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1,574 results for “atmospheres”

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zenodo36/100

Global Catastrophic Effects on Future Climate due to Increasing Total Solar Irradiance. A General Atmospheric Circulation Analysis.

<p>10-yr CESM run with standard TSI (BGCN_T31_g37.cam.h0*)</p> <p>10-yr CESM run with TSI +10% (BGCN_T31_g37_TSI10p.cam.h0*)</p>

opencc-by-4.0Dec 2017View details →
zenodo36/100

Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study

<p>Atmospheric chemistry transport models (ACTMs) are widely used to underpin policy decisions associated with the impact of potential changes in emissions on future pollutant concentrations and deposition. It is therefore essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input pollutant emissions. ACTMs incorporate complex and non-linear descriptions of chemical and physical processes which means that interactions and non-linearities in input&ndash;output relationships may not be revealed through the local one-at-a-time sensitivity analysis typically used. The aim of this work is to demonstrate a global sensitivity and uncertainty analysis approach for an ACTM, using as an example the FRAME model, which is extensively employed in the UK to generate source-receptor matrices for the UK Integrated Assessment Model and to estimate critical load exceedances. An optimised Latin hypercube sampling design was used to construct model runs within &plusmn;&nbsp;40&nbsp;% variation range for the UK emissions of SO<sub>2</sub>, NO<sub>x</sub> and NH<sub>3</sub>, from which regression coefficients for each input-output combination and each model grid (&gt;10,000 across the UK) were calculated. Surface concentrations of SO<sub>2</sub>, NO<sub>x</sub> and NH<sub>3</sub> (and of deposition of S and N) were found to be predominantly sensitive to the emissions of the respective pollutant, while sensitivities of secondary species such as HNO<sub>3</sub> and particulate SO<sub>4</sub><sup>2-</sup>, NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup> to pollutant emissions were more complex and geographically variable. The uncertainties in model output variables were propagated from the uncertainty ranges reported by the UK National Atmospheric Emissions Inventory for the emissions of SO<sub>2</sub>, NO<sub>x</sub> and NH<sub>3</sub> (&plusmn;&nbsp;4&nbsp;%, &plusmn;&nbsp;10&nbsp;% and &plusmn; 20&nbsp;% respectively). The uncertainties in the surface concentrations of NH<sub>3</sub> and NO<sub>x</sub> and the depositions of NH<sub>x</sub> and NO<sub>y</sub> were dominated by the uncertainties in emissions of NH<sub>3</sub>, and NO<sub>x</sub> respectively, whilst concentrations of SO<sub>2</sub> and deposition of SO<sub>y</sub> were affected by the uncertainties in both SO<sub>2</sub> and NH<sub>3</sub> emissions. Likewise, the relative uncertainties in the modelled surface concentrations of each of the secondary pollutant variables (NH<sub>4</sub><sup>+</sup>, NO<sub>3</sub><sup>-</sup>, SO<sub>4</sub><sup>2-</sup> and HNO<sub>3</sub>) were due to uncertainties in at least two input variables. In all cases the spatial distribution of relative uncertainty was found to be geographically heterogeneous. The global methods used here can be applied to conduct sensitivity and uncertainty analyses of other ACTMs.</p> <p>The dataset contains model outputs used for the sensitivity and uncertainty analyses.</p>

opencc-by-4.0Dec 2017View details →
zenodo36/100

Data and code for "Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand"

<p>Data and code for&nbsp;<br>"Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand"</p> <p>All R code used for the analysis is provided in the folder <em>code</em>.&nbsp;<br>Data and intermediate results are provided or stored in the folders <em>data </em>and&nbsp;<em>tmp_data</em>.<br>All results including figures will be stored in the folder&nbsp;<em>results</em>.&nbsp;</p> <p>R version: 4.3.1</p> <p>To carry out the entire analysis the code should be run in the provided order:</p> <p>1) Code to run non-metric multidimensional scaling (NMDS) for habitat groups and&nbsp;<br>produce Fig. 1b (habitat map and legend for Fig 1a: data/eunis_gl_habitat_ger_990m.tif,eunis_gl_habitat_ger_990m_legend.clr)<br>&nbsp;<br>2) Code to generate grassland vitality maps and time series from 1985 to 2021 (Fig. 3).&nbsp;<br>Grassland vitality maps on 30m for all grasslands in Germany provided in data/glv_1985-2021.zip.</p> <p>3) Code to model relation of grassland vitality to five drought indices (VPD, temperature, CWB, soil moisture, precipitation),<br>output are Fig. 4, Fig. S1, Tab. 1.</p> <p>4) Code for trend analysis of drought sensitivity based on 5-, 10-, and 15-year moving windows, output are Fig. 5, Fig. S2.&nbsp;</p> <p>5) Code to model drought sensitivity of grassland habitat groups and habitat types, output are Fig. 6 and table with sensitivity per habitat type.&nbsp;</p>

opencc-by-4.0Feb 2024View details →
zenodo36/100

Raw data for "Direct Observation of Atmospheric Turbulence with a Video-rate Wide-field Wavefront Sensor" (Part. 1)

<p>Raw data for "Direct Observation of Atmospheric Turbulence with a Video-rate Wide-field Wavefront Sensor" (Part. 1). For usage, please refer to https://github.com/freemercury/Widefield_wavefront_sensor.</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Raw data for "Direct Observation of Atmospheric Turbulence with a Video-rate Wide-field Wavefront Sensor" (Part. 2)

<p>Raw data for "Direct Observation of Atmospheric Turbulence with a Video-rate Wide-field Wavefront Sensor" (Part. 2). For usage, please refer to https://github.com/freemercury/Widefield_wavefront_sensor.</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

The Model Grid for The atmosphere of HD 149026b: Low metal-enrichment and weak energy transport

<p>This grid contains cloud-free 1-dimensional radiative-convective-thermochemical equilibrium atmosphere models created using the Python-based code <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters varied for this grid are the atmospheric metallicity (<em>[M/H]</em>), Carbon-to-Oxygen ratio (<em>C/O</em>), heat redistribution factor (<em>rfacv</em>), and the intrinsic temperature of the planet (<em>Tint</em>). The ranges of these parameters have been outlined in the paper.&nbsp;</p> <p>The profile and spectra are provided for each model as a .dat file. Each profile contains the temperature and abundance for a variety of chemicals at each of the 91 pressure levels modeled for the atmosphere. The spectra file contains the wavelength in microns, transit depth, eclipse depth, and emission flux from the planet in ergs/s/cm^3. The isolated planetary thermal emission spectrum needs to be multiplied by 1e6 to be in ppm. There are four types of models, ones with VO, ones with TiO, ones with TiO and VO, and ones without TiO or VO. The files are labeled based on each of the 4 atmospheric parameters and whether they contain TiO and VO.</p> <p>Note on TiO: The inclusion of gaseous TiO in the atmosphere was found to cause strong inversions in the temperature-pressure profile and a worse fit of the thermal emission spectrum to the data. This finding has been described in the paper.</p>

opencc-by-4.0Apr 2024View details →
dryad36/100

Data from: Estimates of late Early Cretaceous atmospheric CO2 from Mongolia based on stomatal and isotopic analysis of Pseudotorellia

<p>Our dataset includes 115 leaf cuticles related to two species of <em>Pseudotorellia</em> Florin from three stratigraphically similar samples at the Tevshiin Govi lignite mine in central Mongolia (~119.7–100.5 Ma, Aptian–Albian, Cretaceous). We apply a well-vetted paleo-CO<sub>2</sub> proxy based on leaf gas-exchange principles (the Franks model) to those leaves for paleo-CO<sub>2</sub> reconstruction, which requires leaf stomata and carbon isotope analysis. All cuticle measurements are summarized in this dataset. </p>

opencc-zeroMay 2024View details →
zenodo36/100

Raw Data for Control of Ferroelectricity in Solution-Processed Hafnia Films through Annealing Atmosphere

<p>The following raw data are the basis of the paper "Control of Ferroelectricity in Solution-Processed Hafnia Films through Annealing Atmosphere" published in Advanced Electronic Materials in 2024 (DOI 10.1002/aelm.202300893).</p> <p>BM and SG acknowledge Luxembourg National Research Fund (FNR) for supporting this work through the project TRICOLOR (INTER/NWO/20/15079143/TRICOLOR). We would like to thank Prof. Beatriz Noheda, Prof. Monica Acuautla, and Dr. Miguel Badillo for their inputs on the growth process used in this work and electrical characterization of the thin films.</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Data and code for: Influence of atmospheric nitrogen deposition on soil greenhouse gas fluxes from forests in China and the world

<p><span>Since the industrial revolution, greenhouse gas emissions (particularly CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O) caused by human activities have accelerated global climate change. To avoid catastrophic transitions in the Earth system, many countries including China have set goals to achieve &ldquo;net zero emission&rdquo; (or &ldquo;carbon neutrality&rdquo;) by mid-21<sup>st</sup> century. Forestland-related practices are among the most preferred &ldquo;natural climate solutions&rdquo;. However, high uncertainties remain in the greenhouse gas fluxes from forest soils, because of the limited capability to observe soil dynamics at a large spatial scale. Meanwhile, forest soil greenhouse gas fluxes are influenced by multiple anthropogenic environmental changes including enhanced atmospheric nitrogen deposition, which further complicates the interactions between forest ecosystem and the atmosphere. During the past half century, simulated nitrogen deposition (or &ldquo;nitrogen addition&rdquo;) experiments have been conducted in various forest sites worldwide, founding a basis for quantifying the spatially-varying responses of soil greenhouse gas flux to nitrogen deposition. </span></p> <p><span>In this research, we systematically synthesized global nitrogen addition experiment data from published literature and public databases, using which we explored the responses of the three major greenhouse gases to N input. Derived sensitivity of soil N<sub>2</sub>O emission to N deposition allowed for determining the N saturation (or limitation) status of global forests. Using process-augmented data-driven approach and random forest regression models, we estimated soil greenhouse gas budgets on regional and global levels. On the basis, we quantified the varying effects of N deposition on soil greenhouse gas fluxes in N-limited and N-saturated forests across biomes.&nbsp;</span><span> </span></p> <p><span>The produced global map of N-saturated forests in this research could facilitate studies on carbon and nitrogen cycles and improve forest nitrogen management. The revealed response patterns and response factors of soil greenhouse gases to N input could help improve the structure and parameters of ecosystem models. Furthermore, the localized N<sub>2</sub>O emission factors for 145 countries could be used to reduce the uncertainties in their national greenhouse gas inventories. The &ldquo;process-augmented data-driven&rdquo; approach could potentially bridge the gap between site-level manipulative experiments and the demand for regional greenhouse gas budgets, allowing manipulative experiments to play a more important role in global change research. </span></p>

opencc-by-4.0May 2024View details →
zenodo36/100

Modeling the impacts of Antarctic Sea Ice Decline: Responses of Atmospheric Dynamics

Open the record for dataset details and reuse information.

opencc-by-4.0May 2024View details →
zenodo36/100

Atmospheric River Database & Detection Code

<p>This database contains the global atmospheric river catalogs detected by the PanLu algorithm within ERA5 and CMIP6 models. The PanLu detection code is also included now.</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Limits of the Habitable Zone CO2 atmosphere with 3D Climate Modelling

<p>Water is crucial for life, regardless of the environment. That's why in search of extraterrestrial life, we focus on planets in the habitable zone (HZ), where liquid water can exist. The size of this zone depends on factors like the star type and planet size. Using the Generic PCM model (https://lmdz-forge.lmd.jussieu.fr/mediawiki/Planets/index.php/Overview_of_the_Generic_PCM), we've defined the limits of the HZ for atmospheres dominated by CO2 in 3D for the first time. You can access the dataset from the simulations in ".nc" file format. Temporal evolution of variables such as surface temperature, surface pressure, water vapour, liquid water, ice etc. are in a 3D grid for different orbital distances and with different surface pressures are present in the dataset. We have used the correlated-k table published in Zenodo for the simulations (https://doi.org/10.5281/zenodo.10978791).</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Correlated-k table for H2 dominated atmospheres for 3D Climate Modelling

<p>Correlated-k table for H2 dominated atmospheres with a variable amount of water vapour &nbsp;built by incorporating absorption data files from the HITRAN database &nbsp;and using the exo\_k code by J.Leconte. This correlated-k tables are created to use with Generic-PCM model to simulate the atmospheres of H2 dominated planets.</p> <p>The calculation of radiative transfer can be performed using the correlated-k method, which efficiently determines net radiative fluxes by categorizing spectral lines into infrared and visible bands (IR x VI) and assigning the average absorption coefficients to each band. These coefficients are pre-calculated based on detailed line-by-line radiative transfer calculations. The correlated-k method is an economic alternative to the line-by-line method, making it possible to accurately and rapidly compute atmospheric radiation.</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Correlated-k table for CO2 dominated atmospheres for 3D Climate Modelling

<p>Correlated-k table for CO2 dominated atmospheres with a variable amount of water vapour &nbsp;built by incorporating absorption data files from the HITRAN database &nbsp;and using the exo\_k code by J.Leconte. This correlated-k tables are created to use with Generic-PCM model to simulate the atmospheres of CO2 dominated planets.</p> <p>The calculation of radiative transfer can be performed using the correlated-k method, which efficiently determines net radiative fluxes by categorizing spectral lines into infrared and visible bands (IR x VI) and assigning the average absorption coefficients to each band. These coefficients are pre-calculated based on detailed line-by-line radiative transfer calculations. The correlated-k method is an economic alternative to the line-by-line method, making it possible to accurately and rapidly compute atmospheric radiation.</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Limits of the Habitable Zone for H2 atmosphere with 3D climate Modelling

<p>Water is crucial for life, regardless of the environment. That's why in search of extraterrestrial life, we focus on planets in the habitable zone (HZ), where liquid water can exist. The size of this zone depends on factors like the star type and planet size. Using the Generic PCM model (https://lmdz-forge.lmd.jussieu.fr/mediawiki/Planets/index.php/Overview_of_the_Generic_PCM), we've defined the limits of the HZ for atmospheres dominated by H2 in 3D for the first time. You can access the dataset from the simulations in ".nc" file format. Temporal evolution of variables such as surface temperature, surface pressure, water vapour, liquid water, ice etc. are in a 3D grid for different orbital distances and with different surface pressures are present in the dataset. We have used the correlated-k table published in Zenodo for the simulations (https://doi.org/10.5281/zenodo.10978762).</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Simulation results with the EULAG research model for the publication: "Large eddy simulations of the interaction between the Atmospheric Boundary Layer and degrading Arctic permafrost"

<p>Supplementary material for the publication</p> <ul> <li>Mark Schlutow, Tobias Stacke, Tom Doerffel, et al. Large eddy simulations of the interaction between the Atmospheric Boundary Layer and degrading Arctic permafrost. ESS Open Archive . January 24, 2024. <a href="https://doi.org/10.22541/essoar.170612558.81370785/v1">https://doi.org/10.22541/essoar.170612558.81370785/v1</a></li> </ul> <p>The material contains all simulation results and raw outputs that are necessary to reproduce the figures and statistics of the publication.&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Nowcast of Aerospace Ionizing Radiation System (NAIRAS) simulation of the effect of the 2024-05-11 coronal mass ejection and solar particle event on Earth's atmosphere

<p>The effect of the CME on the cutoff rigidity and the dose at different altitude as computed by NAIRAS.</p> <p>The neutron monitor data from OULU and the DSCOVR data for solar wind density and speed are put as a reference for when the Forbush decrease happens and when the CME arrives.</p> <p>&nbsp;</p> <p>The version 2 added files with shorter lead time before the CME arrival and bigger labels</p>

opencc-by-4.0May 2024View details →
dryad36/100

Data from: Nitrifier controls on soil NO and N2O emissions in three chaparral ecosystems under contrasting atmospheric N inputs

<p>Nitrogen saturation theory predicts high rates of atmospheric N deposition can increase ecosystem N availability and stimulate ecosystem N losses via soil nitric oxide (NO; an air pollutant at high concentrations) and nitrous oxide (N<sub>2</sub>O; a strong greenhouse gas) emissions. However, it remains unclear whether theories developed in mesic ecosystems apply to drylands, where plant and soil N availability are not always coupled in dry soils. NO and N<sub>2</sub>O are often produced in soils during the oxidation of ammonia by ammonia oxidizing archaea (AOA) or ammonia oxidizing bacteria (AOB) during nitrification. AOB are thought to emit more NO and N<sub>2</sub>O during nitrification than AOA and may be favored in N-rich relative to N-limited environments, suggesting high rates of atmospheric N deposition might produce positive feedback sending more of the N to the atmosphere. To assess how high rates of atmospheric N deposition affect AOB- and AOA-derived N trace gas emissions, we selectively inhibited AOA and AOB nitrifiers and measured NO and N<sub>2</sub>O emissions from soils collected from three dryland sites exposed to relatively low (3.8 kg ha<sup>-1 </sup>= Low N) or high (11.8 kg ha<sup>-1</sup> = High N1; 15.6 kg ha<sup>-1</sup> = High N2) rates of atmospheric N inputs. We found that while the High N2 deposition site had the lowest AOA:AOB ratio (2.33 ± 0.57), consistent with expectations, this site did not emit the most NO and N<sub>2</sub>O. Rather, AOA emitted between 21–78% of the NO from our sites, with higher AOA-derived NO emissions from relatively coarse-textured soils in the Low N deposition site. In addition to nitrification, denitrification also contributed to NO and N<sub>2</sub>O emissions, especially in the Moderate N deposition site (where denitrification-derived NO and N<sub>2</sub>O emissions were 2.0 – 3.7 time greater than the other sites), which had finer textured soils that may favor denitrification. Interactions between soil texture and N availability, therefore, appears to be the primary mechanism determining whether atmospheric N deposition is retained in the ecosystem or reemitted to the atmosphere as NO or N<sub>2</sub>O.</p>

opencc-zeroMay 2024View details →
zenodo36/100

Spatial and temporal variability of freezing level in Patagonia's atmosphere

<p>Deprecated version. Please review the latest version:&nbsp;<a href="../doi/10.5281/zenodo.11397841">10.5281/zenodo.11397841&nbsp;</a></p>

opencc-by-4.0Jan 2024View details →
zenodo36/100

The SPHINX M-dwarf Spectral Grid. I. Benchmarking New Model Atmospheres to Derive Fundamental M-Dwarf Properties

<p><strong>NEW UPDATE:::::::::::::VERSION 4</strong></p> <p>MODEL GRID AND SUPPLEMENTARY FIGURES for&nbsp;<strong>The SPHINX M-dwarf Spectral Grid. I. Benchmarking New Model Atmospheres to Derive Fundamental M-Dwarf Properties:</strong></p> <p><strong>(1) MODEL GRID:</strong> Zip file titled 'SPHINX_MODELS_MLT_1.zip' contains a directory (376MB on disk) that is divided into three folders: ATMS, SPECTRA, and ABUNDANCES. All models here assume mixing length parameter of 1. For more info, we direct the reader to the paper.</p> <p>The ATMS directory contains thermal profiles/atmospheres of all models. (Temperature in K, Pressure in bars)</p> <p>The SPECTRA directory contains synthetic spectra. (Wavelength--0.1 to 20 microns, Flux in W/m2/m, R~250)</p> <p>The ABUNDANCES directory contains mixing ratios of all atomic and molecular species included in these models.</p> <p><strong>(2) SUPPLEMENTARY FIGURES:</strong></p> <p>The plot files are named as 'target name' _ corner.</p> <p>Each file is a corner plot of posterior probability distributions from grid-model fit of low-resolution spectra of benchmark M dwarfs using the SPHINX model grid. We also include posterior distributions of Starfish (Czekala et al.2015) hyperparameters to properly constrain model and data systematics. The vertical blue lines in the plots indicate values from observations (empirically derived [M/H] from Mann et al. 2013 and interferometrically measured radii from Boyajian et al. 2012b).</p> <p>File named Gl436_mixinglength shows difference in grid model fit assuming mixing length parameter 1 vs 0.5.</p> <p>File named Gl725B_spot shows difference in grid model fit assuming stellar photospheric heterogeneity vs without.</p> <p><strong>If you use our stellar atmosphere models, please remember to cite both the zenodo doi for the open source data as well as the paper. Thank you!</strong></p> <p>&nbsp;</p> <p>--&gt; link to <a href="https://iopscience.iop.org/article/10.3847/1538-4357/acabc2/meta">published paper</a></p>

opencc-by-4.0Jun 2022View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record