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2,170 results for “clouds”
Data for: Bulk microphysics schemes may perform better with a unified cloud-rain category
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Data from: Mapping coastal redwoods (<em>Sequoia sempervirens</em>) across their natural range: An updateable and field-validated distribution map using Sentinel satellite data and cloud computing
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Seasonal rainfall in subtropical montane cloud forests drives demographic fluctuations in a Green-backed Tit population
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Data for: Using spatial patterns of seeds and saplings to assess the prevalence of heterospecific replacements among cloud forest canopy tree species
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Data for: Multi-campaign ship and aircraft observations of marine cloud condensation nuclei, and droplet concentrations
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Using optical flow temporal interpolation of satellite imagery to assist multi-sensor global cloud product composites
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Data from: Effects of immune status on stopover departure decisions are subordinate to those of condition, cloud cover and tailwind in autumn-migrating common blackbirds (Turdus merula)
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Detection of standing retention trees in boreal forests with airborne laser scanning point clouds and multispectral imagery
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Data from: Assisted migration of cloud forest trees: Unearthing the effects of climatic transfer distance
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Global overview of cloud-, snow-, and shade-free Landsat (1982-2024) and Sentinel-2 (2015-2024) data
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Supplementary data for: Nowcasting 3D cloud fields using forward warping optical flow
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Wayqecha Amazon cloud curtain ecosystem experiment: Climate data and R processing code
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Cloud_ICA: A deterministic cloud-overlap algorithm for generating a complete set of independent column atmospheres
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An updated cloud-overlap photolysis module for atmospheric chemistry models, UCI Cloud-J v8.0, with near-UV H2O absorption
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A Simple Semantic-based Data Storage Layout for Querying Point Clouds
<p>Dataset contains three datasets: SMALL, MEDIUM and LARGE point cloud.</p> <p>Contains Python code which is made up of two files pc_new_semantics.py and paperutils.py</p> <p> </p>
AMIP and AMIP-P4K simulation dataset with Park-RH and Gauss-PDF cloud scheme
<p>This dataset includes AMIP and AMIP-P4K simulations using Park-RH and Gauss-PDF cloud schemes, respectively. </p> <p>Park-RH cloud scheme is the default cloud macrophysical scheme in NCAR CAM5. </p> <p>Gauss-PDF cloud scheme is a statistical cloud scheme, developed by Qin et al. (2018). </p> <p>All simulations are AMIP-type simulations from 1979 to 1988. The monthly output is archived here. </p> <p>Details of the model setup and the difference of two cloud schemes could be found in its related submitted manuscript. </p>
Data of the paper: Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems
<p>Here you can find the data presented in the paper: <strong>Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems</strong></p> <p>The data include all variables included in the paper for the shallow-cloud and the deep-cloud dominated cases.</p> <p>The variable names are as in the paper (beside T_tot which is the 2m temperature). The numbers in the names of the variables represent the CDNC case.</p> <p>The time series variables are as a function of t. The vertical profiles are as a function of the pressure p. The maps are as a function of latitude and longitude. </p>
Data of the paper: Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions
<p>Data of the paper: Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions</p> <p> </p> <p>The name of variable are as in the paper</p>
Dataset S1 of "A long-lived sharp disruption on the lower clouds of Venus"
<p><strong>Simulation with the IPSL Venus GCM.</strong> This compressed zip file accompanying the article "A long-lived sharp disruption on the lower clouds of Venus" (DOI: 10.1029/2020GL087221) holds a NetCDF file with a README file describing its structure. The NetCDF file contains the IPSL GCM simulation of the Venus atmosphere for the case of a relaxed zonal wind profile (see subsection 2.4 in main article). Computations were performed on a grid of <span class="math-tex">\(altitude\times latitude\times longitude\)</span> with <span class="math-tex">\(50\times 97\times 96\)</span> elements and along 40 time steps covering 23 Earth days.</p> <p>Calculated physical parameters include:</p> <ol> <li>Atmospheric pressure (Pa).</li> <li>Vertical Wind (m s<sup>-1</sup>) [positive downward].</li> <li>Air Temperature (K).</li> <li>Zonal Wind (m s<sup>-1</sup>) [positive westward].</li> <li>Solar radiance at top of the atmosphere (W m<sup>-2</sup>).</li> </ol>
Pangeo Cloud Storage Read Throughput Benchmarks
<p>These are the results of benchmarking distributed reads from various cloud storage services and data formats. All tests were performed from the Google cloud US-CENTRAL1 region.</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.