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1,574 results for “atmospheres”
Data from: The experimental manipulation of atmospheric drought: Teasing out the role of microclimate in biodiversity experiments
<p class="MsoNormal">Climate change alters mean global surface temperatures, precipitation regimes, and atmospheric moisture. Resultant drought affects the composition and diversity of terrestrial ecosystems worldwide. To date, there are no assessments of the combined impacts of reduced precipitation and atmospheric drying on functional trait distributions of any species in an outdoor experiment. Here, we examined whether soil and atmospheric drought affect the functional traits of a focal grass species (<em>Poa secunda)</em> growing in monoculture and 8-species grass communities in outdoor mesocosms. We focused on specific leaf area (SLA), leaf area, stomatal density, root:shoot ratio, and fine root:coarse root ratio responses. Leaf area and overall growth were reduced with soil drying. Root:shoot ratio only increased for <em>P. secunda</em> growing in monoculture under combined atmospheric and soil drought. Plant energy allocation strategy (measured using principal components) differed when <em>P. secunda</em> was grown in combined soil and atmospheric drought conditions compared with soil drought alone. Given a lack of outdoor manipulations of this kind, our results emphasize the importance of atmospheric drying on functional trait responses more broadly. We suggest that drought methods focused purely on soil water inputs may be imprecisely predicting drought effects on other terrestrial organisms as well (other plants, arthropods, and higher trophic levels).</p>
INEMA: High resolution inventory of atmospheric emissions of Chile
<p><strong>Brief description</strong></p> <p>This study presents the first high-resolution national inventory of anthropogenic emission for Chile (INEMA from spanish Inventario Nacional de EMisiones Antropogénicas). INEMA emission dataset considers emissions for Vehicular, point sources (industrial, energy, and other sectors), residential, forest fires, and agricultural waste burning sectors estimated for 2015–2020 and spatially distributed onto a 0.01°x0.01° high-resolution grid. For all sectors, the pollutants included are CO2, NOx, SO2, CO, VOCs, NH3, PM10, and PM2.5. Also, CH4, N2O, and black carbon (BC) are included for transport, forest fires, agricultural waste burning, and residential sources.</p> <p>Emissions are classified on IPCC categories:</p> <table> <tbody> <tr> <td>Sector</td> <td>IPCC codes</td> </tr> <tr> <td>Energy production</td> <td>1A1</td> </tr> <tr> <td>Industrial Energy consumption</td> <td>1A2</td> </tr> <tr> <td>On road transport energy consumption</td> <td>1A3b</td> </tr> <tr> <td>Comercial energy consumption</td> <td>1A4a</td> </tr> <tr> <td>residential firewood consumption</td> <td>1A4b</td> </tr> <tr> <td>Agriculture energy consumption</td> <td>1a4c</td> </tr> <tr> <td>Industrial processes</td> <td>2</td> </tr> <tr> <td>Agriculture waste burning</td> <td>3F</td> </tr> <tr> <td>Forest fires</td> <td>4A1b.iii</td> </tr> </tbody> </table> <p>This work compiles new activity data and emissions factors and distributes them geographically based on census, Chile´s road network and CONAF information. To consult the main methodological considerations and results of the previous version of INEMA, review the article by Alamos et al.(2022).</p> <p>This inventory should contribute to the design of policies that seek to mitigate climate change and improve air quality by providing policy makers, stakeholders and scientists with qualified scientific spatial explicit emission information.</p> <p><strong>Metadata</strong></p> <p>Each .tar file contain netcdf (.nc) files for each pollutant of the sector and year of the .tar file. Netcdf contains annual total emissions for the pollutant and year indicated per grid cell </p> <p>The emission grid consists of Chilean territory in WGS84 projection (lon-lat) with a spatial resolution of 0.01 * 0.01 degrees (lon x lat). The extension boundaries of the grid are: [(-76-56.3), (-66,-17)]</p> <p>The unit in the .nc files is Gigagrames per year [Gg/year]</p> <p><strong>The dataset is described in </strong></p> <p>Álamos, N., Hunneus, N., Opazo, M., Osses, M., Puja, S., Pantoja, N., Calvo, R., Denier Van Der Gon, H.A.C., Schueftan, A., Reyes, R., High-resolution inventory of atmospheric emissions from transport, industrial, energy, mining and residential activities in Chile. <em>Earth System Science Data</em>, <em>14</em>(1), 361-379. 2022</p> <p> </p>
20th Century Atmospheric River Archive for Western North America and Europe
<p><strong>General Description</strong></p> <p>This datasets provides 6-hourly instantaneous atmospheric river absence-presence time series for 13 sub-regions along the coastlines of Western North America and Europe, as well the corresponding Integrated Water Vapor (IVT) values and exceeded climatological quantiles. These data were retrieved from 3 distinct reanalyses:</p> <p>1. ERA-20C, 1900-2010, 1.125 degrees resolution, here termed "era20c"</p> <p>2. NOAA-CIRES 20th Century Reanalysis version 2, 1900-2012, 2 degrees resolution, here termed "c20", ARs were retrieved from instantaneous ensemble-mean data.</p> <p>3. ECMWF ERA-Interim, 1979-2014, 0.75 degrees resolution, here termed "interim"</p> <p>The file structure is as in this example:</p> <p>ar_Brands_v0_interim_scalifornia_JFMAOND_1979_2014.nc</p> <p>translates to:</p> <p>ar_<algorithm name>_<version>_<underlying dataset>_<target region as illustrated in fig_studyregions.pdf>_<considered months>_<start year>_<end_year>.nc</p> <p>The 13 study regions are indicated in <fig_studyregions.pdf> attached below and described in Brands et al. (2017). The lat-lon coordinates of each region are provided in the netCDF files.</p> <p>For western North America and Europe the October-through-April and October-through-March season is covered, respectively. The compressed netCDF4 files offered here come with detailed metadata information. For generating the present dataset, the initial version of the AR detection and tracking algorithm developed in my PhD thesis was used (here referred to as version 0, see Brands et al. 2017 for a full description). Although newer algorithm versions have become available in the framework of the Atmospheric River Method Intercomparison Project (ARTMIP, see Rutz et al. 2019), the initial version 0 was specifically developed for detecting landfalling ARs along the coastlines of Western North America and Europe. The correct functioning was supervised by eye for hundreds, if not thousands of cases.</p> <p>The 9 distinct AR detection and tracking methods contained in each netCDF file (coined "method 0,1...8" in there) use distinct climatological percentile thresholds to 1) detect ARs along the coastline (the detection percentile, termed "prct_detect") and then "crawl" upwards the flow guided by the strongest IVT above the tracking percentile ("prct_track") and by the respective U and V components until a minimum length of 2000 km is reached. The results obtained from the 9 methods thus differ in AR intensity.</p> <p>The netCDF files of the present dataset have been recompiled from the non-standard .mat files generated in my PhD thesis during the years 2013-2017. For the target regions in Europe, the content of the present dataset partly overlaps with the non-standard dataset previously published at http://dx.doi.org/10.13140/RG.2.2.14711.32160. The target regions in western North America have been newly included and are only available from the present dataset.</p> <p>Contact: Swen Brands, brandssf@ifca.unican.es</p> <p> </p> <p><strong>References</strong></p> <p>Brands, S., Gutiérrez, J.M. & San-Martín, D. (2017). Twentieth-century atmospheric river activity along the west coasts of Europe and North America: algorithm formulation, reanalysis uncertainty and links to atmospheric circulation patterns. <em>Climate Dynamics</em> 48, 2771–2795. https://doi.org/10.1007/s00382-016-3095-6</p> <p>Compo, G.P., Whitaker, J.S., Sardeshmukh, P.D., Matsui, N., Allan, R.J., Yin, X., Gleason, B.E., Vose, R.S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R.I., Grant, A.N., Groisman, P.Y., Jones, P.D., Kruk, M.C., Kruger, A.C., Marshall, G.J., Maugeri, M., Mok, H.Y., Nordli, Ø., Ross, T.F., Trigo, R.M., Wang, X.L., Woodruff, S.D. and Worley, S.J. (2011), The Twentieth Century Reanalysis Project. <em>Q.J.R. Meteorol. Soc.</em>, 137: 1-28, https://doi.org/10.1002/qj.776</p> <p>Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-.-J., Park, B.-.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. <em>Q.J.R. Meteorol. Soc.</em>, 137: 553-597, https://doi.org/10.1002/qj.828</p> <p>Poli, P., and Coauthors, 2016: ERA-20C: An Atmospheric Reanalysis of the Twentieth Century. <em>J. Climate</em>, 29, 4083–4097, https://doi.org/10.1175/JCLI-D-15-0556.1</p> <p>Rutz, J. J., Shields, C. A., Lora, J. M., Payne, A. E., Guan, B., Ullrich, P., et al. (2019). The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying uncertainties in atmospheric river climatology. <em>Journal of Geophysical Research: Atmospheres</em>, 2019; 124: 13777– 13802. https://doi.org/10.1029/2019JD030936</p>
Dataset for large-scale self-organisation in dry turbulent atmospheres
<p>Datasets for all figures in "Large-scale self-organisation in dry turbulent atmospheres". The data comes from a simulation of the Boussinesq equations in a triply periodic domain of vertical height H and horizontal dimension L = 32H, in the presence of gravity, a stable mean density gradient, and solid body rotation in the vertical direction. Datasets are in TXT format except for two dimensional spectra, which are stored in NetCDF format.</p>
First Atmospheric Measurements and Emission Estimates of HFO-1336mzz(Z)
<p>Atmospheric measurement data (mole fractions) for HFO-1336mzz(Z) (((<em>Z</em>)-1,1,1,4,4,4-hexafluoro-2-butene, <em>cis</em>-CF<sub>3</sub>CH=CHCF<sub>3</sub>). The data are related to article in ES&T (<a href="https://doi.org/10.1021/acs.est.3c01826">https://doi.org/10.1021/acs.est.3c01826</a>). Observations were made at the sites Beromünster (CH), Sottens (CH), Dübendorf (CH), Jungfraujoch (CH), and Cabauw (NL). Measurements were conducted using Medusa pre-concentration units coupled to gas chromatography and mass spectrometry (GC-MS), as is used within the global AGAGE network.</p>
Model simulation data used in "The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)" (Righi et al., Earth Syst. Dynam., 2023)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Earth Syst. Dynam.</i>, 2023). For details see the README.md file.</p>
Dataset for combined influences of sources and atmospheric bleaching on light absorption of water-soluble brown carbon aerosols
<p>This dataset provides the mass-absorption cross section at 365 nm and the corresponding absorption Ångström exponent, carbon isotope (13C and 14C) signature of water-soluble organic carbon, and OC, EC and WS-BrC concentration for aerosol samples collected in East Asia. The PM2.5 samples were collected simultaneously during the winter period (January 2014) from the representative hotspot regions of BrC emissions in E. Asia, including in the Beijing-Tianjin-Hebei (BTH) area, Yangtze River Delta (YRD), Pearl River Delta (PRD), Sichuan (SC) province and SE Yellow Sea regional receptor site — the Korea Climate Observatory at Gosan (KCOG). The earlier published data in E. and S. Asia, such as KCOG, urban city Delhi, Bangladesh Climate Observatory at Bhola Island (BCOB) in the outflow region of the Indo-Gangetic Plain and Maldives Climate Observatory at Hanimaadhoo Island (MCOH) in the Indian Ocean are from corresponding references (see the annotation in each sheet).</p> <p>Please cite Wenzheng Fang, August Andersson, Meehye Lee, Mei Zheng, Ke Du, Sang-Woo Kim, Henry Holmstrand and Örjan Gustafsson (2023): Combined influences of sources and atmospheric bleaching on light absorption of water-soluble brown carbon aerosols. npj Climate and Atmospheric Science. </p>
Data of "High concentration of atmospheric sub-3 nm particles in polluted environment of eastern China: new particle formation and traffic emission"
<p>The attached data is the measurement data at SORPES station in Yangtze Rive Delta of China. The data is for analysis and figures in the study of "High concentration of atmospheric sub-3 nm particles in polluted environment of eastern China: new particle formation and traffic emission". Currently the manuscript is submitted to JGR-A.</p>
Simulated top-of-atmosphere (120 km) downward and upward solar and thermal-infrared irradiances and ice cloud optical thickness; calculated solar, TIR and net cloud radiative effect. Simulated with ice crystal properties for aggregates, droxtals, and plates based on Yang (2013).
<p>This dataset consists of three .nc files for ice crystal shapes of aggregates, plates, and droxtals. The files include ice cloud optical thickness <span class="math-tex">\(\tau\)</span> (550nm), the simulated upward and downward irradiances <span class="math-tex">\(F\)</span> at the top-of-atmosphere (with and without the presence of the ice cloud), and the calculated ice cloud radiative effect <span class="math-tex">\(\Delta F\)</span> (solar [0.3-3.5 <span class="math-tex">\(\mu\)</span>m], thermal-infrared [3.5-75 <span class="math-tex">\(\mu\)</span>m], and net). The data set allows the user to extract <span class="math-tex">\(\Delta F\)</span> values for their parameter combinations. The available cloudy and cloud-free irradiances further allow to calculate the cirrus radiative effect (RE) by scaling the 'cloudy' RE with the required cloud cover. This serves as a first-approximation because, as 3D effects are neglected.</p>
PALM Model System v 6.0 input and configuration files for coupled large eddy simulations of land surface heterogeneity effects and diurnal evolution of late summer and early autumn atmospheric boundary layers during the CHEESEHEAD19 field campaign
<p>Namelist, configuration and forcing files for the PALM Model System 6.0 revision number 21.10-rc.2 used for the numerical simulations Coupled Large Eddy Simulations of land surface heterogeneity induced atmospheric boundary layer response during the CHEESEHEAD19 field campaign.</p>
Data from: River interlinking alters land-atmosphere feedback and changes the Indian summer monsoon.
<p>The dataset contains post-processed output from two experiments performed for Indian Summer Monsoon (June-September) from 1991-2012 using WRF-CLM4: CTL and IRR. Here, CTL represents WRF-CLM4 simulation with irrigation currently practiced in India. We use a modified irrigation module in CLM4 that better represents the Indian practices of irrigation by incorporating groundwater withdrawal and flood irrigation practiced over paddy fields. The module can be found at <a href="https://github.com/IMMM-SFA/WRF_CLM4_Irrigation">https://github.com/IMMM-SFA/WRF_CLM4_Irrigation</a> and <a href="https://doi.org/10.1029/2019GL083875">https://doi.org/10.1029/2019GL083875</a>. IRR simulation adds additional irrigation to CTL by increasing the percentage of irrigated area to 80% in regions where India's river-interlinking projects target an increase in the culturable command area.</p> <p>The post-processed output contains the following variables:</p> <ol> <li>Mean Daily Temperature</li> <li>Daily Maximum Temperature</li> <li>Latent Heat Flux</li> <li>Sensible Heat Flux</li> <li>Relative Humidity</li> <li>U-Wind at Pressure levels</li> <li>V-Wind at Pressure levels</li> <li>Net-Solar Radiation on Land</li> <li>Soil Moisture</li> </ol> <p>Irrigation input files for CTL and IRR simulations of WRF-CLM4 are also included.</p>
Jupiter Atmospheric Models and Outer Boundary Conditions for Giant Planet Evolutionary Calculations
<p>This data set consists of 1D radiative-convective equilibrium boundary conditions for Jupiter-like giant planets, computed using coolTLUSTY and a recently updated set of molecular absorption cross sections. Models span internal temperatures of 80 - 450 K, and surface gravities of log10(g / [cm/s^2]) = 1.8 - 3.6. The planet is irradiated by a black body star at a distance of 5.2AU with effective temperature of 5777K with the zenith angle factor (accounting for an average incident angle) being FACFLX=0.5 or 0.67. The models assume a composition of 3.16x solar abundance, and allow the formation of ammonia clouds at low temperatures with characteristic sizes of 1 or 3 micron. More numerical details on the treatments of irradiation and clouds can be found in "Jupiter Atmospheric Models and Outer Boundary Conditions for Giant Planet Evolutionary Calculations", arXiv number TBA.</p> <p>See README.txt for a description of data formats.</p>
Atmospheric observations of SF6, HFC-32, HFC-125, and HFC-134a at Sottens, Switzerland
<p>Atmospheric measurement data (mole fractions) for SF<sub>6</sub> (sulfur hexafluoride), HFC-32 (difluoromethane), HFC-125 (1,1,1,2,2-pentafluoroethane), and HFC-134a (1,1,1,2-tetrafluoroethane). Observations were made at Sottens, Switzerland, in 2021. Measurements were conducted using a Medusa pre-concentration unit coupled to gas chromatography and mass spectrometry (GC-MS), as is used within the global AGAGE network.</p>
Data & figures: Comparison between Large-Scale Observed and Simulated Antarctic Sea-Ice Variability Response to Changes in Atmospheric and Oceanic Circulation
<p>These are the model data, key figures, and Python code generated during the project titled “Comparison between Large-Scale Observed and Simulated Antarctic Sea-Ice Variability Response to Changes in Atmospheric and Oceanic Circulation." This project was undertaken during a 3-month research scholarship at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, funded by the Helmholtz Visiting Researcher Grant, a program promoted by the Helmholtz Information and Data Science Academy (HIDA). Statistical methods pertain to the coupling of sea surface temperature and Antarctic sea-ice interactions. These methods can be applied to observations, reanalysis, and earth system model data</p>
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15
"The place where Idid record the sound "saunan lämmitys" is our family's summerhouse. My father bought it year 1955. He was born nearby in Virojoki village in 1911 and passed away in 2003. As you know Sauna a is very relaxing and important thing to Finns. We like the warm and silence of sauna atmosphere and heating the sauna is almost religious to us. For me it is remembering moments Ispent with my dead father and other relatives. Iam 56 years old internist and living 600 km away from that place but still I visit there for about 2 months yearly." [Timo/timofei]14 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"The place where Idid record the sound "saunan lämmitys" is our family's summerhouse. My father bought it year 1955. He was born nearby in Virojoki village in 1911 and passed away in 2003. As you know Sauna a is very relaxing and important thing to Finns. We like the warm and silence of sauna atmosphere and heating the sauna is almost religious to us. For me it is remembering moments Ispent with my dead father and other relatives. Iam 56 years old internist and living 600 km away from that place but still I visit there for about 2 months yearly." [Timo/timofei]14
Data and scripts for GRL article: Author's reply to Comment by Greaves et al. on ``Phosphine in the Venusian Atmosphere: A Strict Upper Limit from SOFIA GREAT Observations''
<p>Python scripts and raw SOFIA Data to reproduce the figures found in GRL article: Author's reply to Comment by Greaves et al. on ``Phosphine in the Venusian Atmosphere: A Strict Upper Limit from SOFIA GREAT Observations''</p>
Direct evidence for atmospheric carbon dioxide removal via enhanced weathering in cropland soil: Supporting data
<p>Datasets (climate, alkalinity, moisture sensors) associated with the manuscript "Direct evidence for atmospheric carbon dioxide removal via enhanced weathering in cropland soil."</p>
Data associated with: Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water
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Data for: The Martian atmospheric waves perturbation Datasets (MAWPD) version 2.0
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