowcast of current air quality conditions.

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