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10,016 results for “Observation”
Observed and deweathered source concentrations of black carbon (BC) in Tianjin, China in 2017-2020
<p>This dataset contains 1) the output of a Dispersion Normalized Positive Matrix Factorization (DN-PMF) modeling of a long-term BC dataset measured in Tianjin, China, and 2) the deweathered source contributions of the six identified BC sources. </p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-11]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier / NGC / IC / Barnard catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS), Benoît Vandame (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p>
Synchronous observation of aerosol at Mt. Hua
<p>The filed observations were synchronously conducted at mountainside and mountain foot sampling sites of Mt. Hua during the period from 27 August to 17 September 2016. And we found that nitrate and ammonium exhibited distinct physicochemical behaviors in transport process. The dataset includes meteorological data and hourly PM<sub>2.5</sub>, NO<sub>2</sub> and O<sub>3</sub> mass concentrations.</p>
Four-dimensional wind fields retrieved from FY4B GIIRS during 15-minute interval intensified observations from 24 to 26 June 2022
<p>This dataset is the four-dimensional (time, pressure, u, v) wind fields retrieved from FY4B GIIRS observations with a 15-minute interval during a northeastern cold vortex event in China.</p>
Four-dimensional wind fields retrieved from FY4A GIIRS during 30-minute interval intensified observations on typhoons Ampil (2018), Mangkhut(2018) and Lekima(2019)
<p>This dataset includes the four-dimensional (time, pressure, u, v) wind fields retrieved from FY4A GIIRS with 30-minute interval during Ampil (2018), Mangkhut(2018) and Lekima(2019).</p>
RInex files from HK GNSS network in observing simultaneous and consecutive occurrence of thunderstorm and geomagnetic storm
<p>These are the RInex files from HK GNSS network in observing simultaneous and consecutive occurrence of thunderstorm and geomagnetic storm</p>
Data records for PdpP phases observed from Fiji-Tonga earthquakes
<p>This data file presents the observations for 21 Fiji-Tonga earthquakes (events 1-21) with high-quality PdpP signals and 5 Fiji-Tonga earthquakes (events 33-37) without PdpP signals. It includes the vertical-component recordings in sub-arrays from China National seismic Network (CNSN) and the corresponding 4-th root vespagrams generated in each sub-array.</p>
Observations of Autumnal Cooling in a Large Estuary: The Glider Data from Long Island Sound in 2014
<p>This data file is a component of the data used in a paper to appear in the Journal of Geophysical Research in 2023 entitled "Observations of Autumnal Cooling in a Large Estuary" by Amin Ilia, Grant McCardell, Kay Howard-Strobel, and James O'Donnell. The data file contains the measurements from a Slocum Glider (V1) from Webb Research used in the paper. The data is in a MATLAB binary (.mat) file as a structure variable with a field MetaData containing some notes, and data in <br> SampleTimeEST- the date and time of the sample (EST) in MATLAB's datenum() format<br> Pressure_dBar - the pressure (or equivalently depth in m) that the sample was acquired <br> Temperature_C - the water temperature in Celcius<br> PracticalSalinty - the practical salinity<br> LatitudeDeg- the latitude of the sampling location (deg)<br> LongitudeDeg - the longitude of the sampling location (deg east)</p> <p>The paper's abstract is: </p> <p>Seasonal variations in solar insolation and wind create an annual water temperature cycle that impacts circulation and biological processes. The waters of Long Island Sound (LIS) warm from March-February until August-October and then begin to cool. Ship surveys show that the vertical temperature structure becomes almost uniform during this season when the area experiences low air temperatures and high winds. However, no observations have resolved the temporal evolution of the vertical structure of temperature during these cooling periods because conditions inhibit ship operations. We report glider measurements of the vertical structure of water temperatures and salinities from October 22 to November 4, 2014, in eastern LIS. We find that 20m of water can cool at approximately 0.5 C/day during intervals of cold air and strong winds. We use the data to estimate heat content tendencies and infer surface fluxes. We also estimate the surface heat fluxes using buoy-mounted instruments and show they are consistent. The net heat flux to the atmosphere exceeds 600 W/m<sup>2</sup> during the gilder deployment and approximately 66% of this is due to latent heat transfer. Using the buoy fluxes and products of an operation regional model, we show that the agreement with the fluxes derived from heat budget is improved by using local wind observations. In addition to confirming the extremely large cooling rates, our results demonstrate that gliders can be used in a complex region with strong tidal currents to resolve the temperature structure and heat budget during the severe weather of the cooling season.</p> <p> </p>
Experimental and observation data used for the paper entitled "Method to constrain the complex refractive index of ambient black carbon aerosol from their observed distribution of the complex forward-scattering amplitude"
<p>The complex forward-scattering amplitude data used for Figure 6 and 7 of the paper entitled "Method to constrain the complex refractive index of ambient black carbon aerosol from their observed distribution of the complex forward-scattering amplitude" by N. Moteki et al.</p>
STROBE checklist for: Serum soluble angiotensin-converting enzyme 2 level and its potential association with the renin-angiotensin-aldosterone system in non-hypertensive covid-19 patients: an observational study
<p>Serum soluble angiotensin-converting enzyme 2 level and its potential association with the renin-angiotensin-aldosterone system in non-hypertensive covid-19 patients: an observational study</p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-12]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier / NGC / IC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS), Benoît Vandame (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p> <p> </p>
The observed and simulated datasets of "21·7" Henan extremely heavy rainfall event
<p>The uploaded files are the observed and simulated datasets of “21·7” Henan extremely heavy rainfall event, including OTT disdrometers, Radar, national and regional gauges, and WRFOUT files. </p>
The Effects of Aerosol on Small-Scale Cloud-Environment Mixing: Implications for Observing Inhomogeneous Mixing
<p>This is the simulation output of the submitted manuscript "The Effects of Aerosol on Small-Scale Cloud-Environment Mixing: Implications for Observing Inhomogeneous Mixing" to the Journal of Geophysical Research: Atmospheres. </p> <p>Abstract: The mixing of clouds with their environment can change the size and number of cloud droplets, two important parameters to understand the role of clouds in the climate system. Because these changes are determined by the way a cloud mixes with its environment, they have been used to characterize the mixing process. Using a highly detailed numerical cloud model coupled with a statistical turbulence model, we show that the adequate consideration of aerosol particles from which cloud droplets grow, can alter the changes of cloud droplets during mixing. This has not been considered in the past. We identify biases that need to be considered when mixing processes are analyzed.</p> <p>The raw data presented here was produced by the aforementioned model only and is completely available.</p>
Camera traps and guard observations as an alternative to researcher observation for studying anthropogenic foraging
<p>Foraging by wildlife on anthropogenic foods can have negative impacts on both humans and wildlife. Addressing this issue requires reliable data on the patterns of anthropogenic foraging by wild animals, but while direct observation by researchers can be highly accurate, this method is also costly and labour-intensive, making it impractical in the long- term or over large spatial areas. Camera traps and observations by guards employed to deter animals from fields could be efficient alternative methods of data collection for understanding patterns of foraging by wildlife in crop fields. Here we investigated how data on crop-foraging by chacma baboons and vervet monkeys collected by camera traps and crop guards predicted data collected by researchers, on a commercial farm in South Africa. We found that data from camera traps and field guard observations predicted crop loss and the frequency of crop-foraging events from researcher observations for crop-foraging by baboons and to a lesser extent for vervets. The effectiveness of cameras at capturing crop-foraging events was dependent on their position on the field edge. We believe that these alternatives to direct observation by researchers represent an efficient and low-cost method for long-term and large-scale monitoring of foraging by wildlife on crops. </p>
Dataset - Observation of photon-photon thermodynamic processes under negative optical temperature conditions
<p>Experimental data and simulation results associated with the article: Observation of photon-photon thermodynamic processes under negative optical temperature conditions</p>
Funka Bay observation bottle data (Nutrients, chlorophyll-a, and oxygen) from February to April of 2019
<p>Bottle data of Nutrients, chlorophyll-a, and oxygen in seawater collected from the Funka Bay, Hokkaido, Japan, from February to April of 2019. Methods are presented in Umezawa et al., Significant nutrient consumption in the dark subsurface layer during a diatom bloom: a case study on Funka Bay, Hokkaido, Japan, Biogeosciences, 2023.</p>
Data for: Torii et al.,Observed Kinetics of Enterovirus Inactivation by Free Chlorine Are Host Cell-Dependent, Environmental Science and Technology, 10.1021/acs.est.2c07048
<p>This folder contains the experimental data to the figures shown in the main manuscript and Supporting Information.</p> <p>- Figure 1 (Inactivation curves for E11 by free chlorine, UV, and heat)</p> <p>- Figure 2 (Inactivation curves for CVA9, CVB1, E7, E9, and E13)</p> <p>- Figure S1 (Loss of attachment and the PCR-target by free chlorine treatment)</p> <p>- Figure S2 (Flow cytometric analysis)</p> <p> </p> <p> </p> <p> </p>
Dataset for publication: The Land-Atmosphere Feedback Observatory: A New Observational Approach for Characterizing Land-Atmosphere Feedback
<p>Here are zip files containing the data sets for the figures of the publication "The Land-Atmosphere Feedback Observatory: A New Observational Approach for Characterizing Land-Atmosphere Feedback" by Späth et al., 2023, GI, doi: 10.5194/gi-12-25-2023.</p><p>Data collected from the Halo Doppler lidar (DL), Atmospheric Raman Temperature and HUmidity Sounder ARTHUS, scanning differential absorption lidar (DIAL), Eddy-Covariance stations (EC) and the Water and Temperature Sensor Network (WaTSeN) of the Land-Atmisphere Feedback Observatory LAFO at University of Hohenheim, Stuttgart, Germany. The data cover the temporal period as presented in the figures in Späth et al., 2023, GI, doi: 10.5194/gi-12-25-2023.</p>
Variability of Atmospheric CO2 Over the Arctic Ocean: Insights From the O-Buoy Chemical Observing Network
<p>This dataset contains relevant files for the GEOS-Chem chemical transport model simulations used in the following manuscript: Graham, K. A., Friedrich, G., Rauschenberg, C. D., Williams, C. R., Bottenheim, J. W., Chavez, F. P., Halfacre, J. W., Holmes, C. D., Perovich, D. K., Shepson, P. B., Simpson, W. R., Tans, P. P., & Matrai, P. A. (2022). Variability of Atmospheric CO<sub>2</sub> Over the Arctic Ocean. <em>Journal of Geophysical Research: Atmospheres</em>. In Review.</p>
Lidar and model data for manuscript submitted to GRL "First Simultaneous Observation of Secondary and Tertiary Gravity Waves by Lidar and Investigation with HIAMCM simulations"
<p>This dataset contains the lidar and model data used in the manuscript submitted GRL titlled '<strong>First Simultaneous Observation of Secondary and Tertiary Gravity Waves by Lidar and Investigation with HIAMCM simulations'</strong></p>
ScienceDex guides
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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.