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81 results for “In situ observations”
Damage Localisation in Fresh Cement Mortar Observed via In Situ (Timelapse) X-ray uCT imaging.
<p>This is dataset to paper: Damage Localisation in Fresh Cement Mortar Observed via In Situ (Timelapse) X-ray uCT imaging.</p>
Structure matters – Direct in-situ observation of cluster nucleation at atomic scale in a liquid phase (supplementary data)
<p>This a dataset of scanning transmission electron microscopy data showing Pt clusters nucleating in an ionic liquid. For each of the 4 movies there is the raw data (uncompressed .tif and compressed as .avi) and denoised versions (uncompressed .tif and compressed as .avi).</p> <p>This data is for the article "Structure matters – Direct in-situ observation of cluster nucleation at atomic scale in a liquid phase" published in ChemNanoMat (2020), by Trond R. Henninen, Debora Keller and Rolf Erni. (https://onlinelibrary.wiley.com/doi/full/10.1002/cnma.202000503)</p> <p><strong>Movie 1:</strong> Homogeneous nucleations of two clusters in a suspended thin film of ionic liquid. </p> <p><strong>Movie 2: </strong>Heterogeneous nucleation of a ca 8-9 atom cluster near the edge of a nanodroplet supported on a carbon film.</p> <p><strong>Movie 3: </strong>Heterogeneous nucleation of multiple clusters in a nanodroplet. Shortly after nucleation, they coalesce to form disordered nanoclusters.</p> <p><strong>Movie 4:</strong> Heterogeneous nucleation and dissolution cycles of spherical particles in a nanodroplet.</p>
In situ observations of Ganymede's outflowing ionosphere
<p>The file contains values for ionospheric moments from the Juno flyby of Ganymede on 7 June 2021, during the period between 16:50 to 17:00, UTC. A description of the flyby and the data set is found in Valek et al. (2022), <em>In situ ion composition observations of the Ganynmede's outflowing ionosphere</em>, GRL DOI:10.1029/2022GL100281.</p>
Data for the publication "Retrieving ice-nucleating particle concentration and ice multiplication factors using active remote sensing validated by in situ observations"
<p>This repository contains the data for the paper:</p> <p>Wieder, J., Ihn, N., Mignani, C., Haarig, M., Bühl, J., Seifert, P., Engelmann, R., Ramelli, F., Kanji, Z. A., Lohmann, U., and Henneberger, J.: Retrieving ice nucleating particle concentration and ice multiplication factors using active remote sensing validated by in situ observations, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-67, in review, 2022.</p> <p>More information can be found in the README files.</p> <p>Note that the scripts to reproduce the figures of the publication are available on request.</p>
Neural Network and objective analysis reconstruction of 3D Mediterranean physical fields from surface satellite and in situ observations at 1/24 deg
<p>Daily Mediterranean 3D fields of temperature, salinity and geostrophic current at 1/24° of resolution, up to 150m-depth and from 2016 to mid 2022, obtained through a 3 steps approach: (1) Temperature and salinity 3D fields have been first estimated by a machine learning approach by using mediterranean reanalysis outputs (https://doi.org/10.25423/CMCC/MEDSEA_MULTIYEAR_PHY_006_004_E3R) together with satellite observations, (2) a combination of this first step with in situ observations through an Optimal interpolation to remove part of large scale biases, (3) the computation of geostrophic currents using the thermal wind equation. This work has been funded by the European Space Agency through the 4DMED-SEA project [ESA contract No. 4000141547/23/I-DT].</p>
First In-Situ Measurements of Travelling Ionospheric Disturbances at 420 km Altitude by the Scintillation Observations and Response of The Ionosphere to Electrodynamics (SORTIE) CubeSat
<p>Companion dataset to the paper entitled "First In-Situ Measurements of Travelling Ionospheric Disturbances at 420 km Altitude by the Scintillation Observations and Response of The Ionosphere to Electrodynamics (SORTIE) CubeSat". The dataset includes the SORTIE CubeSat IVM Level 2 ion density and GPS TEC data used in the study along with the WRF simulation results.</p>
GIS Shapefiles for In Situ Geologic Map based on PMars 2020 Perseverance Rover Observations
<p>These are shapefiles for in situ geologic maps illustrated in Crumpler et al., 2023. n Situ Geologic Context Mapping Transect on the Floor of Jezero Crater from Mars 2020 Perseverance Rover Observations. Journal of Geophysical Research-Planets, Mars 2020 Results Special Collection</p>
Data: Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in situ observations and climate models
<p>These data accompany the publication "Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in situ observations and climate models". The data are organized as follows:</p> <p>- two files with time series (csv) of hourly near-surface climate and surface energy balance values for Neumayer station (ice shelf, East Antarctic ice sheet) and automatic weather station S5 (southwest Greenland ice sheet)</p> <p>- two files (nc) with monthly melt fields from the regional climate model RACMO2.3p2 forced by ERA5 over Greenland (0.05-degree resolution) and Antarctica (0.25-degree resolution)</p> <p>- two files (nc) with annual melt fields from the regional climate model RACMO2.3p2 forced by CESM2 over Greenland (0.1-degree resolution) and Antarctica (0.25-degree resolution) or the historical period (1950-2014)</p> <p>- two files (nc) with annual melt fields from the regional climate model RACMO2.3p2 forced by CESM2 over Greenland (0.1-degree resolution) and Antarctica (0.25-degree resolution) for the future emission scenario SSP5-8.5 (2015-2099)</p>
Supplementary Information for Coverage of in situ climatological observations in the world's mountains (Thornton et al.)
<p>Supplementary Information for "Coverage of in situ climatological observations in the world's mountains" (Thornton et al., Frontiers in Climate).</p>
Fig. 6. Ectoparasite-host interactions for A in Ectoparasitism on deep-sea fishes in the western North Atlantic: In situ observations from ROV surveys
Fig. 6. Ectoparasite-host interactions for A) Antimora rostrata, B) Nezumia bairdii, and C) Synaphobranchus spp. across the region for which the presence or absence of ectoparasites could be confirmed. Circle Size = Number of confirmed ectoparasite-host interactions 10 m —2. Square = No ectoparasites observed. Colors denote habitats.
Fig. 2 in Ectoparasitism on deep-sea fishes in the western North Atlantic: In situ observations from ROV surveys
Fig. 2. Example images of ectoparasites infecting various host species. A) Antimora rostrata with a lernaeopodid copepod (1059 m, Alvin Canyon); B) Synaphobranchus sp. with a sphyriid copepod (820 m, open slope); C) Nezumia bairdii with a sphyriid copepod parasitized by eight leeches (1035 m, Phoenix Canyon; D), Black fish, Diaphus sp. with an unknown siphonostomatid copepod (1130 m, cold seep) attached behind dorsal fin; E) N. bairdii with aegid isopod (780 m, open slope); F) Hoplostethus mediterraneus with a cymothoid isopod (744 m, Nygren Canyon); G) Amblyraja radiata with aegid isopod (1010 m, Alvin Canyon); and H) Cottunculus thomsonii with gnathiids (1210 m, Oceanographer Canyon).
Fig. 3 in Ectoparasitism on deep-sea fishes in the western North Atlantic: In situ observations from ROV surveys
Fig. 3. Percentage of ectoparasites infecting three common demersal fishes. Unconfirmed observations are not included.
Fig. 1 in Ectoparasitism on deep-sea fishes in the western North Atlantic: In situ observations from ROV surveys
Fig. 1. Locations of 43 ROV dives conducted along the northeastern U.S. continental margin and New England Seamount Chain. Circle Size = Number of ectoparasite-host interactions per dive. Square = No ectoparasites observed. Colors denote habitats.
Fig. 5 in Ectoparasitism on deep-sea fishes in the western North Atlantic: In situ observations from ROV surveys
Fig. 5. Mean abundance (±SE) of A) Antimora rostrata, B) Nezumia bairdii, and C) Synaphobranchus spp. per habitat (black bars). Mean abundance (±SE) of ectoparasitehost interactions (grey bars) is also included. n = number of dives during which the species was present.
Fig. 4 in Ectoparasitism on deep-sea fishes in the western North Atlantic: In situ observations from ROV surveys
Fig. 4. Mean abundance (±SE) of A) Antimora rostrata, B) Nezumia bairdii, and C) Synaphobranchus spp. per depth zone (black bars). Mean abundance (±SE) of ectoparasite-host interactions (grey bars) also included. n = number of dives during which the species was present.
EOMORES earth observation and in situ data of water quality in lakes and coastal areas - year 1
<p>EOMORES is a European innovation project aiming to develop commercial services for monitoring the quality of inland and coastal water bodies, using data from Earth Observation (EO) satellites and in situ sensors to measure, model and forecast water quality parameters.</p> <p>The current data set is a sample of the data generated within the first project year (2017), and consists of Earth Observation (EO) data and in situ data from lakes and coastal areas. For full data sets, please contact the respective contact point listed for each area.<br> Data sets of the second (2018) and third (2019) year of EOMORES will also be submitted.</p> <p>The following is included:<br> - Estonia lakes and coast: in situ data 2017<br> - Finland: links to repositories of EO data<br> - Italy Trasimeno: sample of EO data 2017<br> - Lithuania Curonian Lagoon: sample of EO data 2017<br> - Netherlands Lake Markermeer: sample of EO data 2017<br> - Netherlands Lake Paterswoldsemeer: EO data 2015, 2016, 2017<br> - UK Scotland: in situ data Loch Leven and Loch Lomond 2017<br> - UK WCO Sentinel2A match ups: Western Channel Observatory match ups with Sentinel-2 satellite 2016, 2017</p> <p>http://eomores-h2020.eu</p>
In-Situ Aircraft Observations from North China on May 22, 2017 for AAS
<p>dataset for <span>Airborne Investigation of Riming: Cloud and Precipitation Microphysics Within a Weak Convective System in North China</span></p>
Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations
<p>A reliable determination of equivalent black carbon (eBC) mass concentrations derived from filter absorption photometers (FAPs) measurements depends on the appropriate quantification of the mass absorption cross-section (MAC) for converting the absorption coefficient (babs) to eBC. This study investigates the spatial–temporal variability of the MAC obtained from simultaneous elemental carbon (EC) and babs measurements performed at 22 sites. We compared different methodologies for retrieving eBC integrating different options for calculating MAC including: locally derived, median value calculated from 22 sites, and site-specific rolling MAC. The eBC concentrations that underwent correction using these methods were identified as LeBC (local MAC), MeBC (median MAC), and ReBC (Rolling MAC) respectively. Pronounced differences (up to more than 50 %) were observed between eBC as directly provided by FAPs (NeBC; Nominal instrumental MAC) and ReBC due to the differences observed between the experimental and nominal MAC values. The median MAC was 7.8 ± 3.4 m2 g-1 from 12 aethalometers at 880 nm, and 10.6 ± 4.7 m2 g-1 from 10 MAAPs at 637 nm. The experimental MAC showed significant site and seasonal dependencies, with heterogeneous patterns between summer and winter in different regions. In addition, long-term trend analysis revealed statistically significant (s.s.) decreasing trends in EC. Interestingly, we showed that the corresponding corrected eBC trends are not independent of the way eBC is calculated due to the variability of MAC. NeBC and EC decreasing trends were consistent at sites with no significant trend in experimental MAC. Conversely, where MAC showed s.s. trend, the NeBC and EC trends were not consistent while ReBC concentration followed the same pattern as EC. These results underscore the importance of accounting for MAC variations when deriving eBC measurements from FAPs and emphasize the necessity of incorporating EC observations to constrain the uncertainty associated with eBC.</p>
Processed data used for JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations"
<p>This is the processed dataset used in the JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations" by Xiao Ge.</p> <p>Please contact the author (gexiao@tamu.edu) for all the original/processed outputs of R-CESM, and use the following original papers as citations.</p> <p>The dataset used in this research includes:</p> <p>1. Loop Current Dynamics 2009-2011: LC_*.nc is the processed (reorganized) data for each in-situ station, * represents their station ID</p> <ul> <li>https://digital.library.unt.edu/ark:/67531/metadc955416/</li> <li>https://www.sciencedirect.com/science/article/pii/S0377026516301348?via%3Dihub</li> <li>https://search.dataone.org/view/%7BBD2513E6-3B34-4B7C-BCB9-3C4ED5E8D0FB%7D</li> </ul> <p>2. Regional Community Earth System Model, R-CESM: <a href="https://zenodo.org/api/records/13932074/draft/files/h.nc/content" target="_blank" rel="noopener noreferrer">h.nc</a> is the bathymetry data of R-CESM; cmpr_*.nc files are provided as examples of the original R-CESM outputs; pvsf_prho_*.nc are the processed (subsampled at the target region and interpolated on potential density layers, derived stream function, potential vorticity, and relative vorticity) R-CESM outputs used in this research; and <a href="https://zenodo.org/uploads/13932074" target="_blank" rel="noopener noreferrer">LC_pv_40hlp_2013.nc</a> is the example of organized processed R-CESM (pvsf_prho_*.nc files) containing potential vorticity and relative vorticity for figures plotting</p> <ul> <li>https://journals.ametsoc.org/view/journals/bams/102/9/BAMS-D-20-0024.1.xml?tab_body=fulltext-display</li> </ul> <p> </p> <p> </p> <p> </p> <p> </p>
FIGURE 7 in In situ Observations of the Meso-Bathypelagic Scyphozoan, Deepstaria enigmatica (Semaeostomeae: Ulmaridae)
FIGURE 7. Two lithodid crabs (Paralomis sp.) crabs and several caridean shrimp species surrounding carcass of Deepstaria sp. (at left and below). At right (opposite page) a close-up of one crab feeding on the carcass shows the meshwork of the jelly's gastrovascular system.
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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.