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708 results for “Temperature, air”
Exhaled Air Temperature (TAE) As A Marker Of Airway Inflammation In Asthma
ClinicalTrials.gov study NCT02064686. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Air temperature influences early Covid-19 outbreak as indicated by worldwide mortality
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Air temperature data recorded in a shaded area near the shore of the study site Laguna Toreadora (3,920 m asl) from August 2014 to September 2016 using a HOBO Water Temperature Pro v2 Data Logger.
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Leaf traits and leaf-to-air temperature differences in tropical plants suggest variability in thermoregulatory capacities across elevations
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Data from: Disentangling effects of air and soil temperature on C allocation in cold environments: a 14C pulse labelling study with two plant species
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Data from: Interactive effects of soil moisture, air temperature and litter nutrient diversity on soil microbial communities and Folsomia candida population
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Data from: Longleaf pine proximity effects on air temperatures and hardwood top-kill from prescribed fire
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Traces of air and body temperature in six hummingbird species in the Andes
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Ground and Air Temperatures on Hog Island, VA in grassland, shrub thicket, and transition, 2014-2018
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TROPESS AIRS-Aqua L2 Atmospheric Temperature for Forward Stream, Standard Product V1 (TRPSDL2TATMAIRSFS) at GES DISC
The TROPESS AIRS-Aqua L2 Atmospheric Temperature for Forward Stream, Standard Product contains the vertical distribution of the retrieved atmospheric state of atmospheric temperature (TATM), formal uncertainties, and diagnostic information measured by the AIRS instrument on the EOS Aqua satellite. The forward stream standard product is global for the time period from 2021-02-01 to present. The NASA TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) project, uses an optimal estimation algorithm, known as the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES).The data files are written in the netCDF version 4 file format, and each file contains one day of data. The data have a spatial resolution of 14 km (AIRS nadir FOV), and are reported at 31 vertical levels from the surface to 0.1 hPa. The principal investigator for the TROPESS project is Kevin W. Bowman.
Data and model scripts for "Non-structural carbohydrate dynamics associated with antecedent stem water potential and air temperature in a dominant desert shrub"
<p>Model code and data as used in the first revision submitted to Plant, Cell and Environment, Feb. 2020. </p> <p>Models are coded in JAGS or OpenBUGS and run in R. Three related models are presented:</p> <p>1) "mod_allometry.R" and "jags_allometry.R" run the aboveground biomass allometry model described in Methods S1, utilizing stem and leaf mass data ("data_allometry.Rdata") and the associated initial values ("inits_allometry.Rdata")</p> <p>2) "mod_predawn.R" and "bugs_predawn.R" run the gap-filling model described in Methods S2, utilizing predawn water potential data ("data_predawn.Rdata") and the associated initial values ("inits_predawn.Rdata")</p> <p>3) "mod_NSC.R" and "bugs_NSC.R" run the NSC model described in the main text of the manuscript, utilizing NSC and covariate data ("data_NSC.Rdata") and the associated initial values ("inits_NSC.Rdata")</p>
Detectable urbanization effect in observed surface air temperature data series in Pyongyang region, DPR Korea-Supporting Information-data
<p>This is the calculated dataset as supplemental information of a paper entitled "Detectable urbanization effect in observed surface air temperature data series in Pyongyang region, DPR Korea", which will be likely published in Geophysical Research Letters.</p> <p> </p> <p> </p> <p> </p>
1-km daily average air temperature of the Tibetan Plateau (1980-2014)
<p>1) Data content (including elements and meanings): Gridded daily average air temperature of the Tibetan Plateau during 1980-2014 at 1-km resolution</p> <p>2) Data source and processing method: Developed by integrating 8 types of reanalysis data (i.e., NNRP-2, 20CRV2c, JRA-55, ERA-Interim, MERRA2, CFSR, GLDAS and ERA5) downscaled with MODIS-estimated temperature lapse rates based on machine learing</p> <p>3) Data quality description: According to leave-one-out validation based on stations, the average RMSE at China Adimistration Stations is about 1.7 ℃ and that at high-elevation field stations is about 1.9 ℃</p> <p>4) Data application results and prospects: This dataset can be used as air temperature input for driving long-term hydrologial modelling or evaluated for use in climate analysis</p> <p>5) Recommended Citation: Zhang, H., Zhang, F., Zhang, G., Che, T., & Yan, W. (2018). How accurately can the air temperature lapse rate over the Tibetan Plateau be estimated from MODIS LSTs?. Journal of Geophysical Research: Atmospheres, 123(8), 3943-3960.</p>
Effect of earth-air and temperature variation on the concentration of CO2 in the soil in extremely arid regions
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A Daily Highest Air Temperature dataset in China from 1979 to 2018
<p>The DHAT dataset is a daily highest air temperature data during the period of 1979-2018, in Celsius, in daily temporal and 0.1° spatial resolution.</p> <p>It is produced by using meteorological station data and near-surface air temperature reanalysis data (CMFD and ERA5) combined with diurnal variation model of air temperature to establish daily highest air temperature data, and then a correction model is constructed to further correct the data to improve the data accuracy according to different geographic partitions. The accuracy assessments indicate that the dataset exhibits high accuracy and can be used for climate change analysis in China.</p>
Body-air temperature relationship in ectotherms
<p>Dataset and R code to run the thermal model for 1985-2019.</p>
A Comparison of Two Methods For Resolving Displacement Heights in Fitting Logarithmic Windspeed and Air Temperature Profiles
<p>This respository houses a distribution of percentage errors as a comparison between estimated aerodynamic parameters and their known values. This helps to test and quantify the overall accuracy of a new method to resolve the displacement heights in fitting logarithmic windspeed and temperature profiles. This dataset is associated with the MRes project '<span>Aerodynamic Roughness Controlled by Wind Direction, with Implications for Glacial Surface Energy Balance and Melt Rate</span>', by Josh Abrahams, University of Leeds. </p>
Figure 1 in Vocalizations of the Brazilian torrent frog Hylodes heyeri (Anura: Hylodidae): Repertoire and influence of air temperature on advertisement call variation
Figure 1. Advertisement call of Hylodes heyeri from the Municipality of Morretes, Parana´, Brazil. Recorded on 8 April 2002, at 21.7°C. (A) Power spectrum; (B) spectrogram; (C) oscillogram.
Air temperature of surface observation data
<p>Air temperature of surface observation data</p>
Air temperature and thermal comfort data measured and modelled for 121 workplaces in the Upper Rhine Valley
<p>The uploaded files contain the measured and modelled indoor data at different workplaces in the Upper Rhine Valley between August 1, 2021, and July 31, 2022 presented in the article "Predicting Indoor Air Temperature and Thermal Comfort in Occupational Settings Using Weather Forecasts, Indoor Sensors, and Artificial Neural Networks" by Sulzer et al. (2023), <a href="http://doi.org/10.1016/j.buildenv.2023.110077">doi.org/10.1016/j.buildenv.2023.110077</a>. Information about the characteristics of each workplace can be found in the appendix of the article. For every workplace two files are uploaded, one for the data of the indoor air temperature (Ta) and one for indoor physiological equivalent temperature (PET). The workplace ID and variable are stated in the filename. The columns in the files contain the following data:</p> <ul> <li>"Datetime (UTC)": This column contains the timestamp in UTC of the starting point of the interval used for the one-hour mean values .</li> <li>"MoBiMet data": This column contains the one-hour mean values of Ta or PET of the data derived every five minutes by the low-cost Mobile Biometeorology System (MoBiMet) at the corresponding workplace in °C. The MoBiMet are presented in detail in <a href="http://doi.org/10.3390/s22051828">doi.org/10.3390/s22051828</a>.</li> <li>"Used for": This column contains the information if the data point was used for training of the models (t), evaluation of the models (e), or not used for model training or evaluation due to missing indoor observation data (n).</li> <li>"Product 0 (ICON_outdoor)": This column, in the files for the indoor air temperature, contains the ICON-D2 data of the air temperature 2m a.g.l. in °C of the grid cell in which the associated work station is located.</li> <li>"Product 0 (ICON_outdoor) air temperatur 2m (C) input for PET calculation using RayMan","Product 1 (ICON_outdoor) vapor pressure 2m (hPa) input for PET calculation using RayMan","Product 1 (ICON_outdoor) wind speed 10m (m/s) input for PET calculation using RayMan", and "Product 1 (ICON_outdoor) global radiation surface (W/m²) input for PET calculation using RayMan": This columns contain the data of the outdoor air temperature 2m a.g.l. in °C, the vapor pressure 2m a.g.l., derived from the ICON-D2 weather forecast data of the grid cell in which the associated work station is located, which were used in RayMan Pro to calculate the PET for outdoors.</li> <li>"Product 2 (ANN_Generic)": This column contains the indoor data of PET or air temperature in °C modelled by an artificial neural network using generic data as input. The generic data contain hourly solar altitude and azimuth at each location, the weekday, and a sine and cosine function of the daily and yearly cycle.</li> <li>"Product 3 (ANN_AWS) without past data": This column contains the indoor data of PET or air temperature in °C modelled by an artificial neural network using generic data and the meteorological data of air temperature, vapor pressure, mean sea level pressure, global radiation, longwave downwelling radiation, and wind speed of an automated weather station in Freiburg (Station FRCHEM; 48°00’04’’ N; 7°50’55’’ E).</li> <li>"Product 3 (ANN_AWS) with past data": This column contains similar data than the column before but the artificial neural network models used "past data" of the automated weather station as additional input variables to model indoor air temperature and PET in °C. Additional to the hourly average of the meteorological data for each actual time (t), hourly averages for t-1 h, t-3 h, t-6 h, t-12 h, and t-24 h of air temperature, global radiation, and Longwave downwelling radiation are used as so called "past data".</li> <li>"Product 4 (ANN_ICON) without past data": This column contains the indoor data of PET or air temperature in °C modelled by an artificial neural network using generic data and the meteorological data of air temperature, vapor pressure, mean sea level pressure, global radiation, longwave downwelling radiation, and wind speed derived from the ICON-D2 weather forecast data of the grid cell in which the associated work station is located.</li> <li>"Product 4 (ANN_ICON) with past data": This column contains similar data than the column before but the artificial neural network models used "past data" of the ICON-D2 weather forecast data as additional input variables to model indoor air temperature and PET in °C. Additional to the hourly average of the meteorological data for each actual time (t), hourly averages for t-1 h, t-3 h, t-6 h, t-12 h, and t-24 h of air temperature, global radiation, and Longwave downwelling radiation are used as so called "past data".</li> <li>"Product 5 (ANN_Mixed) without past data": This column contains the indoor data of PET or air temperature in °C modelled by the same artificial neural network models as in Product 3 but applied for the same input data of Product 4.</li> <li>"Product 5 (ANN_Mixed) with past data": This column contains similar data than the column before but also takes into account the "past data".</li> </ul> <p>The data of Product 3 (ANN_AWS) and Product 5 (ANN_Mixed) are only available for locations in Freiburg, because the data of an automated weather station in Freiburg was used.<br> Data which is not available is stated as NA.</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.