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In this work we analyze chronological data for lunar meteorites with emphasis on the spatial and temporal distribution of lunar mare basalts. The data are mostly from the Lunar Meteorite Compendium (http://www-curator.jsc.nasa.gov/antmet/lmc/contents.cfm cited thereafter as Compendium) compiled by Kevin Righter and from the associated literature.
A Differential Mobility Analyzer/Tandem Differential Mobility Analyzer (DMA/TDMA) was used to measure submicron aerosol size distributions, hygroscopicity, and occasionally volatility during the May 2003 Aerosol Intensive Operational Period (IOP) at the Central Facility of the Atmospheric Radiation Measurement Program's Southern Great Plains (ARM SGP) site. Hygroscopic growth factor distributions for particles at eight dry diameters ranging from 0.012 micrometers to 0.600 micrometers were measured throughout the study. For a subset of particle sizes, more detailed measurements were occasionally made in which the relative humidity or temperature to which the aerosol was exposed was varied over a wide range. These measurements, in conjunction with backtrajectory clustering, were used to infer aerosol composition and to gain insight into the processes responsible for evolution. The hygroscopic growth of both the smallest and largest particles analyzed was typically less than that of particles with dry diameters of about 0.100 micrometers. It is speculated that condensation of secondary organic aerosol on nucleation mode particles is largely responsible for the minimal hygroscopic growth observed at the smallest sizes considered. Growth factor distributions of the largest particles characterized typically contained a nonhygroscopic mode believed to be composed primarily of dust. A model was developed to characterize the hygroscopic properties of particles within a size distribution mode through analysis of the fixed size hygroscopic growth measurements. The performance of this model was quantified through comparison of the measured fixed size hygroscopic growth factor distributions with those simulated through convolution of the size-resolved concentration contributed by each of the size modes and the mode-resolved hygroscopicity. This transformation from sizeresolved hygroscopicity to mode-resolved hygroscopicity facilitated examination of changes in the hygroscopic properties of particles within a size distribution mode that accompanied changes in the sizes of those particles. This model was used to examine three specific cases in which the sampled aerosol evolved slowly over a period of hours or days.
Global distributions of albedo susceptibility for areas covered by liquid clouds are presented for 4 months in 2005. The susceptibility estimates are based on expanded definitions presented in a companion paper and include relative cloud droplet number concentration (CDNC) changes, perturbations in cloud droplet asymmetry parameter and single-scattering albedo, atmospheric/surface effects, and incorporation of the full solar spectrum. The cloud properties (optical thickness and effective radius) used as input in the susceptibility calculations come from MODIS Terra and Aqua Collection 5 gridded data. Geographical distributions of susceptibility corresponding to absolute ( absolute cloud susceptibility ) and relative ( relative cloud susceptibility ) CDNC changes are markedly different indicating that the detailed nature of the cloud microphysical perturbation is important for determining the radiative forcing associated with the first indirect aerosol effect. However, both types of susceptibility exhibit common characteristics such as significant reductions when perturbations in single-scattering properties are omitted, significant increases when atmospheric absorption and surface albedo effects are ignored, and the tendency to decrease with latitude, to be higher over ocean than over land, and to be statistically similar between the morning and afternoon MODIS overpasses. The satellite-based susceptibility analysis helps elucidate the role of present-day cloud and land surface properties in indirect aerosol forcing responses. Our realistic yet moderate CDNC perturbations yield forcings on the order of 1-2 W/sq m for cloud optical property distributions and land surface spectral albedos observed by MODIS. Since susceptibilities can potentially be computed from model fields, these results have practical application in assessing the reasonableness of model-generated estimates of the aerosol indirect radiative forcing.
Results are summarized from three areas of ozone research: (1) continued analysis of the global distribution of total ozone to extend the global ozone atlas to summarize 15 years (1957-72) of ground based observations; (2) analysis of balloon borne ozonesonde observations for Arosa, Switzerland, and Hohenpeissenberg, Germany (GFR); (3) contined processing of the (Orbiting Geophysical Observatory-4) satellite data to complete the analysis of the stratospheric ozone distribution from the available OGO-4 data. Results of the analysis of the total ozone observations indicated that the long term ozone variation have marked regional patterns and tend to alternate with season and hemisphere. It is becoming increasingly clear that these long period changes are associated with large scale variations in the general upper atmosphere circulation patterns.
The robustness of the assigned prior distribution in a Bayesian estimation problem is examined. A Bayesian analysis for a stochastic intensity parameter of a Poisson distribution is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by assuming the existence of a true prior which is different in form from that of the assigned prior distribution. By using mean-squared error as a measure of performance, the ensuing Bayes decision function is compared to the corresponding minimum variance unbiased estimator. Results indicate that the Bayes estimator is largely robust to deviations from the assigned prior and remains squared-error superior to the MVU type within a broad region.
Our purpose was to evaluate normal tissue complication probability (NTCP) models for their ability to describe the increase in tolerance as the length of irradiated spinal nerve is reduced in a pig.
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A method is presented for calculating the spanwise lift distribution on straight-wing/propeller combinations. The method combines a modified form of the Prandtl wing theory with a realistic representation of the propeller slipstream distribution. The slipstream analysis permits calculations of the nonuniform axial and rotational slipstream velocity field of propeller/nacelle combinations. This nonuniform field was then used to calculate the wing lift distribution by means of the modified Prandtl wing theory. The theory was developed for any number of nonoverlapping propellers, on a wing with partial or full-span flaps, and is applicable throughout an aspect ratio range from 2.0 and higher. A computer program was used to calculate slipstream characteristics and wing span load distributions for a number of configurations for which experimental data are available, and favorable comparisons are demonstrated between the theoretical predictions and the existing data.
A technique is developed to measure the local convective heat transfer coefficient on a model surface in a supersonic flow field. The technique uses a laser to apply a discrete local heat flux at the model test surface, and an infrared camera system determines the local temperature distribution due to heating. From this temperature distribution and an analysis of the heating process, a local convective heat transfer coefficient is determined. The technique was used to measure the load surface convective heat transfer coefficient distribution on a flat plate at nominal Mach numbers of 2.5, 3.0, 3.5, and 4.0. The flat plate boundary layer initially was laminar and became transitional in the measurement region. The experimental results agreed reasonably well with theoretical predictions of convective heat transfer of flat plate laminar boundary layers. The results indicate that this non-intrusive optical measurement technique has the potential to obtain high quality surface convective heat transfer measurements in high speed flowfields.
A technique is developed to measure the local convective heat transfer coefficient on a model surface in a supersonic flow field. The technique uses a laser to apply a discrete local heat flux at the model test surface, and an infrared camera system determines the local temperature distribution due to the heating. From this temperature distribution and an analysis of the heating process, a local convective heat transfer coefficient is determined. The technique was used to measure the local surface convective heat transfer coefficient distribution on a flat plate at nominal Mach numbers of 2.5, 3.0, 3.5, and 4.0. The flat plate boundary layer initially was laminar and became transitional in the measurement region. The experimentally determined convective heat transfer coefficients were generally higher than the theoretical predictions for flat plate laminar boundary layers. However, the results indicate that this nonintrusive optical measurement technique has the potential to measure surface convective heat transfer coefficients in high speed flow fields.
A technique is developed to measure the local convective heat transfer coefficient on a model surface in a supersonic flow field. The technique uses a laser to apply a discrete local heat flux at the model test surface, and an infrared camera system determines the local temperature distribution due to the heating. From this temperature distribution and an analysis of the heating process, a local convective heat transfer coefficient is determined. The technique was used to measure the local surface convective heat transfer coefficient distribution on a flat plate at nominal Mach numbers of 2.5, 3.0, 3.5, and 4.0. The flat plate boundary layer initially was laminar and became transitional in the measurement region. The experimentally determined convective heat transfer coefficients were generally higher than the theoretical predictions for flat plate laminar boundary layers. However, the results indicate that this nonintrusive optical measurement technique has the potential to measure surface convective heat transfer coefficients in high-speed flowfields.
Real-time observations of transparent analog materials have provided insight, yet the results of these observations are not necessarily representative of opaque metallic systems. In order to study the detailed dynamics of the solidification process, we develop the technologies needed for real-time X ray microscopy of solidifying metallic systems, which has not previously been feasible with the necessary resolution, speed, and contrast. In initial studies of Al-In monotectic alloys unidirectionally solidified in an X-ray transparent furnace, in situ records of the evolution of interface morphologies, interfacial solute accumulation, and formation of the monotectic droplets were obtained for the first time: A radiomicrograph of Al-30In grown during aircraft parabolic maneuvers is presented, showing the volumetric phase distribution in this specimen. The benefits of using X-ray microscopy for postsolidification metallography include ease of specimen preparation, increased sensitivity, and three-dimensional analysis of phase distribution. Imaging of the solute boundary layer revealed that the isoconcentration lines are not parallel (as is often assumed) to the growth interface. Striations in the solidified crystal did not accurately decorate the interface position and shape. The monotectic composition alloy under some conditions grew in an uncoupled manner.
During July 2002, measurements of cloud condensation nuclei were made in the vicinity of southwest Florida as part of the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) field campaign. These observations, at supersaturations of 0.2 and 0.85%, are presented here. The performance of each of the two CCN counters was validated through laboratory calibration and an in situ intercomparison. The measurements indicate that the aerosol sampled during the campaign was predominantly marine in character: the median concentrations were 233 cm-3 (at S = 0.2%) and 371 cm(sup -3) (at S = 0.85%). Three flights during the experiment differed from this general trend; the aerosol sampled during the two flights on 18 July was more continental in character, and the observations on 28 July indicate high spatial variability and periods of very high aerosol concentrations. This study also includes a simplified aerosol/CCN closure analysis. Aerosol size distributions were measured simultaneously with the CCN observations, and these data are used to predict a CCN concentration using Kohler theory. For the purpose of this analysis, an idealized composition of pure ammonium sulfate was assumed. The analysis indicates that in this case, there was good general agreement between the predicted and observed CCN concentrations: at S = 0.2%, N(sub predicted)/N(sub observed)= 1.047 (R(sup 2)= 0.911)); at S = 0.85%, N(sub predicted)/N(sub observed)=1.201 (R(sup 2)= 0.835)). The impacts of the compositional assumption and of including in-cloud data in the analysis are addressed. The effect of removing the data from the 28 July flight is also examined; doing so improves the result of the closure analysis at S = 0.85%. When omitting that atypical flight, N(sub predicted)/N(sub observed) = 1.085 (R(sup 2) = 0.770) at S = 0.85%.
Performance Assessment models often require inputs representing specific hydrologic processes such as streamflow and sediment flux. This paper details the development of a process-level hydrologic model and its use in a Probabilistic Performance Assessment (PPA) system-level model for the West Valley Site in western New York. For this PPA model, a watershed model was developed using SWAT (Soil and Water Assessment Tool) and used to evaluate water and sediment fluxes in nearby streams draining the Site. A particular challenge of probabilistic modeling over long periods of time is scaling parameters appropriately so that outcomes are not grossly over- or underestimated. This challenge is especially important when the spatial and temporal scales of process and system level models differ. In this instance, the SWAT watershed model and GoldSim PPA model have similar spatial scales of stream reaches and sub-catchments within a single watershed (approximately hundreds to tens of thousands of square meters, but the temporal scales differ considerably. The SWAT model calculates streamflow and sediment transport rates at the daily scale, while the PPA model requires long-term average values that are applied over hundreds to thousands of year-long periods. As such, distributions of daily climatic parameters such as average precipitation rate, temperature, wind speed, and relative humidity were developed to force a transient SWAT model that captures the dynamic behavior of the watershed in response to daily changes in the weather. Output from the model, which includes stream flow (m{sup 3}/y) and sediment transport rate (Mg/y) is then averaged over a 100-year period as an approximation for the long-term average values which can be applied in GoldSim. A single SWAT model was run 5000 times with varying climatic inputs and deterministic soil, land use, and elevation data, and the range of outputs were compiled into a distribution which can be implemented stochastically into the PPA Model. Additionally, this paper includes a high-level discussion of how changes in future climate affect weather input distributions, and a summary of how those changes in weather affect the outcomes from the SWAT model and the inputs into the PPA model. In this analysis, future climate distributions were developed based on climate research documenting the expected changes to precipitation and temperature in western New York. The 5,000 SWAT simulations were then repeated with these future climate distributions, and the resulting output was implemented into the PPA Model as hydrologic conditions under a future climate. In the current version of the PPA Model, hydrologic parameters change linearly from the 'current climate' conditions to the 'future climate' conditions over a period of 100 years, after which they remain constant. (authors)
A coupled general ocean circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. The model is driven by climatological meteorological conditions, cloud cover, and sea surface temperature. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability, and the interactions among three functional phytoplankton groups (diatoms, chorophytes, and picoplankton) and three nutrient groups (nitrate, ammonium, and silicate). Phytoplankton groups are initialized as homogeneous fields horizontally and vertically, and allowed to distribute themselves according to the prevailing conditions. Basin-scale model chlorophyll results are in very good agreement with CZCS pigments in virtually every global region. Seasonal variability observed in the CZCS is also well represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are also in good conformance, although occasional departures are apparent. Agreement of nitrate distributions with in situ data is even better, including seasonal dynamics, except for the equatorial Atlantic. The good agreement of the model with satellite and in situ data sources indicates that the model dynamics realistically simulate phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization, and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.
Joint and marginal distributions in the frequency, direction, and time domain are employed to demonstrate their value for wave energy resource characterization when full spectra are available. Insights gained through analysis of these distributions support wave energy converter concept design, operation and maintenance. Spatial trends in the wave energy resource and contributing wave energy systems along the continental shelf of the West Coast of the United States are investigated using the most recent two-dimensional wave spectra measurements at four buoys over an eleven year period (2008 to 2018). Resource hot spots and dominant resolved energy resource bands in the frequency-direction-time domain are delineated. Resource attributes, including frequency and directional spreading, and seasonal variability, are characterized using joint distributions and marginal distributions of wave power spectra. North Pacific westerly swells in the winter season, augmented by Aleutian low-pressure southwesterly swells, are the principal suppliers of the dominant resource and main drivers influencing resource attributes. In conclusion, the modification of these systems southward, especially the North Pacific westerly swells, explains the observed spatial resource trends. The dominant resource wave period shifts two seconds to higher wave periods, thirty degrees in the dominant direction band to a more northward orientation, and forward by one month.
The Boltzmann-Fokker-Planck equation is solved with the Chapman-Enskog method of analysis for the velocity distribution functions of helium, carbon, nitrogen, and oxygen. The analysis is a perturbation scheme based on the assumption of a collision-dominated gas, and the calculations are carried out to first order. The elements considered are treated as trace constituents in an electron-proton gas. From the resulting distribution functions, diffusion coefficients are computed which are found to be 20-30% less than those obtained by Chapman and Burgers. In addition, it is shown that the return current of cold electrons needed to maintain quasi-neutrality in a plasma with a temperature gradient contributes a term in the thermal diffusion coefficient omitted erroneously in previous works. This added term resolves the longstanding controversy over the discrepancy between the coefficients of Chapman and Burgers, which are seen to be completely equivalent in the light of this analysis. The viscosity coefficient for an electron-proton gas is also computed and found to be 7% less than that obtained by Braginskii.
The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).