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Institution

University of Maryland, Baltimore County

EducationBaltimore, Maryland, United States
About: University of Maryland, Baltimore County is a education organization based out in Baltimore, Maryland, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.


Papers
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Journal ArticleDOI
TL;DR: The current understanding of the microbial diversity and physiology of RAS biofilters is summarized and directions for future studies are discussed.

209 citations

Journal ArticleDOI
TL;DR: In this paper, an analysis of satellite data suggests that increases in aerosol abundance are associated with local intensification of rain rates over land and ocean, and thus the radiative balance of the planet and the water cycle.
Abstract: Atmospheric aerosols affect cloud properties, and thereby the radiative balance of the planet and the water cycle. An analysis of satellite data suggests that increases in aerosol abundance are associated with local intensification of rain rates over land and ocean.

209 citations

Journal ArticleDOI
TL;DR: The result suggests both empathic accuracy and response type have significant influence on online interpersonal trust, which implies a relationship between daily trust attitude and online interpersonaltrust.
Abstract: The rapid growth of personal email communication, instant messaging and online communities has brought attention to the important role of interpersonal trust in online communication. An empirical study was conducted focusing on the effect of empathy on online interpersonal trust in textual IM. To be more specific, the relationship between empathic accuracy, response type and online interpersonal trust was investigated. The result suggests both empathic accuracy and response type have significant influence on online interpersonal trust. The interaction between empathic accuracy and response type also significantly influences online trust. Interestingly, the results imply a relationship between daily trust attitude and online interpersonal trust. People who are more trusting in their daily life may experience more difficulty in developing trust online. There is also some evidence to suggest that different communication scenarios may have an influence on online trust.

209 citations

Journal ArticleDOI
TL;DR: It is shown that, although sun glint contamination has a minor effect on retrieving ocean color products, the effect on retrieved atmospheric products, e.g., aerosol optical thickness, is significant and the derived ocean and atmospheric products are improved.
Abstract: For remote sensing of the ocean and atmosphere optical properties, the measurement of radiances affected by sun glint has to be avoided and/or masked out. There are usually no meaningful retrievals in regions significantly contaminated by sun glint. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is capable of operationally tilting the sensor 20 degrees away from nadir to minimize sun glint contamination. The sun glint mask is computed from the Cox and Munk model [J. Opt. Soc. Am. 44, 838-850 (1954)] and applied to the SeaWiFS data. However, sun glint is still a factor near the subsolar point. We present results that demonstrate the effect of sun glint contamination on retrievals of ocean bio-optical and atmospheric products. We show that, although sun glint contamination has a minor effect on retrieved ocean color products, the effect on retrieved atmospheric products, e.g., aerosol optical thickness, is significant. We describe a sun glint correction scheme implemented in the SeaWiFS data-processing system and compare the results with and without sun glint correction. With sun glint correction the derived ocean and atmospheric products are improved. Also, the sun glint masked area can be reduced and therefore can increase significantly the coverage area near the subsolar point.

209 citations

Journal ArticleDOI
TL;DR: In this paper, the radiative effects of cloud 3-dimensional structure in retrievals of droplet effective radii were investigated and it was found that ignoring subpixel (unresolved) variability produces a negative bias in the retrieved effective radius, while ignoring cloud inhomogeneity at scales larger than a pixel scale leads to overestimation of the domain average droplet size.
Abstract: [1] There are several dozen papers that study the effects of cloud horizontal inhomogeneity on the retrievals of cloud optical thickness, but only a few of them deal with cloud droplet sizes. This paper is one of the first comprehensive attempts to fill this gap: It takes a close theoretical look at the radiative effects of cloud 3-D structure in retrievals of droplet effective radii. Under some general assumptions, it was found that ignoring subpixel (unresolved) variability produces a negative bias in the retrieved effective radius, while ignoring cloud inhomogeneity at scales larger than a pixel scale (resolved variability), on the contrary, leads to overestimation of the domain average droplet size. The theoretical results are illustrated with examples from Large Eddy Simulations (LES) of cumulus (Cu) and stratocumulus (Sc) cloud fields. The analysis of cloud drop size distributions retrieved from both LES fields confirms that ignoring shadowing in 1-D retrievals results in substantial overestimation of effective radii which is more pronounced for broken Cu than for Sc clouds. Collocated measurements of broken Cu clouds by Moderate Resolution Imaging Spectrometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are used to check simulations and theory with observations. The analysis of ASTER and MODIS data and associated derived products recommends against blindly using retrieved effective radii for broken cloud fields, especially if one wants to relate aerosol amounts to cloud droplet sizes.

209 citations


Authors

Showing all 8862 results

NameH-indexPapersCitations
Robert C. Gallo14582568212
Paul T. Costa13340688454
Igor V. Moskalenko13254258182
James Chiang12930860268
Alex K.-Y. Jen12892161811
Alan R. Shuldiner12055771737
Richard N. Zare120120167880
Vince D. Calhoun117123462205
Rita R. Colwell11578155229
Kendall N. Houk11299754877
Elliot K. Fishman112133549298
Yoram J. Kaufman11126359238
Paulo Artaxo10745444346
Braxton D. Mitchell10255849599
Sushil Jajodia10166435556
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202371
2022165
20211,065
20201,091
2019989
2018929