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157 results for “Mixing ratio”
Isoprene mixing ratio in ambient air across the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This dataset contains the mixing ratios of isoprene (C5H8) in ambient air measured during the Antarctic Circumnavigation Expedition around the Southern Ocean in the austral summer of 2016/2017 using the iDirac, an autonomous gas chromatograph (Bolas et al., 2020). Samples were collected at a temporal resolution of approximately 10 minutes, with sizeable gaps in the dataset during Legs 1 and 3 due to instrument malfunction.</p> <p>Isoprene represents one of the largest biogenic emissions on the planet. While the magnitude and mechanism of its emissions on land are well established, there is still large uncertainty on the drivers of marine isoprene emissions. This dataset, consisting of continuous measurements at a relatively high temporal resolution, represents a unique opportunity to better understand marine isoprene emissions in the Southern Ocean.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_isoprene_mixing_ratio_ambient_air_v1.1.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> <li>change_log.txt, metadata, text</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - data files updated</p> <ul> <li>more accurate isoprene quantification from improved chromatogram baseline removal</li> </ul> <p>v1.0 - initial release of dataset</p>
Trace gas mixing ratios measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate to be contacted if the data is used for any purpose.</p> <p>We measured mixing ratios of CO, CO<sub>2</sub> and CH<sub>4</sub> with a PICARRO G2401 Gas Analyzer. Ozone (O<sub>3</sub>) mixing ratios were measured with a 2B Technology ozone monitor, model 205. We report five-minute averaged data cleaned from exhaust gas influence. Temporal coverage is from December 20, 2016 to April 10, 2017.</p> <p>The trace gas concentrations represent a large number of atmospheric processes that happen on different time scales. CO for example, has basically no sources other than combustion and can hence be used as tracer for air mass transport from regions with combustion activities (e.g., South Africa). CO has a lifetime of a few weeks. CO<sub>2</sub> and CH<sub>4</sub> are longer-lived trace gases which disperse globally. The data set shows that concentrations in the Northern Hemisphere are higher than in the Southern Hemisphere. Both trace gases are emitted by anthropogenic activities as well as natural sources. Over the cruise track, areas of the Southern Ocean were passed where these trace gases either outgas or are absorbed. Ozone is a secondary trace gas, meaning that it is formed in the atmosphere. It’s concentrations are relatively low.</p> <p>All trace gases data have been cleaned from exhaust gas influence.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_trace_gas_concentration.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> <li>change_log.txt, metadata, text</li> </ul> <p>NaN values denote missing values because of e.g., ship exhaust contamination or instrument maintenance. For latitude and longitude, NaN values are noted in cases where position data was not available for the given time period.</p> <p><strong>Dataset license</strong></p> <p>This trace as mixing ratio dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p> <p><strong>Change log</strong></p> <p>v1.1 - data file updated<br> - Ozone was corrected because a wrong calibration factor was applied in version 1.0<br> - CO2 and CH4 are now dry mixing ratios, the previous data were not corrected for water vapour<br> - README updated accordingly with details of changes to processing<br> - added change_log.txt file</p> <p>v1.0 - initial release of dataset</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (T- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <p> </p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between 575 to 1200 K (applicable for T- type objects). The models for Teff between 275 to 550 K (applicable for Y- type objects) are available in the Zenodo DOI :- <a href="../records/10381250">https://zenodo.org/records/10381250</a>. The models for Teff between 1300 to 2400 K (applicable for L- type objects) are available in the Zenodo DOI :- <a href="../records/10385987">https://zenodo.org/records/10385987</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020</a> HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> PH3 abundance is treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. Therefore in our v2 of this model grid we will further diminish the abundance.</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (L- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <p> </p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between 1300 to 2400 K (applicable for L- type objects). The models for Teff between 275 to 550 K (applicable for Y- type objects) are available in the Zenodo DOI :- <a href="../records/10381250">https://zenodo.org/records/10381250</a>. The models for Teff between 575 to 1200 K (applicable for T- type objects) are available in the Zenodo DOI :- <a href="../records/10385821">https://zenodo.org/records/10385821</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020 </a>HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> In v1, PH3 abundance was treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. In v2 we completely remove the contribution of PH3. </p>
Annual mean TROPOMI-derived ground-level NO2 mixing ratio (2019 - North America v1)
<p>Annual mean ground-level NO2 mixing ratio for 2019 inferred from the TROPOMI satellite instrument over North America at 0.025x0.03125 degree resolution. Included is 2019 annual mean and 1.5 year mean spanning July 2018 – December 2019.</p> <p><strong>Reference:</strong></p> <p>Cooper, M.J., R.V. Martin, C.A. McLinden, and J.R. Brook (2020), Inferring ground-level nitrogen dioxide concentrations at fine spatial resolution applied to the TROPOMI satellite instrument, Env. Res. Lett., DOI:10.1088/1748-9326/aba3a5</p>
Figure 1 in How Spiromesifen affects some biological parameters and switching behavior of predatory mite Amblyseius swirskii (Acari: Phytoseiidae) when feeding on different ratios of mixed preys
Figure 1. Linear relation between initial number of Bemisia tabaci (left)/ Tetranychus urticae (right) treated with recommended concentration of Spiromesifen and number of preys eaten by predatory mite Amblyseius swirskii.
Figure 2 in How Spiromesifen affects some biological parameters and switching behavior of predatory mite Amblyseius swirskii (Acari: Phytoseiidae) when feeding on different ratios of mixed preys
Figure 2. Fitted regression equation between the proportion of consumed mite to total preys and preference index (β) of Amblyseius swirskii.
WV-TTL: water vapor mixing ratio from GEOSCCM and trajectory model simulations in tropical tropopause layer
<p>This dataset includes 100 hPa water vapor mixing ratio simulated from a trajectory transport model and a climate-chemistry model in the tropical tropopause layer from 2005 to 2016 in the format of netCDF. The data are monthly and have three dimensions as lon/lat/time in the unit of parts per million by volume.</p> <p>Also included the tropical average time series of indices for Brewer-Bobson circulation (BDC), tropospheric temperature and/or Quasi-biennial Oscillation (QBO) from ERAi/MERRA-2/GEOSCCM. These indices are used in a multivariate regression.</p>
STRATIFICATION EFFECTS ON FLOW HYDRODYNAMICS AND MIXING AT A CONFLUENCE WITH A HIGHLY DISCORDANT BED AND A RELATIVELY LOW VELOCITY RATIO
<p>The effects of temperature induced stratification on flow hydrodynamics, thermal mixing and the capacity of the flow to entrain sediment at a medium-size stream confluence with a highly discordant bed are investigated. To isolate the effects due to differences in the temperature/density of the incoming streams, two simulations were conducted with identical flow conditions (mean velocity ratio VR=2.44, temperature difference between the two streams ΔT=4.7<sup>0 </sup>C). In the first case the Richardson number was Ri=0 (no coupling between the temperature and the momentum equations via the Boussinesq approximation), while in the second simulation Ri=0.67. Even in the Ri=0 case the structure of the mixing interface (MI) was different from the one expected for concordant bed confluences with a similar confluence angle and VR. The MI contained only co-rotating eddies shed in the shear layer forming on the fast speed side of the confluence apex. In the Ri = 0.67 case no wake region was present but a large recirculation eddy formed not far from the confluence apex. In both cases, the flow near the upstream part of the MI was found to be highly 3D and to allow the passage of particles from one side of the confluence to the other. While in the Ri = 0 case mixing was driven by the MI eddies, in the Ri = 0.67 case mixing was controlled by large near-bed intrusions of heavier fluid from the tributary containing colder water and also by the fluid advected in and out of the recirculation eddy.</p>
MESA histories for "Characterizing Observed Extra Mixing Trends in Red Giants using the Reduced Density Ratio from Thermohaline Models"
<p>This repository provides MESA history files for each of the stellar models in the publication "Characterizing Observed Extra Mixing Trends in Red Giants using the Reduced Density Ratio from Thermohaline Models". The MESA version used was stable release version 21.12.21. Runs are organized into tarballs according to the thermohaline mixing prescription used:</p> <ul> <li>BGS13 = Brown, Garaud, Stellmach 2013</li> <li>Kipp1e-1 = Kippenhahn with alpha_th = 0.1</li> <li>Kipp2 = Kippenhahn with alpha_th = 2</li> <li>Kipp7e2 = Kippenhahn with alpha_th = 700</li> </ul> <p>and are additionally grouped according to the stellar mass (M = 0.9, 1.1, 1.3, 1.5, 1.7 in units of Msol). Within each tarball is a number of run directories which contain a LOGS/history.data file from the MESA run. The subdirectories in the tarball contain runs at various metallicities; conversion between Z (MESA input) and [Fe/H] (paper reported value) are found in Table 2 of the manuscript.<br> <br> Inlists and information for recreating these MESA simulations can be found online at the paper's github repository: <a href="https://github.com/afraser3/Empirical-Magnetic-Thermohaline">https://github.com/afraser3/Empirical-Magnetic-Thermohaline</a> (a copy of the code from this Github repository is located in this Zenodo repository in: Empirical-Magnetic-Thermohaline-main.zip)</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (Y- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between Teff of 275 to 550 K (applicable to Y-type objects). The models for Teff between 575 to 1200 K (applicable for T- type objects) are available in the Zenodo DOI :- <a href="../records/10385821">https://zenodo.org/records/10385821</a>. The models for Teff between 1300 to 2400 K (applicable for L- type objects) are available in the Zenodo DOI :- <a href="../records/10385987">https://zenodo.org/records/10385987</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020</a> HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> PH3 abundance is treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. Therefore in our v2 of this model grid we will further diminish the abundance.</p>
CO and CO2 mixing ratios and flux measurements from the Amazon tropical rainforest
<p>CO and CO2 mixing ratio and flux measurements from the Amazon tropical rainforest</p><p>This dataset belongs to the manuscript 'The emission of CO from tropical rain forest soils', submitted to the journal Biogeosciences in December 2023.</p><p>More details on this dataset can be found in this manuscript:</p><p>https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2746/egusphere-2023-2746.pdf</p><p> For questions, please reach out to Hella van Asperen: hasperen@bgc.mpg-jena.de</p><p>########################################</p><p>Plateau tower CO and CO2 mixing ratio measurements</p><p>Plateau tower CO and CO2 mixing ratio measurements took place in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021) at the K34 tower at field site ZF2 in the Amazon rain forest (-2.60898, -60.209106). Due to a problem in the beginning of the dry season campaign, the measurements at the tower were continued until outside the campaign period, until 18 October 2020. Measurements were performed by a Spectronus FTIR analyzer. Concentrations were measured at 3 heights (5,15 and 36m) every half hour. Canopy height is ~28m.</p><p>########################################</p><p>Valley CO and CO2 mixing ratio measurements</p><p>Valley CO and CO2 mixing ratio measurements took place in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021) at a valley close to the K34 tower at field site ZF2 (-2.600026, -60.217079). Since no electricity was available, automatic battery-driven bag sampling was performed during the night at 3h time intervals, with 4 measurements per night from a 1m height inlet (~18:00, ~21:00, ~0:00, ~3:00). Bag samples were measured the following morning by a Spectronus FTIR-analyzer. </p><p>########################################</p><p>Plateau and valley chamber CO and CO2 fluxes</p><p>Flux chamber measurements were performed over soil and litter together on the plateau and in the valley at field site ZF2, in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021). Five soil collars were installed in the valley, and five on the plateau. Each collar was measured 3 times during each campaign week (on different days). Measurements from the same collar are indicated as (for example) V1A, V1B, V1C. After each flux chamber measurement, soil moisture and soil temperature was measured.</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 20 g per s and a Mixing Ratio of 95 vs. 5 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</p> <p> </p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 15 g per s and a Mixing Ratio of 10 vs. 90 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 15 g per s and a Mixing Ratio of 50 vs. 50 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Develo</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 10 g per s and a Mixing Ratio of 90 vs. 10 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 10 g per s and a Mixing Ratio of 75 vs. 25 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 10 g per s and a Mixing Ratio of 95 vs. 5 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 15 g per s and a Mixing Ratio of 95 vs. 5 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</p>
Images of Construction and Demolition Waste Consting of Brick and Sand-lime Brick Transported on a Conveyor Belt - Recording with a Mass Flow of 20 g per s and a Mixing Ratio of 90 vs. 10 %
<p>This data set comprises images of bulk material of brick and sand-lime brick on a conveyor belt. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden,Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer</em>, <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>,Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/insideschuettgut">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings of construction and demolition waste consisting of brick and sand-lime brick on optical sorters. Please use the search function with the keywords "Images of Construction and Demolition Waste" (in quotes) to find them. The data set was recorded with a Bonito CL-400C. Please see the debayer script on GitHub <a href="https://github.com/geomai/debayer_bonito">https://github.com/geomai/debayer_bonito</a>. The frame rate is approximately 192 Hz.</p> <p><br> To this date, publications that used this data include</p> <ul> <li><em>Marcel Reith-Braun, Albert Bauer, Maximilian Staab, Florian Pfaff, Georg Maier, Robin Gruna, Thomas Längle, Jürgen Beyerer, Harald Kruggel-Emden and Uwe D. Hanebeck</em>, <strong>GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs</strong>, 22nd IFAC World Congress, Yokohama, Japan, July 2023.</li> </ul> <p><strong>Acknowledgment</strong><br> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Climate Action on the basis of a resolution of the German Bundestag.</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.