Institution
Langley Research Center
Facility•Hampton, Virginia, United States•
About: Langley Research Center is a facility organization based out in Hampton, Virginia, United States. It is known for research contribution in the topics: Mach number & Wind tunnel. The organization has 15945 authors who have published 37602 publications receiving 821623 citations. The organization is also known as: NASA Langley & NASA Langley Research Center.
Topics: Mach number, Wind tunnel, Aerodynamics, Boundary layer, Supersonic speed
Papers published on a yearly basis
Papers
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TL;DR: In this article, a radiative-convective model study of the increase in global surface temperature due to an increase in the CO2 concentration is presented, which considers several weak bands of CO2 which contribute about 30% to ΔTg.
Abstract: A radiative-convective model study of the increase in global surface temperature ΔTg due to an increase in the CO2 concentration is presented. The model considers several weak bands of CO2 which contribute about 30% to ΔTg. A comparison study of the various published results with the present analysis indicates that, for the CO2 bands in the 12–18 µm region, the best estimate of ΔTg for the constant cloud top radiative-convective model is about 1.9 K for a doubling of the CO2 concentration. The inclusion of the CO2 bands in the 10 and 7.6 µm regions increases the value of ΔTg to about 2 K. The computed value of ΔTg is very sensitive to radiative-convective model assumptions regarding cloud top and relative humidity. Because of this sensitivity the estimated value of ΔTg for a doubling of the CO2 concentration ranges from 1.98 to 3.2 K.
161 citations
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TL;DR: In this article, the authors developed automated routines to derive water vapor mixing ratio, relative humidity, aerosol extinction and backscatter coefficient, and linear depolarization profiles, as well as total precipitable water vapor and aerosol optical thickness from the operational Raman lidar at the Atmospheric Radiation Measurement (ARM) program's site in north-central Oklahoma.
Abstract: Automated routines have been developed to derive water vapor mixing ratio, relative humidity, aerosol extinction and backscatter coefficient, and linear depolarization profiles, as well as total precipitable water vapor and aerosol optical thickness, from the operational Raman lidar at the Atmospheric Radiation Measurement (ARM) program's site in north-central Oklahoma These routines have been devised to maintain the calibration of these data products, which have proven sensitive to the automatic alignment adjustments that are made periodically by the instrument Since this Raman lidar does not scan, aerosol extinction cannot be directly computed below approximately 800 m due to the incomplete overlap of the outgoing laser beam with the detector's field of view Therefore, the extinction-to-backscatter ratio at 1 km is used with the aerosol backscatter coefficient profile to compute aerosol extinction from 60 m to the level of complete overlap Comparisons of aerosol optical depth derived using
161 citations
01 Jan 1992
TL;DR: In this article, it was shown that the original version of the RNG K-epsilon model substantially underpredicts the reattachment point in the backstep problem.
Abstract: A two-equation turbulence model of the K-epsilon type was recently derived by using Renormalization Group (RNG) methods. It was later reported that this RNG based model yields substantially better predictions than the standard K-epsilon model for turbulent flow over a backward facing step - a standard test case used to benchmark the performance of turbulence models in separated flows. The improvements obtained from the RNG K-epsilon model were attributed to the better treatment of near wall turbulence effects. In contrast to these earlier claims, it is shown in this paper that the original version of the RNG K-epsilon model substantially underpredicts the reattachment point in the backstep problem. This is a deficiency that is traced to the modeling of the production of dissipation term. However, with the most recent improvements in the RNG K-epsilon model, excellent results for the backstep problem are now obtained.
160 citations
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TL;DR: The second Texas Air Quality Study (TexAQS II) as discussed by the authors was conducted in eastern Texas during 2005 and 2006, and the results reported in this special journal section are based on observations collected on four aircraft, one research vessel, networks of ground-based air quality and meteorological (surface and radar wind profiler) sites in Eastern Texas, a balloon-borne ozonesonde-radiosonde network, and satellites.
Abstract: [1] The Second Texas Air Quality Study (TexAQS II) was conducted in eastern Texas during 2005 and 2006. This 2-year study included an intensive field campaign, TexAQS 2006/Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS), conducted in August–October 2006. The results reported in this special journal section are based on observations collected on four aircraft, one research vessel, networks of ground-based air quality and meteorological (surface and radar wind profiler) sites in eastern Texas, a balloon-borne ozonesonde-radiosonde network (part of Intercontinental Transport Experiment Ozonesonde Network Study (IONS-06)), and satellites. This overview paper provides operational and logistical information for those platforms and sites, summarizes the principal findings and conclusions that have thus far been drawn from the results, and directs readers to appropriate papers for the full analysis. Two of these findings deserve particular emphasis. First, despite decreases in actual emissions of highly reactive volatile organic compounds (HRVOC) and some improvements in inventory estimates since the TexAQS 2000 study, the current Houston area emission inventories still underestimate HRVOC emissions by approximately 1 order of magnitude. Second, the background ozone in eastern Texas, which represents the minimum ozone concentration that is likely achievable through only local controls, can approach or exceed the current National Ambient Air Quality Standard of 75 ppbv for an 8-h average. These findings have broad implications for air quality control strategies in eastern Texas.
160 citations
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TL;DR: The A-Train satellite constellation as mentioned in this paper is a 10-year demonstration of coordinated formation flying that made it possible to develop integrated products and that offered new insights into key atmospheric processes.
Abstract: One of the most successful demonstrations of an integrated approach to observe Earth from multiple perspectives is the A-Train satellite constellation. The science enabled by this constellation flourished with the introduction of the two active sensors carried by the National Aeronautics and Space Administration (NASA) CloudSat and the NASA–Centre National d’Etudes Spatiales (CNES) Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites that were launched together on 28 April 2006. These two missions have provided a 10-yr demonstration of coordinated formation flying that made it possible to develop integrated products and that offered new insights into key atmospheric processes. The progress achieved over this decade of observations, summarized in this paper, clearly demonstrate the fundamental importance of the vertical structure of clouds and aerosol for understanding the influences of the larger-scale atmospheric circulation on aerosol, the hydrological cycle, t...
160 citations
Authors
Showing all 16015 results
Name | H-index | Papers | Citations |
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Daniel J. Jacob | 162 | 656 | 76530 |
Donald R. Blake | 118 | 727 | 49697 |
Veerabhadran Ramanathan | 100 | 301 | 47561 |
Raja Parasuraman | 91 | 402 | 41455 |
Robert W. Platt | 88 | 638 | 31918 |
James M. Russell | 87 | 691 | 29383 |
Daniel J. Inman | 83 | 918 | 37920 |
Antony Jameson | 79 | 474 | 31518 |
Ya-Ping Sun | 79 | 277 | 28722 |
Patrick M. Crill | 79 | 228 | 20850 |
Richard B. Miles | 78 | 759 | 25239 |
Patrick Minnis | 77 | 490 | 23403 |
Robert W. Talbot | 77 | 297 | 19783 |
Raphael T. Haftka | 76 | 773 | 28111 |
Jack E. Dibb | 75 | 344 | 18399 |