Institution
University of Maryland, Baltimore County
Education•Baltimore, 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 & Aerosol. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.
Papers published on a yearly basis
Papers
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TL;DR: This article found that comments about the content of the storybook were the most common type of utterance during reading interactions and the affective quality of the reading interaction was the most powerful predictor of children's motivations for reading.
310 citations
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TL;DR: The thought processes, advances in synthetic chemistry and lessons learned from antiviral testing that led to a few molecules being moved forward to eventual approval for human therapies, while others were discarded.
310 citations
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TL;DR: In this paper, a cloud masking algorithm based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths was developed for the retrieval of aerosol properties by MODIS.
Abstract: ] A cloud masking algorithm based on the spatial variability ofreflectances at the top of the atmosphere in visible wavelengths wasdeveloped for the retrieval of aerosol properties by MODIS. It isshown that the spatial pattern of cloud reflectance as observed fromspace, is very different from that of aerosols. Clouds show a veryhigh spatial variability in the scale of hundred meters to fewkilometers, whereas aerosols in general are very homogeneous. Theconcept of spatial variability of reflectances at the top of theatmosphere is mainly applicable over the ocean where the surfacebackground is sufficiently homogeneous for the separation betweenaerosols and clouds. Aerosol retrievals require a particular cloudmasking approach since a conservative mask will screen out strongaerosol episodes and a less conservative mask could allow forcloud contamination that tremendously affect the retrieved aerosoloptical properties (e.g. aerosol optical depth and effective radii). Adetailed study on the effect of cloud contamination on aerosolretrievals is performed and parameters are established determiningthe threshold value for the MODIS aerosol cloud mask (3X3-STD)over the ocean. The 3X3-STD algorithm discussed in this paper isthe operational cloud mask used for MODIS aerosol retrievals overthe ocean. I
309 citations
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Goddard Space Flight Center1, Science Applications International Corporation2, University of Maryland, Baltimore County3, Hokkaido University4, European Centre for Medium-Range Weather Forecasts5, University of Guelph6, Florida State University7, Catalan Institution for Research and Advanced Studies8, National Oceanic and Atmospheric Administration9, University of Gothenburg10, Environment Canada11, Princeton University12, Michigan State University13, ETH Zurich14, Royal Netherlands Meteorological Institute15
TL;DR: The second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture as mentioned in this paper.
Abstract: The second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forec...
309 citations
Authors
Showing all 8862 results
Name | H-index | Papers | Citations |
---|---|---|---|
Robert C. Gallo | 145 | 825 | 68212 |
Paul T. Costa | 133 | 406 | 88454 |
Igor V. Moskalenko | 132 | 542 | 58182 |
James Chiang | 129 | 308 | 60268 |
Alex K.-Y. Jen | 128 | 921 | 61811 |
Alan R. Shuldiner | 120 | 557 | 71737 |
Richard N. Zare | 120 | 1201 | 67880 |
Vince D. Calhoun | 117 | 1234 | 62205 |
Rita R. Colwell | 115 | 781 | 55229 |
Kendall N. Houk | 112 | 997 | 54877 |
Elliot K. Fishman | 112 | 1335 | 49298 |
Yoram J. Kaufman | 111 | 263 | 59238 |
Paulo Artaxo | 107 | 454 | 44346 |
Braxton D. Mitchell | 102 | 558 | 49599 |
Sushil Jajodia | 101 | 664 | 35556 |