Multi-sensor Cloud and Aerosol Retrieval Simulator and Its Applications

Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.

Reclaiming the Vocal High Ground: Performing Baroque Repertoire in a Modern World

The early music revival of the late twentieth century revolutionized music with the birth of historically lnformed performance. With this revolution came a stereotype of the "early music singing voice" as small, bright, straight-toned, and unfortunately, often inferior techrucally to the mainstream opera singer. An assessment of the validity of this stereotype was made though readings of treatises and modern manuals of performance practice, and through listening to recordings. Sources on ornamentation, recitative, dance rhythm, and baroque gesture were examined, resulting in the finding that these issues are far more important to historical accuracy than are voice timbre and size. This dissertation is comprised of three historically informed performances intended to satisfy both the early music specialist and the mainstream voice teacher. Program One (May 15, 2004) is a performance of The "Peasant" Cantata, BWV 212, by J.S. Bach, with The Bach Sinfonia at the Washington Conservatory of Music. Program Two (January 29, 2005) is the role of Eurilla in a staged production of Antonio Vivaldi's serenata, Eurilla e Alcindo. The performance is a collaboration with the Baltimore-based ensemble, La Rocinante, and is conducted from the keyboard by Joseph Gascho. Program Three (March 14, 2005) is a solo recital entitled, Fairest Isle: Music of Baroque London. All three programs are documented in a digital audio format available on compact disc, with accompanying programs and notes also available in digital format.

Prevalence of MRSA and Antimicrobial Resistance of Staphylococcus aureus in Maryland Ground Meat Products

Gemstone Team Antibiotic Resistance