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Dataset results
11 results for “generators of atmosphere”
Data archive for "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network"
<p>This datasets supports the paper "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network" submitted to IEEE Transactions in Geoscience and Remote Sensing. A preprint of the paper can be found here: <a href="https://arxiv.org/abs/2005.10374">https://arxiv.org/abs/2005.10374</a>. The code that uses these data is available at <a href="https://github.com/jleinonen/downscaling-rnn-gan">https://github.com/jleinonen/downscaling-rnn-gan</a>.</p> <p>The file "goes-samples-2019-128x128.nc" contains the training dataset called "GOES-COT" in the paper, consisting of cloud optical depth measurements from the GOES-16 satellite. The files "gen_weights*.nc" contain the generator weights saved at different time steps during training for the two different datasets described in the paper.<br> </p>
Generative convective parametrization of a dry atmospheric boundary layer
<p>The repository contains simulation snapshots of a dry convective boundary layer (CBL). The snapshots comprise horizontal snapshots of vertical velocity (w) and buoyancy (b) field at three heights, namely z/h(t) = 0.2, 0.5, 1.0. Further, the Python scripts for the Generative Adversarial Network (GAN) are also provided, as well as the DNS renormalization procedure.</p>
Generators of Architectural Atmosphere Symposium
<p>This dataset is an output of the ‘Generators of Architectural Atmosphere’ Symposium, an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the 2020 Regnier Chair. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on April 12, 2022. Speakers: Bob Condia (Kansas State University), Elisabetta Canepa (University of Genoa and Kansas State University), Kutay Güler (Kansas State University), and Tiziana Proietti (Oklahoma University).</p> <p><br> Recent advances in science confirm many of the architect’s expert intuitions opening new doors to the perception of space and the meaning of architectural and urban design. The symposium ‘Generators of Architectural Atmosphere’ presented to an audience of students, educators, architects, and scientists a conversation about human perception of design and building, specifically speaking to the significance of atmosphere, mood, architectural proportion, and virtual reality.</p> <p><br> This dataset is made of six files:<br> no. 1 dataset summary (.pdf)<br> no. 1 symposium poster (.pdf)<br> no. 4 videos containing speakers’ presentations (.mp4).</p> <p><br> Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (UCk32skDiT4Bz1AHnltT51Yg).</p>
Cloud_ICA: A deterministic cloud-overlap algorithm for generating a complete set of independent column atmospheres
<p>In calculating solar radiation, climate models make many simplifications, in part to reduce computational cost and enable climate modeling, and in part from lack of understanding of critical atmospheric information. Whether known errors or unknown errors, the community's concern is how these could impact the modeled climate. The simplifications are well known and most have published studies evaluating them, but with individual studies it is difficult to compare. Here, we collect a wide range of such simplifications in either radiative transfer modeling or atmospheric conditions and assess potential errors within a consistent framework on climate‐relevant scales. We build benchmarking capability around a solar heating code (Solar‐J) that doubles as a photolysis code for chemistry and can be readily adapted to consider other errors and uncertainties. The broad classes here include: use of broad wavelength bands to integrate over spectral features; scattering approximations that alter phase function and optical depths for clouds and gases; uncertainty in ice‐cloud optics; treatment of fractional cloud cover including overlap; and variability of ocean surface albedo. We geographically map the errors in W m−2 using a full climate re‐creation for January 2015 from a weather forecasting model. For many approximations assessed here, mean errors are ∼2 W m−2 with greater latitudinal biases and are likely to affect a model's ability to match the current climate state. Combining this work with previous studies, we make priority recommendations for fixing these simplifications based on both the magnitude of error and the ease or computational cost of the fix.</p>
Cloud_ICA: A deterministic cloud-overlap algorithm for generating a complete set of independent column atmospheres
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Data from: Upper atmosphere heating from ocean-generated acoustic wave energy
Colliding sea surface waves generate the ocean microbarom, an acoustic signal that may transmit significant energy to the upper atmosphere. Previous estimates of acoustic energy flux from the ocean microbarom and mountain/wind interactions are on the order of 0.01 to 1 mW/m2, heating the thermosphere by tens of degrees Kelvin per day. We captured up going ocean microbarom waves with a balloon borne infrasound microphone; the maximum acoustic energy flux was approximately 0.05 mW/m2. This is about half the average value reported in previous ground-based microbarom observations spanning eight years. The acoustic flux from the microbarom episode described here may have heated the thermosphere by several degrees Kelvin per day while the source persisted. We suggest that ocean wave models could be used to parameterize acoustically-generated heating of the upper atmosphere based on sea state.
Code and data for Porting the Meso-NH Atmospheric Model on Different GPU Architectures for the Next Generation of Supercomputers (version MESONH-v55-OpenACC)
<p>GeometricMG.pdf (source: https://bitbucket.org/em459/tensorproductmultigrid/src/master/Documentation/)<br>MESONH_Bench_HECTOR_ADASTRA_LEONARDO.tar.gz: code and data for Meso-NH bench<br>Performance.zip: code and data for figures related to performance<br>WeatherApplications.zip: namelists for running weather applications<br>OASIS3_WW3.tar.gz: OASIS and WW3 codes for running the Meso-NH WWW3 coupled simulation</p>
Supporting data for Assessing clouds using satellite observations through three generations of global atmosphere models
<p>Monthly data from CAM4, CAM5, and CAM6 that are needed to reproduce the analysis and figures in the manuscript entitled: Assessing clouds using satellite observations through three generations of global atmosphere models by Brian Medeiros, Jonah Shaw, Jennifer Kay, and Isaac Davis.</p>
Data from: Upper atmosphere heating from ocean-generated acoustic wave energy
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Numerical simulation "Numerical simulation of atmospheric Lamb waves generated by the 2022 Hunga-Tonga volcanic eruption"
<p>Numerical simulation results for the atmospheric Lamb waves generated by the Hunga-Tonga volcano explosion on January 15th 2022.</p>
Quarterly and Annual Efficiency, Reliability, and Resilience of Atmospheric Water Generators
<p>These data support the article, "Benchmarks of Production for Atmospheric Water Generators in the United States," by Sadowski et al. in PLOS Water.</p>
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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.