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22 results for “Atmospheric properties”
Influence of Atmospheric Air Plasma Pre-Treatment of Veneers on the Mechanical Properties and Stability of Beech Plywood
<p>Wood-based sheet materials such as plywood, fiberboard, particleboard, and oriented strain board find applications in civil engineering, building technology, furniture manufacturing and many more. All these materials rely strongly on an effective bond formation between the resin and the wood base material, which gives rise to their mechanical performance and stability, as well as their resistance to moisture and liquids. In our study, we present the use of a commercial atmospheric air plasma system, which we used for the pretreatment of veneers of common beech (<em>Fagus sylvatica</em> L.) wood before formation of plywood boards. Plasma treatment parameters were optimized following the change in water contact angle. Two different stacking patterns were used for plasma-treated veneers. The time stability of the plasma modification was investigated by forming a second set of plywood boards 70 hours after plasma treatment of the respective veneers. The influence of the plasma treatment on mechanical properties was studied via bending and shear strength of the four sets of plasma-treated boards in comparison to a plywood out of the same veneer without plasma treatment. Water and moisture resistance were tested through water immersion and surface water resistance tests. Further, confocal laser scanning microscopy was used to determine changes of the surfaces’ morphologies.</p>
The dataset by "Spectrally Consistent Scattering, Absorption, and Polarization Properties of Atmospheric Ice Crystals at Wavelengths from 0.2 to 100 μm"
<p>This is the ice crystal single-scattering property dataset introduced in the paper "Yang, Ping, et al. "Spectrally consistent scattering, absorption, and polarization properties of atmospheric ice crystals at wavelengths from 0.2 to 100 μ m." <em>Journal of the Atmospheric Sciences</em> 70.1 (2013): 330-347.".</p>
Simulated top-of-atmosphere (120 km) downward and upward solar and thermal-infrared irradiances and ice cloud optical thickness; calculated solar, TIR and net cloud radiative effect. Simulated with ice crystal properties for aggregates, droxtals, and plates based on Yang (2013).
<p>This dataset consists of three .nc files for ice crystal shapes of aggregates, plates, and droxtals. The files include ice cloud optical thickness <span class="math-tex">\(\tau\)</span> (550nm), the simulated upward and downward irradiances <span class="math-tex">\(F\)</span> at the top-of-atmosphere (with and without the presence of the ice cloud), and the calculated ice cloud radiative effect <span class="math-tex">\(\Delta F\)</span> (solar [0.3-3.5 <span class="math-tex">\(\mu\)</span>m], thermal-infrared [3.5-75 <span class="math-tex">\(\mu\)</span>m], and net). The data set allows the user to extract <span class="math-tex">\(\Delta F\)</span> values for their parameter combinations. The available cloudy and cloud-free irradiances further allow to calculate the cirrus radiative effect (RE) by scaling the 'cloudy' RE with the required cloud cover. This serves as a first-approximation because, as 3D effects are neglected.</p>
Closure Study on Hygroscopic Properties of Water-soluble Matter in Atmospheric PM2.5 at a Rural Site in Northwest China
<p>The data supports the manuscript entitled “<strong>Closure Study on </strong><strong>Hygroscopic Properties</strong> <strong>of Water-soluble Matter in Atmospheric PM<sub>2.5</sub> at a Rural Site in Northwest China”</strong>. The data can be used freely for scientific purposes with the appropriate citation.</p>
Data from: Elevated atmospheric concentrations of carbon dioxide reduce monarch tolerance and increase parasite virulence by altering the medicinal properties of milkweeds
Hosts combat their parasites using mechanisms of resistance and tolerance, which together determine parasite virulence. Environmental factors, including diet, mediate the impact of parasites on hosts, with diet providing nutritional and medicinal properties. Here, we present the first evidence that ongoing environmental change decreases host tolerance and increases parasite virulence through a loss of dietary medicinal quality. Monarch butterflies use dietary toxins (cardenolides) to reduce the deleterious impacts of a protozoan parasite. We fed monarch larvae foliage from four milkweed species grown under either elevated or ambient CO2, and measured changes in resistance, tolerance, and virulence. The most high-cardenolide milkweed species lost its medicinal properties under elevated CO2; monarch tolerance to infection decreased, and parasite virulence increased. Declines in medicinal quality were associated with declines in foliar concentrations of lipophilic cardenolides. Our results emphasize that global environmental change may influence parasite-host interactions through changes in the medicinal properties of plants.
Flowfield Properties for Calculating Electrical Conductivity in a CO2 Atmosphere
<p>This dataset provides flowfield quantities necessary to calculate the electrical conductivity in the flowfield around an entry vehicle in a CO2 atmosphere. The CFD data was generated using the Data Parallel Line Relaxation Code. The freestream conditions cover velocities from 5 - 12 km/s and altitudes from 20 - 80 km at Mars (85 - 115 km at Venus). The vehicle geometry is a 10 m diameter 70 deg spherecone.</p>
Datasets for Yue et al. (2022), Atmospheric Measurement Techniques: "Evaluating the Consistency and Continuity of Pixel-Scale Cloud Property Data Records From Aqua and SNPP"
<p>Pixel scaled collocated AIRS, Aqua MODIS, SNPP CrIS, and SNPP VIIRS cloud retrieval products. These datasets are used to generate analyses and results presented in Yue et al. (2022, AMT): "Evaluating the Consistency and Continuity of Pixel-Scale Cloud Property Data Records From Aqua and SNPP"</p>
Additional Figures for winning models for sample in A Comparative L-dwarf Sample Exploring the Interplay Between Atmospheric Assumptions and Data Properties
<p>Additional Figures for winning models for sample in <em>A Comparative L-dwarf Sample Exploring the Interplay Between Atmospheric Assumptions and Data Properties (<a href="https://arxiv.org/pdf/2209.02754.pdf">https://arxiv.org/pdf/2209.02754.pdf</a>).</em></p> <p>Model naming key: NC = cloud-free, d2_89 = power-law deck cloud</p> <p>SDSS J1416+1348A: Winning model: power-law deck cloud</p> <p>Spectral Type Comparison J1526+2043 Winning model: Cloud-free</p> <p>Temperature Comparisons</p> <p>J1539-0520 Winning model: Power-law deck cloud and cloud-free tied.</p> <p>J0539-0059 Winning model: Power-law deck cloud and cloud-free tied. </p> <p><br> </p>
The SPHINX M-dwarf Spectral Grid. I. Benchmarking New Model Atmospheres to Derive Fundamental M-Dwarf Properties
<p><strong>NEW UPDATE:::::::::::::VERSION 4</strong></p> <p>MODEL GRID AND SUPPLEMENTARY FIGURES for <strong>The SPHINX M-dwarf Spectral Grid. I. Benchmarking New Model Atmospheres to Derive Fundamental M-Dwarf Properties:</strong></p> <p><strong>(1) MODEL GRID:</strong> Zip file titled 'SPHINX_MODELS_MLT_1.zip' contains a directory (376MB on disk) that is divided into three folders: ATMS, SPECTRA, and ABUNDANCES. All models here assume mixing length parameter of 1. For more info, we direct the reader to the paper.</p> <p>The ATMS directory contains thermal profiles/atmospheres of all models. (Temperature in K, Pressure in bars)</p> <p>The SPECTRA directory contains synthetic spectra. (Wavelength--0.1 to 20 microns, Flux in W/m2/m, R~250)</p> <p>The ABUNDANCES directory contains mixing ratios of all atomic and molecular species included in these models.</p> <p><strong>(2) SUPPLEMENTARY FIGURES:</strong></p> <p>The plot files are named as 'target name' _ corner.</p> <p>Each file is a corner plot of posterior probability distributions from grid-model fit of low-resolution spectra of benchmark M dwarfs using the SPHINX model grid. We also include posterior distributions of Starfish (Czekala et al.2015) hyperparameters to properly constrain model and data systematics. The vertical blue lines in the plots indicate values from observations (empirically derived [M/H] from Mann et al. 2013 and interferometrically measured radii from Boyajian et al. 2012b).</p> <p>File named Gl436_mixinglength shows difference in grid model fit assuming mixing length parameter 1 vs 0.5.</p> <p>File named Gl725B_spot shows difference in grid model fit assuming stellar photospheric heterogeneity vs without.</p> <p><strong>If you use our stellar atmosphere models, please remember to cite both the zenodo doi for the open source data as well as the paper. Thank you!</strong></p> <p> </p> <p>--> link to <a href="https://iopscience.iop.org/article/10.3847/1538-4357/acabc2/meta">published paper</a></p>
Data from: Separating the impact of individual land surface properties on the terrestrial surface energy budget in both the coupled and uncoupled land–atmosphere system
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Data from: Elevated atmospheric concentrations of carbon dioxide reduce monarch tolerance and increase parasite virulence by altering the medicinal properties of milkweeds
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Dataset 2 "Aerosol optical properties within the atmospheric boundary layer predicted from ground-based observations compared to Raman lidar retrievals during RITA-2021"
<p>This dataset provides additional profiles for the manuscript titled "Aerosol optical properties within the atmospheric boundary layer predicted from ground-based observations compared to Raman lidar retrievals during RITA-2021". It is available for those who are interested.</p>
Data set for publication "Effect of milling atmosphere on stability and surface properties of ZnO/vermiculite hybrid nanocomposite powders"
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X-Shooting ULLYSES: Massive Stars at low metallicity VI. Atmosphere and mass-loss properties of O-type giants in the SMC
<p>Figures from X-Shooting ULLYSES: Massive Stars at low metallicity VI. Atmosphere and mass-loss properties of O-type giants in the SMC. The individual fits of the stars and their explored parameter space. </p> <p>Caption:</p> <p>Overview of the fitting results of AV\,80. The \textit{top} part shows the line profiles included in the fitting process, with the name of each feature indicated in the bottom left. The green line shows the best fit, with the shaded region showing the 1$\sigma$ uncertainty on the model fit. The black vertical bars indicate the observed flux, with the length indicating the uncertainty. The horizontal axis shows the wavelength in \AA. The \textit{bottom} part shows the distribution of $1/\chi^2_{\rm r}$ for each parameter (indicated on the top left), with $\chi^2_{\rm r}$ the reduced $\chi^2$ value. Each scatter point indicates one {\sc Fastwind} model calculated by Kiwi-GA. The color indicates the generation in which the model was computed, with light gray the first generation and black the last. The vertical yellow line indicates the best fit value for each parameter, and the shaded regions are the 1 and 2 $\sigma$ confidence intervals. The distributions in the red shaded area are from the optical only GA fit.</p>
Sand transport processes change in response to changing atmospheric properties at higher elevations
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Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Atmospheric Properties from PREFIRE Satellite 1 R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Atmospheric Properties from PREFIRE Satellite 1 (PREFIRE_SAT1_2B-ATM) contains several geophysical variables, such as atmospheric temperature and water content, derived from data collected by the PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) aboard PREFIRE-SAT1. Dual CubeSats each carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other models to predict future conditions more accurately.PREFIRE_SAT1_2B-ATM contains column water vapor, temperature, pressure, and water vapor profiles, surface temperature, and surface pressure as derived from PREFIRE Spectral Radiance (PREFIRE_SAT1_1B-RAD) data using an Optimal Estimation retrieval via a Radiative Transfer Model with inputs from PREFIRE_SAT1_2B-MSK (cloud mask), PREFIRE_SAT1_AUX-MET, and PREFIRE_SAT1_SFC. Science data retrieval started July 24, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each PREFIRE-TIRS. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was ~264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint size will slowly become smaller as the orbit altitude decreases with time. This data has a temporal resolution of 0.707 seconds and is available in netCDF-4.The atmospheric properties data for the sister instrument aboard PREFIRE-SAT2 can be found in the PREFIRE_SAT2_2B-ATM collection.
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Atmospheric Properties from PREFIRE Satellite 1 COG R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Atmospheric Properties from PREFIRE Satellite 1 COG (PREFIRE_SAT1_2B-ATM_COG) is derived from data collected by the PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) aboard PREFIRE-SAT1. Dual CubeSats each carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other models to predict future conditions more accurately.PREFIRE_SAT1_2B-ATM_COG contains Cloud-Optimized GeoTIFF (COG) files that each contain a georeferenced rendering of retrieved column water vapor (CWV) values. Those CWV data values are computed from a single granule of PREFIRE Spectral Radiance (PREFIRE_SAT1_1B-RAD) data using an Optimal Estimation retrieval via a radiative transfer model with inputs from PREFIRE_SAT1_2B-MSK (cloud mask), PREFIRE_SAT1_AUX-MET, and PREFIRE_SAT1_2B-SFC. The retrieved CWV values are only available for clear-sky conditions. As part of the rendering process, mean retrieved CWV values are computed for a global grid of raster elements (each approximately 2.23 km in width), based on which raster elements each PREFIRE ground footprint overlaps. This procedure is done in order to better visualize the PREFIRE data despite substantial overlap of adjacent along-track ground footprints – but it is important to remember that the individual PREFIRE ground footprints are much bigger (by about 80x, in terms of area) than each of the GeoTIFF raster elements. These cloud-optimized GeoTIFF images may be viewed using many geographic information systems (GIS), such as the freely available QGIS.Science data retrieval started July 24, 2024 and is ongoing. Currently, the geographic coverage is for latitudes between approximately 60° to 84° in both polar regions, although future releases may include data for all latitudes equatorward of about 84°. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each TIRS-PREFIRE. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was about 264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint and swath sizes will slowly become smaller as the orbit altitude decreases with time.Similar CWV GeoTIFF renderings for the sister instrument aboard PREFIRE-SAT2 can be found in the PREFIRE_SAT2_2B-ATM_COG collection.
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Atmospheric Properties from PREFIRE Satellite 2 R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Atmospheric Properties from PREFIRE Satellite 2 (PREFIRE_SAT2_2B-ATM) contains several geophysical variables, such as atmospheric temperature and water content, derived from data collected by the PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) aboard PREFIRE-SAT2. Dual CubeSats each carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other models to predict future conditions more accurately.PREFIRE_SAT2_2B-ATM contains column water vapor, temperature, pressure, and water vapor profiles, surface temperature, and surface pressure as derived from PREFIRE Spectral Radiance (PREFIRE_SAT2_1B-RAD) data using an Optimal Estimation retrieval via a Radiative Transfer Model with inputs from PREFIRE_SAT2_2B-MSK (cloud mask), PREFIRE_SAT2_AUX-MET, and PREFIRE_SAT2_SFC. Science data retrieval started June 29, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each PREFIRE-TIRS. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was ~264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint size will slowly become smaller as the orbit altitude decreases with time. This data has a temporal resolution of 0.707 seconds and is available in netCDF-4.The atmospheric properties data for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_2B-ATM collection.
Fractal geometry features of aerosol particle and its contribution to atmospheric optical property: development of Fractal Aerosol Cluster Model and its validation of atmospheric visibility during a heavy haze event
<p>-------------------------<br>Content of the dataset<br>-------------------------<br>****** the experiment case (EXP) ; the control case (CTR) ******</p> <p>1. Meteorological elements.tar contains observational and simulated data for T2, WS, RH, and PM2.5 time series, which can be used to plot Figure 4 and build Table 2</p> <p>2. Planar distribution.tar contains the horizontal spatial distribution data of aerosol extinction coefficients simulated by CTR and EXP for the four typical moments selected in this paper, which can be used to plot Figures 5, 6, and 7</p> <p>3. PM.rar contains the vertical profile data of simulated Particulate Matter concentrations by CTR and EXP during the study period in the paper, which can be utilized for drawing Fig. 11.</p> <p>4. Timeseries.tar contains observational and simulated data for time series of atmospheric visibility and surface shortwave radiation, which can be used to plot Figures 5, 6, 7, 8, S1, and build Table 3</p> <p>5. wrfbiochemi.rar contains the biogenic emissions data for simulation both for CTR and EXP.</p> <p>6. wrffirechemi.rar contains the biomass burning emissions data for simulation both for CTR and EXP.</p> <p>7. wrfchemi.rar contains the Anthropogenic emissions data for simulation both for CTR and EXP.</p> <p>8. The file module_optical_averaging.F contains the main code of the improved visibility model, the Fractal Aerosol Cluster Model</p> <p>(FACM), which is coupled to WRF-Chem and used by EXP. It is located in the chem/ directory and called by optical_driver.F.</p> <pre> </pre> <p> </p> <p>-------------------------</p> <p>Contact information</p> <p>-------------------------</p> <p> </p> <p>Zhenxin Liu</p> <p>liuzhenxin@nuist.edu.cn</p> <p> </p> <p> </p>
Flowfield Properties for Calculating Electrical Conductivity in a Rarefied CO2 Atmosphere with DSMC
<p>This dataset provides flowfield quantities necessary to calculate the electrical conductivity in the flowfield around an entry vehicle in a rarefied CO2 atmosphere. The DSMC data was generated using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer. The freestream conditions cover velocities from 6 - 8.5 km/s and altitudes from 80 - 110 km at Mars. The vehicle geometry is a 70 deg spherecone with varying diameters between 5 and 10 m.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.