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3,018 results for “aire”
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 5, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 7, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from a side-slope station located in Watershed 27, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from a ridge station in Watershed 18, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 32, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Continuously measured soil moisture, soil temperature, and air temperature from stations in Watershed 36, Coweeta Hydrologic Laboratory
Long-term soil moisture stations were established within the Coweeta Hydrologic Lab Basin to collect measurements of soil moisture, soil temperature, air temperature, and relative humidity at a range of spatial scales, from ridge to cove and low to high elevations in the southern Appalachians, and across the regional range of rainfall amounts.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Soil and Air Temperature
Soil temperature was measured on all Climate Change Across Seasons Experiment (CCASE) plots. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). This data set includes tree dbh measurements for 2012. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
McMurdo Dry Valleys Glacier melt modeling: Air Temperature 1996-2011
This is the data and metatada for modeled Air Temperature - part of six modeled parameters that comprise the Taylor Valley Galcier Melt modeling Data contained and described in this document correspond to the physically-based surface energy balance model for the glaciers of Taylor Valley developed by the dataset owners. The spatial variability in ablation (ice melt and sublimation), runoff, and climate sensitivity of the glaciers was modeled using 16 years of meteorological and surface mass balance (the net mass gain or loss of ice on the surface of the glacier) observations collected in Taylor Valley (see figure).  An unusual aspect of the model is the inclusion of transmission of solar radiation into the ice and subsequent drainage of some subsurface melt .  Melt model was applied to the ablation zones of the glaciers of Taylor Valley, identified by colored areas. Mass balance stakes, meteorological stations, and stream gages shown for reference. This dataset package is part of a 6-pack multi-set, which you can find at http://mcmlter.org The input files, parameters and examples are found in this package: http://mcmlter.org/content/glacier-melt-modeling-inputs-and-example-m-file-reader
Air temperature and solar radiation data for Green Lake 4 data logger (DP211), 1986 - 2006.
Climatological data were collected from an upper Green Lakes Valley climate station (Green Lake 4=D4) throughout the year using an Omnidata DP211 datapod. This instrument has a sample interval of 5 minutes and records averages of those 5-minute readings every 2 hours. Thus, daily totals represent totals of 288 values. Parameters measured were temperature and solar radiation.
Air temperature and solar radiation data for Saddle data logger (DP211), 1990 - 2006.
Climatological data were collected from a Niwot Ridge climate station (Saddle) throughout the year using an Omnidata DP211 datapod. This instrument has a sample interval of 5 minutes and records averages of those 5-minute readings every 2 hours. Thus, daily totals represent totals of 288 values. Parameters measured were air temperature (averages) and solar radiation (totals).
High resolution Air Photo Mosaic for Hog Island, VA, 2011
High resolution (6 cm pixel) RGB true color tiled air photo mosaics for Hog Island, Northampton County, VA, collected on October 11, 2011 on behalf of the USACE Engineer Research and Development Center using the Coastal Zone Mapping and Imaging Lidar (CZMIL) system. CZMIL integrates a lidar sensor with topographic and bathymetric capabilities, a digital camera and a hyperspectral imager on a single remote sensing platform for use in coastal mapping and charting activities. LiDAR data is provided as a separate VCRLTER dataset. Two data entities are included here: (1) a tiled collection of air photo mosaics created from the CZMIL camera imagery (6 cm. resolution; tiles approximately 690 x 715 m. in X and Y, resp.) composed of 71 individual georeferenced TIFF files; and (2) a polygon INDEX shapefile showing the footprint of each TIFF file and containing ID information in the attribute table (column, row, and colrow matching the TIFF naming convention). Note that the two co-collected 2011 USACE datasets (LiDAR and RGB ) are in different coordinate systems: (A) the horizontal and vertical units of the LiDAR data are in US feet, not meters; and (B) the horizontal units of the associated RGB mosaic images are in [standard] meters. Also Note that THESE ARE VERY LARGE DATASETS and download should not be attempted unless you have a fast network connection and plenty of disk space. The LAS file data collection is 7.3 GB compressed (11.7 GB uncompressed). The RGB imagery mosaic data collection is 12.9 GB compressed (30.8 GB uncompressed).
Air-sea gas transfer velocities measured at wind speeds up to 85m/s in fresh water and seawater
<p>This data set contains gas transfer velocities of 12 tracers (CF4, He, SF6, He, Kr, Pentafluoroethane, Xe, Acetylene, Hexafluorobenzene, Difluoromethane, 1,4-Difluorobenzene, Dimethyl Sulfide, Methyl Acetate) measured in the Kyoto High Speed Wind-Wave tank with fresh water and modeled seawater and the Miami SUSTAIN wind-wave tank with seawater at wind speeds up to 85m/s.</p> <p> </p>
Air quality Modelling data for Guildford City
<p>The simulation data for Guildford City using ADMS-Urban at 1 km spatial resolution. </p>
Malaga air quality
<p>An open-source dataset containing air quality information for Malaga in 2018</p>
Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants
<p>Data for "Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants"</p>
Near-global CFC-11 retrieved from Atmospheric Infrared Sounder (AIRS) from 2003 to 2018
<p>CFC-11 surface mole fractions were retrieved from monthly clear-sky nadir-view Atmospheric Infrared Sounder (AIRS) observations on 30-deg by 10-deg over 55S-55N. </p> <p>Dataset is available at https://github.com/Huang-Group-UMICH/CFC-11-retrievals-from-AIRS.</p>
Five-minute average horizontal wind velocity data combined from both sensors (which has been corrected for air-flow distortion) from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4.
<p><strong>Dataset abstract</strong></p> <p>The horizontal wind velocity data from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4 has been corrected for air-flow distortion. The measurements from both the port and starboad side anemometer were averaged to five-minute resolution and have been combined via vector averaging of the data. The ten meter neutral wind speed (U10N) has been estimated using ERA-5 surface heat fluxes, which were interpolated onto the ship's track, and the COARE 3.5 drag coefficient. This data set provides a continous and high-resolution record of the wind speed and direction near to the ship's location.</p> <p><strong>Dataset contents</strong></p> <ul> <li>wind-observations-port-stbd-corrected-combined-5min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This five-minute averaged wind velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This data set contains the air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017. The data are provided over overlapping wind direction secotors of 5(10) degree width stepped by 1(2) degrees relative wind direction. These bias factors can be used to correct the observed wind speeds for air-flow distortion on a sample by sample basis. For details see Landwehr et al. (2019; DOI: https://doi.org/10.5194/amt-2019-366).</p> <p><strong>Dataset contents</strong></p> <ul> <li>flow_distortion_bias_sensor1.csv, data file, comma-separated values</li> <li>flow_distortion_bias_sensor2.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This dataset of air-flow distortion factors is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
One-minute average horizontal wind velocity data (which has been corrected for air-flow distortion) from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4.
<p><strong>Dataset abstract</strong></p> <p>One-minute average horizontal wind velocity data from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4. The data has been filtered for spurious observations and the true wind correction has been redone using the quality checked one-minute ship track velocity data. The data has been corrected for air-flow distortion, which was caused by the ship's super structure.</p> <p><strong>Dataset contents</strong></p> <ul> <li>wind-observations-stbd-corrected-1min-legs0-4.csv, data file, comma-separated values</li> <li>wind-observations-port-corrected-1min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This one-minute averaged wind velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Enhancing accuracy of air quality and temperature forecasts during paddy crop-residue burning season in Delhi via chemical data assimilation
<p>This paper examines the accuracy of Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) generated 72 h fine particulate matter (PM<sub>2.5</sub>) forecasts in Delhi during the crop residue burning season of Oct-Nov 2017 with respect to assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals, persistent fire emission assumption, and aerosol-radiation interactions. The assimilation significantly pushes the model AOD and PM<sub>2.5</sub> towards the observations with the largest changes below 5 km altitude in the fire source regions (northeastern Pakistan, Punjab, and Haryana) as well as the receptor New Delhi. WRF-Chem forecast with MODIS AOD assimilation, aerosol-radiation feedback turned on, and real-time fire emissions reduce the mean bias by 88-195 µg/m<sup>3</sup> (70-86%) with the largest improvement during the peak air pollution episode of 6-13 November 2017. Aerosol-radiation feedback contributes ~21%, ~25%, and ~24% to reduction in mean bias of the first, second, and third day of PM<sub>2.5 </sub>forecast. Persistence fire emission assumption is found to work really well, as the accuracy of PM<sub>2.5</sub> forecasts driven by persistent fire emissions was only 6% lower compared to those driven by real fire emissions. Aerosol-radiation feedback extends the benefits of assimilating satellite AOD beyond PM<sub>2.5</sub> forecasts to surface temperature forecast with a reduction in the mean bias of 0.9<sup>o</sup>C - 1.5<sup>o</sup>C (17-30%). These results demonstrate that air quality forecasting can benefit substantially from satellite AOD observations particularly in developing countries that lack resources to rapidly build dense air quality monitoring networks.</p>
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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.