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1,574 results for “atmospheres”
Ivanciu et al., 2020 - Effects of prescribed CMIP6 ozone on simulating the Southern Hemisphere atmospheric circulation response to ozone depletion
<p>Model data used in the analysis published in the study by Ivanciu et al., 2020 "Effects of prescribed CMIP6 ozone on simulating the Southern Hemisphere atmospheric circulation response to ozone depletion". The data was produced using the coupled climate model FOCI (Flexible Ocean and Climate Infrastructure, Matthes et al., 2020). An overview of the available fields can be found in the README.md file.</p>
Improved representation of clouds in the atmospheric component LMDZ6A of the IPSL Earth system model IPSL-CM6A : Source codes and supporting files
<p>Source codes and supporting files of the paper by J-B Madeleine et al., 2020, entitled "Improved representation of clouds in the atmospheric component LMDZ6A of the IPSL Earth system model IPSL-CM6A" published in the Journal of Advances in Modeling Earth Systems. See the README file for more information.</p>
Dataset for: "The ARCiS framework for Exoplanet Atmospheres: Modelling Philosophy and Retrieval"
<p>This is the data package accompanying the publication: The ARCiS framework for Exoplanet Atmospheres: Modelling Philosophy and Retrieval</p> <p>Accepted for publication in A&A</p>
Unusual changes in the Antarctic Middle Atmosphere during the 2019 Warming in the Southern Hemisphere
<p>For the Antarctic mesosphere study, we used wind measurements by the King Sejong Station (62.22<sup>o</sup>S, 58.78°W) Meteor Radar (KSSMR). The KSS MR provides winds from the altitude 70 km to 100 km with 1 hour and 2 km height resolutions. Here we uploaded the daily zonal and meridional winds during July to October of Southern Hemisphere. The data files contains the height and time evolution of wind components. Each file contains the height (First Column) and Winds (from Second column). The time period is from Julian Day 180 to 285 for the year 2019.</p>
Water availability drives fine root dynamics in a Eucalyptus woodland under elevated atmospheric CO2 concentration
<p>Fine roots are a key component of carbon and nutrient dynamics in forest ecosystems. Rising atmospheric [CO<sub>2</sub>] (eCO<sub>2</sub>) is likely to alter the production and activity of fine roots, with important consequences for forest carbon storage. Yet empirical evidence of the role of eCO<sub>2</sub> in driving root dynamics in low-nutrient forested ecosystems is limited, particularly for grassy woodlands, an ecosystem type of global importance.</p> <p>We sampled fine roots across seasons over a two-year period to examine the effects of eCO<sub>2</sub> on their biomass, production, turnover and functional traits in a native mature grassy <i>Eucalyptus</i> woodland in eastern Australia (EucFACE).</p> <p>Fine root biomass, production and turnover varied greatly through time, increasing as soil water content declined. Despite a lack of persistent effects of eCO<sub>2</sub> on fine root biomass, production or turnover across the two-year sampling period, we found enhanced production pulses under eCO<sub>2</sub> between 10-30 cm soil depth. These eCO<sub>2</sub>-driven production pulses were associated with large changes in abiotic conditions. In addition, eCO<sub>2</sub> led to greater carbon and phosphorus concentrations in fine roots and increased root diameter, but no detectable effects on other morphological traits.</p> <p>Synthesis. We found minor quantitative effects of eCO<sub>2</sub> on fine root biomass dynamics that were largely driven by temporal variations in soil water availability. Our results suggest that in this mature grassy woodland, and perhaps also in other similar forested ecosystem types characterized by low phosphorus content in the soil, eCO<sub>2</sub> effects are small and transient. This suggests limited belowground fine root productivity responses to rising atmospheric CO<sub>2</sub> concentrations and, thus, perhaps also a limited ability of these systems to mitigate climate change through belowground mechanisms.</p>
Atmospheric aerosol, gases and meteorological parameters measured during the LAPSE-RATE campaign - Finnish Meteorological Institute data sets
<p>This publication summarizes the measurements and data sets generated by Finnish Meteorological Institute (FMI) during the LAPSE-RATE that took place in the San Luis Valley of Colorado during the summer of 2018. These data sets offer observations of atmospheric aerosols and gases at the surface and in vertical column acquired by FMI rotary-wing Unmanned Aerial System and FMI ground module. </p>
Contrasting aerosol effects on longwave cloud forcing in South East Asia and Amazon simulated with Community Atmosphere Model version 5.3
<p>Aerosols modify cloud microphysical and radiative properties and thus impact the shortwave (SW) and longwave cloud forcing (LWCF). This study first reports the finding of contrasting aerosol effects on LWCF in South East Asia and Amazon in the Community Atmosphere Model version 5.3 (CAM5.3), which corresponds to the sum of LW indirect and semi-direct effects investigated in Ghan et al., (2012). A series of numerical experiments is conducted to decompose the complex aerosol effects on LWCF. Our analysis indicates that the cooling (negative aerosol effects on LWCF) in Amazon is due mainly to the aerosol effects on warm clouds and the inhibition of vertical motion by the aerosol-induced radiative cooling. In contrast, the warming (positive aerosol effects on LWCF) in South East Asia is due mainly to the aerosol effect on homogeneous freezing, thus reducing the ice particle size and prolonging the existence of ice cloud. Our results emphasize that a comprehensive analysis of integrated aerosol effects on both warm and ice clouds is necessary for better understanding the aerosol effects on LWCF.</p>
Data from: Variability of the atmospheric PM10 microbiome in three climatic regions of France
<p>Air pollution is a major public-health concern and it is recognized that particulate matter causes damage to human health through oxidative-stress, being responsible for several million premature deaths worldwide each year. Recent findings showed that, airborne microorganisms/spores can modulate aerosol toxicity by altering the oxidative potential of PM10. Primary Biogenic Organic Aerosols (PBOA) appears to be produced by only few genera of microorganisms, emitted by surrounding vegetation in the case of a regionally-homogeneous field site. This study presents the first comprehensive description of the structure and main sources of airborne microbial communities associated with the temporal trends in PM10 SC concentrations at 3 French sites, under different climates. By combining sugar chemistry and DNA Metabarcoding approaches, we intended to identify PM10-associated microbial communities and their main sources at three climatically different sampling-sites in France during summer 2018. This study accounted also for the interannual variability of the structure of summer airborne microbial community associated with PM10-SC concentrations during a consecutive 2-year survey at one site. Our results showed that the temporal evolutions of SC in PM10 in the three sites are associated with the abundance of only few specific airborne fungal and bacterial taxa. These taxa differ significantly between the 3 climatic regions studied. The structure of microbial communities associated with PM10 SC concentrations during a consecutive 2-year survey remained stable in the rural area. The atmospheric concentration levels of PM10 SC-species vary significantly between the 3 studied sites, but with no clear difference according to site typology (rural vs urban), suggesting that SC emissions are more related to regional climatic characteristics. The overall microbial beta diversity in PM10 samples is significantly different from that of the main vegetation around the studied urban sites. This indicates that airborne microorganisms at such urban sites do not originate only from the immediate surrounding vegetation, which is contrasting with observations at the scale of a regionally homogeneous rural site made in 2017. These results improve our understanding of the spatial behavior of tracers of PBOA emission sources, which need to be better characterized to further implement this important OM-mass fraction into CTM models.</p>
Data from: Climate and atmospheric change impacts on sap-feeding herbivores: a mechanistic explanation based on functional groups of primary metabolites
Global climate and atmospheric change are widely predicted to affect many ecosystems. Herbivorous insects account for 25% of the planet's species so their responses to environmental change are pivotal to how future ecosystems will function. Atmospheric change affects feeding guilds differently, however, with sap-feeding herbivores consistently identified as net beneficiaries of predicted increases in atmospheric carbon dioxide concentrations (eCO2). The mechanistic basis for these effects remains largely unknown, and our understanding about how multiple environmental changes, acting in tandem, shape plant–insect interactions is incomplete. This study investigated how increases in temperature (eT) and eCO2 affected the performance of the pea aphid (Acyrthosiphon pisum) via changes in amino acid concentrations in the model legume, lucerne (Medicago sativa). Aphid performance increased under eCO2 at ambient temperatures, whereby aphid fecundity, longevity, colonization success and rm increased by 42%, 30%, 25% and 21%, respectively. eT negated the positive effects of eCO2 on both fecundity and rm, however, and performance was similar to when aphids were reared at ambient CO2. We identified discrete functional groups of amino acids that underpinned the effects of climate and atmospheric change, in addition to plant genotype, on aphid performance. Effects of eT and eCO2 held true across five M. sativa genotypes, demonstrating the generality of their effects. Combining this knowledge with amino acid profiles of existing cultivars raises the possibility of predicting future susceptibility to aphids and preventing outbreaks of a global pest. Moreover, environmentally induced changes in the nutritional ecology of aphids have the capacity to change life-history strategies of aphids and their direct and indirect interactions with many other organisms, including mutualists and antagonists.
Data from: Impacts of silicon-based grass defences across trophic levels under both current and future atmospheric CO2 scenarios
Silicon (Si) has important functional roles in plants, including resistance against herbivores. Environmental change, such as increasing atmospheric concentrations of CO2, may alter allocation to Si defences in grasses, potentially changing the feeding behaviour and performance of herbivores, which may in turn impact on higher trophic groups. Using Si-treated and untreated grasses (Phalaris aquatica) maintained under ambient (400 ppm) and elevated (640 and 800 ppm) CO2 concentrations, we show that Si reduced feeding by crickets (Acheta domesticus), resulting in smaller body mass. This, in turn, reduced predatory behaviour by praying mantids (Tenodera sinensis), which consequently performed worse. Despite elevated CO2 decreasing Si concentrations in P. aquatica, this reduction was not large enough to affect the feeding behaviour of crickets or their predator. Our results suggest that Si-based defences in plants have adverse impacts on both primary and secondary trophic taxa, and these are not likely to decline under future climate change scenarios.
Data from: Timing of morphological and ecological innovations in the cyanobacteria – a key to understanding the rise in atmospheric oxygen
When cyanobacteria originated and diversified, and what their ancient traits were, remain critical unresolved problems. Here, we used a phylogenomic approach to construct a well-resolved 'core' cyanobacterial tree. The branching positions of four lineages (Thermosynechococcus elongatus, Synechococcus elongatus, Synechococcus PCC 7335 and Acaryochloris marina) were problematic, probably due to long branch attraction artifacts. A consensus genomic tree was used to study trait evolution using ancestral state reconstruction (ASR). The early cyanobacteria were probably unicellular, freshwater, had small cell diameters, and lacked the traits to form thick microbial mats. Relaxed molecular clock analyses suggested that early cyanobacterial lineages were restricted to freshwater ecosystems until at least 2.4 Ga, before diversifying into coastal brackish and marine environments. The resultant increases in niche space and nutrient availability, and consequent sedimentation of organic carbon into the deep oceans, would have generated large pulses of oxygen into the biosphere, possibly explaining why oxygen rose so rapidly. Rapid atmospheric oxidation could have destroyed the methane-driven greenhouse with simultaneous drawdown in pCO(2), precipitating 'Snowball Earth' conditions. The traits associated with the formation of thick, laminated microbial mats (large cell diameters, filamentous growth, sheaths, motility and nitrogen fixation) were not seen until after diversification of the LPP, SPM and PNT clades, after 2.32 Ga. The appearance of these traits overlaps with a global carbon isotopic excursion between 2.2 and 2.1 Ga. Thus, a massive re-ordering of biogeochemical cycles caused by the appearance of complex laminated microbial communities in marine environments may have caused this excursion. Finally, we show that ASR may provide an explanation for why cyanobacterial microfossils have not been observed until after 2.0 Ga, and make suggestions for how future paleobiological searches for early cyanobacteria might proceed. In summary, key evolutionary events in the microbial world may have triggered some of the key geologic upheavals on the Paleoproterozoic Earth.
Temporal and spatial variability of the stable isotopic composition of atmospheric molecular hydrogen: observations at six EUROHYDROS stations
<p>These are the H2 mixing ratio and deuterium content data used in: <br /> Batenburg, A. M., Walter, S., Pieterse, G., Levin, I., Schmidt, M., Jordan, A., Hammer, S., Yver, C., and Röckmann, T.: Temporal and spatial variability of the stable isotopic composition of atmospheric molecular hydrogen: observations at six EUROHYDROS stations, Atmos. Chem. Phys., 11, 6985-6999, doi:10.5194/acp-11-6985-2011, 2011,http://www.atmos-chem-phys.net/11/6985/2011/acp-11-6985-2011.html<br /> <br /> Please cite this ACP article when using these data in a publication, and kindly notify the first author (annekebatenburg'at'gmail.com).<br /> <br /> In the CSV files:<br /> - Mixing ratios are reduction gas analyzer results obtained at UHEI-IUP, MPI-BGC and LSCE.<br /> - dD(H2) data are obtained from analysis with the GC-IRMS system at the IMAU-APCG lab of Utrecht University. The estimated standard deviation/error in a single measurement is 4.5 permil, based on measurements of a laboratory working tank.<br /> - Outlier selection was based on visual inspection of the time series.<br /> - The "biased" or "downshifted" flag indicates dD measurements performed in a period where the dD results seemed to have a positive bias of approximately 9.5 permil. These samples were shown in the time series figure with the 9.5 permil subtracted, but excluded from the following quantitative analyses.<br /> - The last column indicates the number of succesfull repeat measurements of dD.<br /> <br /> More information can be found in the published, open-access article. Please do not hesitate to contact annekebatenburg'at'gmail.com if you have any questions.</p>
Test result data for idealised numerical atmospheric transport
<p>The results of idealised numerical tests of atmospheric flows performed with OpenFOAM.</p>
Impact of horizontal resolution and model time step on European precipitation extremes in the OpenIFS 43r3 atmosphere model
<p>Python scripts used for GMD paper</p>
Fractal geometry features of aerosol particle and its contribution to atmospheric optical property: development of Fractal Aerosol Cluster Model and its validation of atmospheric visibility during a heavy haze event
<p>-------------------------<br>Content of the dataset<br>-------------------------<br>****** the experiment case (EXP) ; the control case (CTR) ******</p> <p>1. Meteorological elements.tar contains observational and simulated data for T2, WS, RH, and PM2.5 time series, which can be used to plot Figure 4 and build Table 2</p> <p>2. Planar distribution.tar contains the horizontal spatial distribution data of aerosol extinction coefficients simulated by CTR and EXP for the four typical moments selected in this paper, which can be used to plot Figures 5, 6, and 7</p> <p>3. PM.rar contains the vertical profile data of simulated Particulate Matter concentrations by CTR and EXP during the study period in the paper, which can be utilized for drawing Fig. 11.</p> <p>4. Timeseries.tar contains observational and simulated data for time series of atmospheric visibility and surface shortwave radiation, which can be used to plot Figures 5, 6, 7, 8, S1, and build Table 3</p> <p>5. wrfbiochemi.rar contains the biogenic emissions data for simulation both for CTR and EXP.</p> <p>6. wrffirechemi.rar contains the biomass burning emissions data for simulation both for CTR and EXP.</p> <p>7. wrfchemi.rar contains the Anthropogenic emissions data for simulation both for CTR and EXP.</p> <p>8. The file module_optical_averaging.F contains the main code of the improved visibility model, the Fractal Aerosol Cluster Model</p> <p>(FACM), which is coupled to WRF-Chem and used by EXP. It is located in the chem/ directory and called by optical_driver.F.</p> <pre> </pre> <p> </p> <p>-------------------------</p> <p>Contact information</p> <p>-------------------------</p> <p> </p> <p>Zhenxin Liu</p> <p>liuzhenxin@nuist.edu.cn</p> <p> </p> <p> </p>
Climate Changes in the Upper Atmosphere: Contributions by the Changing Greenhouse Gas Concentrations and Earth's Magnetic Field
<p>These are data that were used to write the paper: "Climate Changes in the Upper Atmosphere: Contributions by the Changing Greenhouse Gas Concentrations and Earth's Magnetic Field " by Liying Qian, Joseph M. McInerney, Stan S. Solomon, Hanli Liu, Alan G. Burns.</p>
Datasets used in "Large Eddy Simulation for Investigating Coupled Forest Canopy and Turbulence Influences on Atmospheric Chemistry"
<p>Model archived fields used in the generation of the figures in: Clifton, O. E., E. G. Patton, S. Wang, M. Barth, J. Orlando, R. H. Schwantes (2022), Large Eddy Simulation for Investigating Coupled Forest Canopy and Turbulence Influences on Atmospheric Chemistry, Journal of Advances in Modeling Earth Systems.</p>
Atmosphere output of simulations in paper "https://doi.org/10.1029/2023GL107310"
Open the record for dataset details and reuse information.
Atmospheric trace elements in Pudong, Shanghai
Open the record for dataset details and reuse information.
Full-coverage atmospheric CO2 reconstruction data in China from 2010 to 2019
<p>This monthly atmospheric CO2 dataset was reconstructed from GOSAT XCO2 retrievals using a spatiotemporal kriging method. We employed this dataset to investiage the spatiotemporal variation in atmospheric CO2 and its influencing factors. Please the publication as below:</p><p>--Chen, X., He, Q., Ye, T., Liang, Y., & Li, Y. (2023). Decoding spatiotemporal dynamics in atmospheric CO2 in Chinese cities: Insights from satellite remote sensing and geographically and temporally weighted regression analysis. <i>Science of The Total Environment</i>, 167917.</p><p> </p><p>We also share other atmopsheric reconstruction datasets:</p><p>For full-coverage, 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-coverage, 1-km, CO2 data in China, please go to <a href="https://zenodo.org/doi/10.5281/zenodo.10022904">10.5281/zenodo.10022904. </a>This dataset was reconstructed based on OCO-2 XCO2 retrievals and machine learning algorithm.</p><p>For full-covereage, 1-km, PM2.5 data in China, please go to <a href="https://zenodo.org/doi/10.5281/zenodo.8437234">10.5281/zenodo.8437234 or </a><a href="https://zenodo.org/record/8347128">10.5281/zenodo.8347128.</a></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.