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1,574 results for “atmospheres”
Dataset: Insights into the Stabilization of Atmospheric Iron(II) by Water-Soluble Organic Matter: Role of Aliphatic Organosulfates
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Spatiotemporal high-resolution (daily, 1-km) atmospheric CO2 reconstruction data across China
<p>We employed an enhanced regression-based machine learning model to reconstruct full-coverage daily atmospheric CO2 concentrations in China from 2015 to 2020 at a 0.01° spatial resolution. Utilizing spatiotemporal high-resolution column-averaged dry-air mole fraction of CO2 (XCO2) data from the Orbiting Carbon Observatory 2 (OCO-2) as the dependent variable and multi-source environmental factors as independent variables, we achieved overall, spatial, and temporal cross-validation R2 [RMSE] results of 0.98 [0.74 ppm], 0.95 [1.15 ppm], and 0.93 [1.44 ppm], respectively. </p> <p>The daily XCO2 data are archieved in NetCDF format. If you want to use this dataset, please cite the following publication. If you want annual or monthly data, please go to <a href="../records/10022905">10.5281/zenodo.10022905</a>.</p> <p>--He, Q., Ye, T., Chen, X., Dong, H., Wang, W., Liang, Y., & Li, Y. (2023). Full-coverage mapping high-resolution atmospheric CO2 concentrations in China from 2015 to 2020: Spatiotemporal variations and coupled trends with particulate pollution. <em>Journal of Cleaner Production</em>, 139290. [<a href="https://doi.org/10.1016/j.jclepro.2023.139290">url</a>]</p> <p> </p> <p>We also share other reconstruction datasets of atmopsheric parameters:</p> <p>For full-coverage, daily, 1-km, AOD data in China, please go to <a href="https://dataverse.harvard.edu/dataverse/atmospheric_data_by_WHUT">harvard dataverse</a>. This dataset was imputed based on MODIS MAIAC 1-km AOD retrievals.</p> <p>For full-covereage, daily, 1-km, PM2.5 data in China, please go to <a href="../doi/10.5281/zenodo.8437234">10.5281/zenodo.8437234 or </a><a href="../record/8347128">10.5281/zenodo.8347128.</a></p> <p>For full-coverage, daily, 1-km ozone data in China, please go to <a href="13623698">10.5281/zenodo.13623698</a>.</p>
RFM atmospheric profiles input
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Reproduction package for the paper: "Cold day-side winds shape large leading streams in evaporating exoplanet atmospheres"
<p>Supplementary material for the paper "Cold day-side winds shape large leading streams in evaporating exoplanet atmospheres" by Nail et al. (2024). <br><br>We provide the results of the 3D hydrodynamic simulation with Athena++, with key files including the input file and a snapshot from the simulation taken after 8 orbits for all models discussed in the paper. The post-processing is performed using a radiative transfer code found in the "post-process_HAT67" folder. This code, described by MacLeod & Oklopcic (2022), produces synthetic spectra from the simulation snapshots and has been enhanced for precise calculations in high-density regions. Additionally, a Jupyter notebook demonstrates how to analyze the data and create the figures presented in the paper.</p> <p>Note: In the new version of the paper, we use "dtaui = d['nhe3'] * d['dr'] * csi * Voigt(nu_cell, da1, natural_gamma)" in the Figures.ipynb notebook in cell 42. </p>
Supplementary Figures for paper "First Comparative Exoplanetology Within a Transiting Multi-planet System: Comparing the atmospheres of V1298 Tau b and c" (accepted A&A)
<p>Supplementary figures for paper entitled "First Comparative Exoplanetology Within a Transiting Multi-planet System: Comparing the atmospheres of V1298 Tau b and c" accepted for publication in Astronomy & Astrophysics (A&A)</p>
Enhanced Ice Nucleation Activity by Metal Elements and Secondary Aerosols in Polluted Urban Atmosphere
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Data from: Increased root herbivory under elevated atmospheric carbon dioxide concentrations is reversed by silicon-based plant defences
Predicted increases in atmospheric concentrations of CO2 may alter the susceptibility of many plants to insect herbivores due to changes in plant nutrition and defences. Silicon plays a critical role in plant defence against herbivores, so increasing such silicon-based defences in plants may help remediate situations where plants become more susceptible to herbivores. Sugarcane (Saccharum spp. hybrid) were subjected to fully factorial treatment combinations of ambient (aCO2) or elevated (eCO2) atmospheric CO2 concentrations; ambient silicon or silicon supplementation; insect-free or subject to root herbivory by greyback canegrub (Dermolepida albohirtum). A glasshouse study was used to determine how these factors affected rates of photosynthesis, growth, chemistry (concentrations of silicon, carbon, nitrogen and non-structural carbohydrates). Changes in canegrub mass were determined in the glasshouse pot study, together with more detailed assessment of how eCO2 and silicon supplementation affected performance and feeding behaviour (relative growth rate and relative consumption) in a 24-hour feeding efficiency assay. eCO2 and silicon supplementation increased rates of photosynthesis (+32% and 14%, respectively) sugarcane biomass (+45% and 69%, respectively). Silicon supplementation increased silicon concentrations in both leaves and roots by 54% and 75%, respectively. eCO2 caused root C:N to increase by 12%. Canegrub performance and consumption increased under eCO2; relative growth rate (RGR) increased by 116% and consumed 57% more root material (suggestive of compensatory feeding). Silicon application reversed these effects, with large decreases in mass change, RGR and root consumption (65% less root mass consumed). Synthesis and applications. Our results suggest future atmospheric carbon dioxide concentrations could lead to increased crop damage by a below-ground herbivore. Increasing bioavailable silicon in soil stimulated silicon-based defences which dramatically decreased herbivory and herbivore performance. Our findings suggest future pest management strategies could benefit from characterising deficiencies in bioavailable silicon in agricultural soils and targeted application of silicon fertilisers. Moreover, future breeding programmes should exploit variation in silicon uptake between cultivars to enhance silicon uptake in new crop varieties. Silicon-based plant defence proved to be highly beneficial for remediating the negative effects of atmospheric change on sugarcane susceptibility to herbivory and could be applicable in other crops.
Ground-based vertical observations of atmospheric composition from field campaign on the Tibetan Plateau
<p>We introduce a long-term (2017-2019) vertical observational dataset of atmospheric composition in the TP from MAX-DOAS, a passive remote sensing technique.</p>
Genesis locations of the costliest atmospheric rivers impacting the Western United States (insurance claim data)
<p>Atmospheric rivers (ARs) are responsible for the vast majority (approximately 88%) of flood damage in the Western U.S, an annual average of USD$1.1 billion. Here, using historical flood insurance data, we investigate the genesis characteristics of damaging ARs in the Western U.S. ARs exceeding USD$20 million in damage (90th percentile), are shown to travel further across the Pacific Ocean, with median genesis locations 8° to 27° further westward compared to typical ARs. Identifying regions of preferential genesis of damaging ARs elicit important implications for AR observation campaigns, highlighting distant regions not currently considered for AR reconnaissance. The genesis of damaging ARs is associated with elevated upper-level zonal wind speeds along with deeper cyclonic anomalies, most pronounced for Washington and Oregon ARs. Linking AR dynamics and lifecycle characteristics to economic damage provides an opportunity for impact-based forecasting of ARs prior to landfall, supporting efforts to mitigate extreme flood damages.</p>
Bottom-of-atmosphere reflectance data from aerial imaging for Lake Mulargia (Sardinia, Italy) (2020/09/24)
<p>This dataset contains the surface reflectance Hyspex images derived with ATCOR code by CNR of Lake Mulargia (Sardinia, Italy). The acquisition was done by CGR Spa (Italy).</p>
Explosion of red-supergiant stars: Influence of the atmospheric structure on shock breakout and early-time supernova radiation
<p>Model spectra from <a href="https://ui.adsabs.harvard.edu/abs/2017A%26A...605A..83D">Dessart, Hillier & Audit 2017, A&A, 605, 83</a>.</p>
Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
<p>This data set contains the interannual variability fields for the sea level (ssh_var_inter_1993_2015_annuel.tar.gz) and its steric (hsterica_var_inter_1993_2015_annuel.tar.gz) and manometric (obp_var_inter_1993_2015_annuel.tar.gz) components over 1993-2015 from the OCCIPUT ensemble simulations. It is used in the paper « Atmospherically forced and chaotic interannual variability of regional sea level and its components over 1993-2015 » published in Journal of Geophysical Research - Oceans.</p> <p>This dataset has been computed from the OceaniC Chaos – ImPacts, strUcture, predicTability (OCCIPUT) global ocean/sea-ice ensemble simulation. It is composed of 50 members with a horizontal resolution of 1/4° and 75 geopotential levels (Bessières et al., 2017, Penduff et al., 2014). The numerical configuration is based on the version 3.5 of the NEMO model (Madec, 2008). The 50 members were started on January 1st 1960 from a common 21-year spinup. A small stochastic perturbation is applied to the equation of state of sea water (as in Brankart, 2013) within each member during 1960, then switched off during the rest of the simulation. This 1-year perturbation generates an ensemble spread which grows and saturates after a few months up to a few years depending on the region. The 50 members are driven through bulk formulae during the whole 1960-2015 simulation by the same realistic 6-hourly atmospheric forcing (Drakkar Forcing Set DFS5.2, Dussin et al., 2016) derived from ERA interim atmospheric reanalysis.</p> <p> </p> <p>For each member, the simulated sea surface height (SSH) over 1993-2015 is considered. As NEMO is a Boussinesq model, it conserves volume instead of mass. Therefore, the steric effect is missing into the global mean sea level change (Greatbatch 1994). To overcome this issue, we remove the global mean estimate for the sea level time series at each grid point. Then the sea level anomalies obtained are averaged per year and a linear trend is removed from each member. The same processes are applied to the steric and manometric sea level time series.</p> <p> </p> <p>Here is an example of the file header</p> <p><em><strong>dimensions:</strong></em></p> <p><em><strong>member = UNLIMITED ; // (50 currently)</strong></em></p> <p><em><strong>time = 23 ;</strong></em></p> <p><em><strong>y = 1021 ;</strong></em></p> <p><em><strong>x = 1442 ;</strong></em></p> <p><em><strong>variables:</strong></em></p> <p><em><strong> float ssh(member, time, y, x) ;</strong></em></p> <p><em><strong> ssh:long_name = "sea level interannual variability" ;</strong></em></p> <p><em><strong> ssh:standard_name = "sea_level interannual variability" ;</strong></em></p> <p><em><strong> ssh:units = "m" ;</strong></em></p> <p><em><strong> ssh:FillValue = "nan" ;</strong></em></p> <p><em><strong> float nav_lat(member, y, x) ;</strong></em></p> <p><em><strong> nav_lat:axis = "Y" ;</strong></em></p> <p><em><strong> nav_lat:long_name = "Latitude" ;</strong></em></p> <p><em><strong> nav_lat:standard_name = "latitude" ;</strong></em></p> <p><em><strong> nav_lat:units = "degrees_north" ;</strong></em></p> <p><em><strong> float nav_lon(member, y, x) ;</strong></em></p> <p><em><strong> nav_lon:axis = "Y" ;</strong></em></p> <p><em><strong> nav_lon:long_name = "Longitude" ;</strong></em></p> <p><em><strong> nav_lon:standard_name = "longitude" ;</strong></em></p> <p><em><strong> nav_lon:units = "degrees_east" ;</strong></em></p> <p><em><strong> float time(time) ;</strong></em></p> <p><em><strong> time:long_name = "time" ;</strong></em></p> <p><em><strong> time:standard_name = "time" ;</strong></em></p> <p><em><strong> time:units = "years since 1992" ;</strong></em></p> <p> </p> <p>nav_lat and nav_lon represent the latitude and longitude of the NEMO model whereas var represents the interannual variability time series. </p>
Intercomparison of Middle Atmospheric Meteorological Analyses for the Northern Hemisphere Winter 2009-2010
<p>Model output required to reproduce figures in McCormack et al. (2021) ACP</p>
Figure 1 from: Máguas C, Pinho P, Branquinho C, Hartard B, Lakatos M (2013) Carbon-Water-Nitrogen relationships between lichens and the atmosphere: Tools to understand metabolism and ecosystem change. MycoKeys 6: 95-106. https://doi.org/10.3897/mycokeys.6.4814
Figure 1 - Schematic illustration of a cross-section through a lichen thallus with distinctive cortex, algal layer and medulla and the main factors contributing to thallus CO2 exchange and the consequence for carbon d13C fractionation that affects organic matter in lichens.
Figure 2 from: Piazza P, Blazewicz-Paszkowycz M, Ghiglione C, Alvaro M, Schnabel K, Schiaparelli S (2014) Distributional records of Ross Sea (Antarctica) Tanaidacea from museum samples stored in the collections of the Italian National Antarctic Museum (MNA) and the New Zealand National Institute of Water and Atmospheric Research (NIWA). ZooKeys 451: 49-60. https://doi.org/10.3897/zookeys.451.8373
Figure 2 - Map of sampling stations. Green dots: samples stored at the MNA. Blue dots: samples stored at the NIWA.
Advanced methods for uncertainty assessment and global sensitivity analysis of a Eulerian atmospheric chemistry transport model
<p>Atmospheric chemistry transport models (ACTMs) are extensively used to provide scientific support for the development of policies to mitigate against the detrimental effects of air pollution on human health and ecosystems. Therefore, it is essential to quantitatively assess the level of model uncertainty and to identify the model input parameters that contribute the most to the uncertainty. For complex process-based models, such as ACTMs, uncertainty and global sensitivity analyses are still challenging and are often limited by computational constraints due to the requirement of a large number of model runs. In this work, we demonstrate an emulator-based approach to uncertainty quantification and variance-based sensitivity analysis for the EMEP4UK model (regional application of the European Monitoring and Evaluation Programme Meteorological Synthesizing Centre-West). A separate Gaussian process emulator was used to estimate model predictions at unsampled points in the space of the uncertain model inputs for every modelled grid cell. The training points for the emulator were chosen using an optimised Latin hypercube sampling design. The uncertainties in surface concentrations of O<sub>3</sub>, NO<sub>2</sub>, and PM<sub>2.5</sub> were propagated from the uncertainties in the anthropogenic emissions of NO<sub>x</sub>, SO<sub>2</sub>, NH<sub>3</sub>, VOC, and primary PM<sub>2.5</sub> reported by the UK National Atmospheric Emissions Inventory. The results of the EMEP4UK uncertainty analysis for the annually averaged model predictions indicate that modelled surface concentrations of O<sub>3</sub>, NO<sub>2</sub>, and PM<sub>2.5</sub> have the highest level of uncertainty in the grid cells comprising urban areas (up to ± 7%, ± 9%, and ± 9% respectively). The uncertainty in the surface concentrations of O<sub>3 </sub>and NO<sub>2</sub> were dominated by uncertainties in NO<sub>x</sub> emissions combined from non-dominant sectors (i.e. all sectors excluding energy production and road transport) and shipping emissions. Additionally, uncertainty in O<sub>3</sub> was driven by uncertainty VOC emissions combined from sectors excluding solvent use. Uncertainties in the modelled PM<sub>2.5</sub> concentrations were mainly driven by uncertainties in primary PM<sub>2.5</sub> emissions and NH<sub>3</sub> emissions from the agricultural sector. Uncertainty and sensitivity analyses were also performed for five selected grid sells for monthly averaged model predictions to illustrate the seasonal change in the magnitude of uncertainty and change in the contribution of different model inputs to the overall uncertainty. Our study demonstrates the viability of a Gaussian process emulator-based approach for uncertainty and global sensitivity analyses, which can be applied to other ACTMs. Conducting these analyses helps to increase the confidence in model predictions. Additionally, the emulators created for these analyses can be used to predict the ACTM response for any other combination of perturbed input emissions within the ranges set for the original Latin hypercube sampling design without the need to re-run the ACTM, thus allowing fast exploratory assessments at significantly reduced computational costs.</p> <p>The upload contains the uncertainty and sensitivity data together with the analysis scripts.</p>
Supplementary material 1 from: Balestrini R, Delconte C, Buffagni A, Fumagalli A, Freppaz M, Calvo E, Buzzetti I (2019) Dynamic of nitrogen and dissolved organic carbon in an alpine forested catchment: atmospheric deposition and soil solution trends. In: Mazzocchi MG, Capotondi L, Freppaz M, Lugliè A, Campanaro A (Eds) Italian Long-Term Ecological Research for understanding ecosystem diversity and functioning. Case studies from aquatic, terrestrial and transitional domains. Nature Conservation 34: 41-66. https://doi.org/10.3897/natureconservation.34.30738
: Data type: statistical data
Global simulations of multi-frequency HF signal absorption for direct observation of middle atmosphere temperature and composition
<p>The model used in the publication for Global simulations of multi-frequency HF signal absorption for direct observation of middle atmosphere temperature and composition</p> <p> </p> <p>This paper presents the first numerical study on a new concept for the direct measurement of D-region absorption in the HF band. Numerical simulations based on the Appleton–Hartree and Garrett equations of refractive index are presented. Electron temperature as a result of HF radio pumping of the ionosphere is included in the calculations using proper numerical formulation. Both O- and X-mode radio wave polarizations are taken into consideration. A global map of HF absorption in the northern hemisphere is calculated. Detailed calculations of HF radio wave absorption as it propagates through the lower atmosphere are presented. The effect of several parameters on the amount of absorption is calculated. The best frequencies to be used for the purpose of this study are discussed. A machine learning model is developed and the capability of the model in estimation of D and E-region constituents includes $N_2$, $O$, $O_2$, as well as $T$ and $N_e$ is examined. Such a technique can also lead to global mapping of HF absorption and improve OTHR (over-the-horizon-radar) performance. </p>
Prestorm atmospheric dynamic variable profiling dataset in Beijing as observed from the Radar wind profiler mesonet
<p>This dataset contains prestorm atmospheric dynamical variables of 30 minutes before rainfall onset in summer (June ~ August) for the period 2018–2019, which is determined by the measurements from the triangular mesonet of radar wind profile in Beijing. Each data file is stored in CSV format, containing the triangle area averaged divergence, vertical velocity and vorticity at 400、450、500、550, 600, 650, 700, 750, 775, 800, 825, 850, 875 and 900 hPa levels. The name for each data is formatted as RWP_YYYY_NNN hPa_Lead-MM min.csv, where YYYY refers to 2018 and 2019, NNN refers to 400、450、500、550, 600, 650, 700, 750, 775, 800, 825, 850, 875 and 900 hPa, and MM refers to 12, 18, 24, 30, 36 and 42 minutes prior to rainfall onset. </p>
Simulations of Typhoon In-Fa (2106) and air-sea interactions using a coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system
<p>The Observation data supporting the result of our manucript submitted to JGR-Ocean.</p> <p> </p>
ScienceDex guides
Understand access before you commit
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.