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2,170 results for “clouds”
FIGURE 1. The combined 16S in A new species of Isthmura (Caudata: Plethodontidae) from the montane cloud forest of central Veracruz, Mexico
FIGURE 1. The combined 16S and cytb mtDNA gene tree of Aquiloeurycea and Isthmura from maximum likelihood analysis. Numbers above branches correspond to bootstrap proportions, and numbers below branches correspond to posterior probabilities from Bayesian analysis. Branch lengths are in estimated number of substitutions per site.
FIGURE 3 in A new species of Isthmura (Caudata: Plethodontidae) from the montane cloud forest of central Veracruz, Mexico
FIGURE 3. Osteological details of head and teeth detail of paratype of Isthmura corrugata: V= vomerine teeth, M= maxillary teeth and, PM= premaxillary teeth, PS= parasphenoid.
FIGURE 2 in A new species of Isthmura (Caudata: Plethodontidae) from the montane cloud forest of central Veracruz, Mexico
FIGURE 2. Holotype of Isthmura corrugata. A) Lateral and B) Ventral view. C) Coloration and form of costal grooves. D) Left hand (up) and left foot (down). E) Details of the head. F) Dorsal view. (G–H) Holotype (above) and paratype (below) dorsal and ventral coloration in preservation. All photographs by A. Sandoval-Comte.
Model and observational data for Morrison et al. (2020) JAMES paper entitled "Confronting the challenge of modeling cloud and precipitation microphysics"
This dataset was used to generate plots for a paper conditionally accepted in the Journal of Advances in Modeling Earth Systems (JAMES), an AGU journal. It comprises four different data sources: WRF simulations, radar observations, an idealized steady-state column model called the Bayesian Observationally-Constrained Statistical Scheme (BOSS), and idealized column rainshaft model using bin microphysics. The WRF simulations consist of output from a set of 11 runs using either bulk or bin microphysics schemes. The version of WRF is V3.9.1. To limit storage requirements, we have only saved a single time-slice of output at hour 6 of the simulations, along with the namelist.input file to generate these runs. The observational data are gridded and rotated composite NEXRAD reflectivity measurements from central Oklahoma. BOSS model output consists of microphysical parameter probability density functions and profiles of (as described in the meta-file for these data). The idealized bin microphysics rainshaft model output consists of profiles of drop mean size, reflectivity factor, precipitation rate, and drop concentration at two different time slices (described in the meta-data file for these data). We are requesting these data be added to the managed NCAR repository so they may be accessible to the community per AGU publication policy and in accordance with a U.S. DOE grant that partially supported this work.
Queensland Cloud Seeding Research Program (QCSRP) Aircraft Measurements
Research aircraft collected in situ microphysical and aerosol data during the QCSRP over two summer seasons in Queensland, Australia between 2007 and 2009, as described in Tessendorf et al. (2012, BAMS). The files are netcdf and/or .txt formats, and are roughly 3 GB altogether.
On the stepped-leader development of negative cloud-to-ground lightning associated with the evolution of thunderstorm
<p>The files contain the complete radar and lightning datasets of the 12 thunderstorms used in the analysis presented in “On the stepped-leader development of negative cloud-to-ground lightning associated with the evolution of thunderstorms.”</p>
Lung250M-4B: A Combined 3D Dataset for CT- and Point Cloud-Based Intra-Patient Lung Registration
<p>Point Cloud Data from the Lung250M-4B dataset.</p><p>Visit https://github.com/multimodallearning/Lung250M-4B for image data and associated code.</p>
Dataset collected from the observational studies of individual cloud droplet/residual particle
<p>This is the dataset for the review paper titled "Fog/cloud processing of atmospheric aerosols from a single particle perspective: a review of field observations". The dataset is collected from previous studies as cited in Table 1. The dataset mainly includes the sampling sites, droplet sizes, single particle technique used, and the major particle types identified.</p>
Data and codes for figures in "Open water in sea ice causes high bias in polar low-level clouds in GFDL CM4"
Open the record for dataset details and reuse information.
AssemblyNet: A Point Cloud Dataset for Predicting Part Directions in an Exploded Layout
<p>The AssemblyNet dataset contains 5420 samples of 512-point and 1024-point point clouds of mixed industrial assemblies and LEGO models.</p><p>The dataset contains classification and regression annotations for predicting which direction a part should be removed in to create an exploded layout.</p><p>Classification annotations use 26 classes representing 26 world space directions while regression annotations use the actual world space direction as X, Y, and Z values.</p>
Artifact Evaluation for "CSAL: the Next-Gen Local Disks for the Cloud" (EuroSys 2024)
<p>This is for Artifact Evaluation of paper "CSAL: the Next-Gen Local Disks for the Cloud" published in EuroSys 2024.</p>
Figure 5 in Biogeography and evolution of Central American cloud forest salamanders (Caudata: Plethodontidae: Cryptotriton), with the description of a new species
Figure 5. Results of LAGRANGE analysis of geographic range evolution of Cryptotriton. Results for other genera are not shown. Pies at nodes are colored by the relative probability of each geographic range combination, and squares at tips show the areas currently occupied by each species. Each node has a pie representing the range of the ancestor prior to the speciation event and two pies representing the range of each daughter species immediately after the speciation event.
Figure 3 in Biogeography and evolution of Central American cloud forest salamanders (Caudata: Plethodontidae: Cryptotriton), with the description of a new species
Figure 3. Species tree estimate from *BEAST analysis of nuclear loci. Numbers indicate posterior probability of clades.
Figure 2 in Biogeography and evolution of Central American cloud forest salamanders (Caudata: Plethodontidae: Cryptotriton), with the description of a new species
Figure 2. Mitochondrial gene tree from maximum likelihood (ML) analysis of 16S and cytb data. Numbers above branches are bootstrap support values from ML analysis, and numbers below branches are posterior probabilities from Bayesian analysis. Bootstraps below 50 and posterior probabilities below 0.5 are not shown.
Figure 1 in Biogeography and evolution of Central American cloud forest salamanders (Caudata: Plethodontidae: Cryptotriton), with the description of a new species
Figure 1. Map of Nuclear Central America showing the distributions of described species of Cryptotriton, as well as several undescribed populations from Alta Verapaz. Dotted lines separate the three geological regions used in biogeographic analysis: (1) Chiapas highlands of the Maya block, (2) Motagua-Polochic fault zone, and (3) Chortís highlands.
Synthetic Observation of Column Density Maps Derived from Cloud Factory Data via Radiative Transfer Simulations
<p>This dataset contains synthetic observation data derived from Cloud Factory data, processed through radiative transfer simulations using POLARIS. The data focuses on several star-forming regions, providing valuable insights into the evolution of filaments within these areas. The dataset is presented at three different resolutions: high (0.25 pc/pixel), medium (0.5 pc/pixel), and low (1 pc/pixel), to cater to various analytical needs. Files labeled as RA, RB, and RC correspond to three distinct regions under study. Additionally, each file is tagged with a 's' followed by a number, indicating the snapshot sequence. </p>
ACCESS-AM2 daily and hourly cloud and radiation data for model evaluation at Macquarie Island
<p>The ACCESS-AM2 (Australian Community Climate and Earth-System Simulator - Atmospheric Model Version 2) daily and hourly data used for the study described in Pei et al. (2023), accepted in <i>Atmospheric Chemistry and Physics (ACP),</i> 'Assessing the cloud radiative bias at Macquarie Island in the ACCESS-AM2 model<i>' .</i> </p><p>Included files: </p><ul><li>ACCESS_AM2_daily.zip - daily model outputs from 2016-04 to 2018-03</li><li>ACCESS_AM2_hourly.zip - hourly model outputs from 2017-09 to 2018-02</li></ul><p>The code that performs the analysis/generates this data can be found here: https://github.com/ZhangchengPei/codes-for-MI-paper</p>
FIGURE 4 in Three new species of Epidendrum (Orchidaceae: Laeliinae) from the cloud forests of Chota, northern Peru
FIGURE 4. Lankester Composite Dissection Plate (LCDP) of Epidendrum bicornialpicola Hágsater, Chamaya & Iberico. A. Plant habit. B. Inflorescence. C. Flower, lateral view. D. Dissected perianth. E. Ovary with lip and column; upper and lateral views. F. Pollinarium. Prepared by Anaís Cisneros from the images by J. A. Chamaya taken from the specimen that served as the holotype.
FIGURE 3 in Three new species of Epidendrum (Orchidaceae: Laeliinae) from the cloud forests of Chota, northern Peru
FIGURE 3. Lankester Composite Dissection Plate (LCDP) of Epidendrum retrolobatum Hágsater, Chamaya, J.Duarte & Iberico. A. Plant habit. B. Inflorescence. C. Flower, lateral view. D. Dissected perianth. E. Lip in natural position. F. Lateral lobe of lip spread. G. Ovary and column lateral view. H. Ovary and longitudinal section of column. I. Anther cap (top view and underside) and pollinarium. Prepared by Anaís Cisneros from the images by J. A. Chamaya taken from the specimen that served as the holotype.
FIGURE 2 in Three new species of Epidendrum (Orchidaceae: Laeliinae) from the cloud forests of Chota, northern Peru
FIGURE 2. Lankester Composite Dissection Plate (LCDP) of Epidendrum acuntasiorum Hágsater, Chamaya, J.Duarte & Iberico. A. Plant habit. B. Inflorescence. C. Flower, lateral view. D. Dissected perianth. E. Ovary. F. Column, ventral view. G. Anther cap and pollinarium. Prepared by Anaís Cisneros from the images by J. A. Chamaya taken from the specimen that served as the holotype.
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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.