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10,016 results for “Observation”
Observations of trace gases in the lowermost stratosphere and upper troposphere from the SPURT aircraft measurement program
<p><strong>Introduction</strong></p> <p>SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) was an aircraft measurement program funded by the AFO 2000 programme of the German Ministry for Education and Research (BMBF). Eight campaigns (36 flights in total) were conducted between November 2001 and July 2003 to investigate trace gas transport in the extratropical upper troposphere and lowermost stratosphere in all seasons. A wide range of trace gases with different lifetimes and sink/source characteristics were measured in-situ from a Learjet 35A aircraft flying at altitudes up to 13.7 km. The data set is well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the upper troposphere and lowermost stratosphere as demonstrated in numerous accompanying studies.</p> <p><strong>Dataset content</strong></p> <ol> <li>In-situ measurements of N<sub>2</sub>O, CH<sub>4</sub>, CO, CO<sub>2</sub>, CFC12, H<sub>2</sub>, SF<sub>6</sub>, NO, NO<sub>y</sub>, O<sub>3</sub> and H<sub>2</sub>O along all flight tracks.</li> <li>Position and meteorological quantities recorded by the aircraft along all flight tracks.</li> <li>Meteorological data from ECMWF analysis fields and derived products such as potential vorticity and equivalent latitude interpolated to all flight tracks.</li> <li>Merge files (extension .mrg) of all observations, aircraft positions and other data merged into one single file per flight at 5 sec temporal resolution. Due to different instrument response times or computer clocks, the individual measurements were typically shifted by several seconds relative to each other. These time shifts are corrected for in the merge files.</li> <li>Ten day backward trajectories started every 12 minutes along the flight tracks computed with <em>Lagranto</em> (<a href="https://dx.doi.org/10.5194/gmd-8-2569-2015">doi:10.5194/gmd-8-2569-2015</a>) based on 3-hourly ECMWF IFS analysis/forecast fields.</li> <li>Further information such as flight quicklooks, flight protocols, meteorological reports, etc.</li> </ol> <p>All measurement data are provided in NASA/Ames format (<a href="https://espo.nasa.gov/content/Ames_Format_Specification_v20">https://espo.nasa.gov/content/Ames_Format_Specification_v20</a>), which is a self-explaining ASCII format that can conveniently be read by many software packages, e.g. the nappy library for python.</p> <p><strong>Quick start guide</strong></p> <ol> <li>Download and unpack the gzip compressed tar file (unpacking generates the two directories <em>images </em>and <em>data</em>)</li> <li>Change to the directory <em>data </em>and open the file index.html with a web browser. This will open a web page providing an overview of the eight campaigns and associated data.</li> <li>For most purposes it will be sufficient to work with the merge files: Change to the <em>data</em> directory and list all merge files by typing "ls */*/*.mrg" (Linux) or "dir *\*\*.mrg" (Windows).</li> </ol> <p> </p> <p><strong>References:</strong></p> <p>The reference journal article for the SPURT project is</p> <p><em>Engel, A., Bönisch, H., Brunner, D., Fischer, H., Franke, H., Günther, G., Gurk, C., Hegglin, M., Hoor, P., Königstedt, R., Krebsbach, M., Maser, R., Parchatka, U., Peter, T., Schell, D., Schiller, C., Schmidt, U., Spelten, N., Szabo, T., Weers, U., Wernli, H., Wetter, T., and Wirth, V.: Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the Spurt project: an overview, Atmos. Chem. Phys., 6, 283–301, https://doi.org/10.5194/acp-6-283-2006, 2006. </em></p> <p>Many more scientific publications emerged from the project (see reference list and object identifiers).</p>
Bayesian Analysis for Remote Biosignature Identification on exoEarths (BARBIE) I: Using Grid-Based Nested Sampling in Coronagraphy Observation Simulations for H2O
<p>We present all of the data across our SNR and abundance study for the molecule H2O for an exoEarth twin. The wavelength range is from 0.515-1 micron, with 25 evenly spaced 20% bandpasses in this range. The SNR ranges from 3-16, and the abundance values range from log10(VMR) = -3.5 to -1.5 in steps of 0.5 and 0.25 (all presented in VMR in the associated table). We present the lower and upper wavelength per bandpass, the input H2O value (abundance case), the retrieved H2O value (presented as the log10(VMR)), the lower and upper limits of the 68% credible region (presented as the log10(VMR)), and the log-Bayes factor for H2O. For more information about how these were calculated, please see Bayesian Analysis for Remote Biosignature Identification on exoEarths (BARBIE) I: Using Grid-Based Nested Sampling in Coronagraphy Observation Simulations for H2O, accepted and currently available on arXiv. </p> <p>To open this csv as a Pandas dataframe, use the following command:</p> <p>your_dataframe_name = pd.read_csv(f'zenodo_table.csv', dtype={'Input H2O': str})</p>
High-resolution surface wind observations over complex terrain: Big Southern Butte, Salmon River Canyon, Birch Creek
<p>This dataset contains high-resolution wind observations from three field campaigns that took place during 2010-2014 at Big Southern Butte, Salmon River Canyon, and Birch Creek, Idaho. There are three SQLite databases containing 30-s averaged 3-m wind speed, wind direction, and wind gust data from 30-90 cup-and-vane anemometers over a period of 2-4 months at each field site.</p>
Data and Supplementary Material for "Insights into Lightning K-Leader Initiation and Development from Three Dimensional Broadband Interferometric Observations" by Jensen et al.
<p>Data and Supplementary Material for the manuscript “Insights into Lightning K-Leader Initiation and Development from Three Dimensional Broadband Interferometric Observations” by Jensen et al., submitted to Journal of Geophysical Research: Atmospheres. Further description in included PDF (01file_description.pdf)</p>
Airborne Infrasound Data from The AtmoSOFAR Channel: First Direct Observations of an Elevated Acoustic Duct
<p>Airborne infrasound data including waveform recordings from two payloads attached to a single 6 m heliotrope that was launched at dawn (~0700 local) out of Belen Regional Airport, NM, USA. Balloon trajectory is also included. This data accompanies the publication titled, "The AtmoSOFAR Channel: First Direct Observations of an Elevated Acoustic Duct" submitted to Earth & Space Science.</p>
List of Electron Diffusion Regions (EDR) observed by NASA/MMS
<p><strong>List of Electron Diffusion Regions (EDR) during the phases 1a & 1b of the NASA/MMS mission.</strong><br> EDR from Lenouvel_et_al._[2021] and Lenouvel_(unpublished) were detected with two distinct machine learning algorithms. The first algorithm (MLP) is detailed in Lenouvel_et_al._[2021]. Both algorithms (MLP and CNN) are described in Q. Lenouvel's PhD manuscript and in "Advanced Methods for Analyzing In-Situ Observations of Magnetic Reconnection" submitted to Space Science Reviews by Hasegawa et al..<br> For completeness, other EDR events reported in the literature are added to the list. All references are given below. Note that some events were observed by other MMS spacecraft at slightly different times.</p> <p>Burch, J. L., and T. D. Phan, Magnetic reconnection at the dayside magnetopause: Advances with MMS, Geophysical Research Letters, 43 (16), 8327–8338, https://doi.org/10.1002/2016GL069787, 2016.<br> Burch, J. L., et al., Electron-scale measurements of magnetic reconnection in space, Science, 352 (6290), aaf2939, https://doi.org/10.1126/science.aaf2939, 2016.<br> Chen, L.-J., et al., Electron energization and mixing observed by mms in the vicinity of an electron diffusion region during magnetopause reconnection, Geophysical Research Letters, 43 (12), 6036–6043, https://doi.org/10.1002/2016GL069215, 2016.<br> Chen, L.-J., et al., Electron diffusion region during magnetopause reconnection with an intermediate guide field: Magnetospheric multiscale observations, Journal of Geophysical Research: Space Physics, 122 (5), 5235–5246, https://doi.org/10.1002/2017JA024004, 2017.<br> Cozzani, G., et al., In situ spacecraft observations of a structured electron diffusion region during magnetopause reconnection, Phys. Rev. E 99, 043204 (2019); https://doi.org/10.1103/PhysRevE.99.043204<br> Dong, X.-C., et al., Observation of nonuniform energy dissipation in the electron diffusion region of magnetopause reconnection, Geophysical Research Letters, 48 (13), e2020GL091928, https://doi.org/10.1029/2020GL091928, 2021.<br> Ergun, R. E., et al., Drift waves, intense parallel electric fields, and turbulence associated with asymmetric magnetic reconnection at the magnetopause, Geophysical Research Letters, 44 (7), 2978–2986, https://doi.org/10.1002/2016GL072493, 2017.<br> Eriksson, S., et al., Magnetospheric multiscale observations of the electron diffusion region of large guide field magnetic reconnection, Phys. Rev. Lett., 117, 015,001, https://doi.org/10.1103/PhysRevLett.117.015001, 2016.<br> Fuselier, S. A., et al., Large-scale characteristics of reconnection diffusion regions and associated magnetopause crossings observed by mms, Journal of Geophysical Research: Space Physics, 122 (5), 5466–5486, https://doi.org/10.1002/2017JA024024, 2017.<br> Genestreti, K. J., et al., Mms observation of asymmetric reconnection supported by 3-d electron pressure divergence, Journal of Geophysical Research: Space Physics, 123 (3), 1806–1821, https://doi.org/10.1002/2017JA025019, 2018.<br> Graham, D. B., et al., Instability of agyrotropic electron beams near the electron diffusion region, Phys. Rev. Lett., 119, 025,101, https://doi.org/10.1103/PhysRevLett.119.025101, 2017.<br> Khotyaintsev, Y. V., et al., Electron jet of asymmetric reconnection, Geophysical Research Letters, 43 (11), 5571–5580, https://doi.org/10.1002/2016GL069064, 2016.<br> Lenouvel, Q., Identification par apprentissage machine et analyse de régions de diffusion électronique à la magnétopause terrestre observées par MMS, Thèse de doctorat en Astrophysique, Sciences de l'Espace, Planétologie, Université de Toulouse, http://thesesups.ups-tlse.fr/5558/, 2022.<br> Lenouvel, Q., et al., Identification of electron diffusion regions with a machine learning approach on mms data at the earth’s magnetopause, Earth and Space Science, 8 (5), e2020EA001530, https://doi.org/10.1029/2020EA001530, 2021.<br> Li, W. Y., et al., Electron Bernstein waves driven by electron crescents near the electron diffusion region, Nature Communications, 11 (1), 141, https://doi.org/10.1038/s41467-019-13920-w, 2020.<br> Norgren, C., et al., Finite gyroradius effects in the electron outflow of asymmetric magnetic reconnection, Geophysical Research Letters, 43 (13), 6724–6733, https://doi.org/10.1002/2016GL069205, 2016.<br> Phan, T. D., et al., Mms observations of electron-scale filamentary currents in the reconnection exhaust and near the x line, Geophysical Research Letters, 43 (12), 6060–6069, https://doi.org/10.1002/2016GL069212, 2016.<br> Webster, J. M., et al., Magnetospheric Multiscale Dayside Reconnection Electron Diffusion Region Events, Journal of Geophysical Research (Space Physics), 123 (6), 4858–4878, https://doi.org/10.1029/2018JA025245, 2018.</p> <p> </p>
Supplement to "Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: A comprehensive long-term dataset of remote sensing observations"
<p>This dataset is a supplement to "Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: A comprehensive long-term dataset of remote sensing observations", available at <a href="http://doi.org/10.5281/zenodo.7803064">doi.org/10.5281/zenodo.7803064</a>. The additional variables here included are: slow edge velocity, fast edge velocity, and eddy dissipation rate (EDR). All variables are stored on the same time and range grids adopted for the main dataset. Similarly, the event selection and file structure are identical to those of the main dataset.<br><br>Slow and fast edge velocities are derived from Doppler spectra recorded by the zenith-pointing 94-GHz cloud radar. The slow (fast) edge velocity is calculated as the velocity associated with the slowest (fastest) Doppler bin above the peak noise level, belonging to a spectral cluster whose width is at least 5 Doppler bins.<br><br>The EDR is retrieved following the approach by Borque et al. (2016; <a href="http://doi.org/10.1002/2015JD024543">doi.org/10.1002/2015JD024543</a>), using as input the slow edge velocity, and model horizontal wind speed from the main dataset. EDR is retrieved in 5 minute intervals, up to a maximum range of 3 km.<br><br>The detailed documentation of the variables here included can be found in the Supporting Information to the following publication: <a href="https://doi.org/10.1029/2023GL106599" target="_blank" rel="noopener">doi.org/10.1029/2023GL106599</a>.</p>
Code and data for manuscript: Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir.
<p>This is the source code and data required to reproduce data analysis and figures from the manuscript, "Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir". </p>
GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — Parameter estimation data release
<p>This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>).</p> <p><strong>Parameter estimation data release</strong></p> <p>This data release contains posterior samples (*.h5) for gravitational-wave candidates from the second part of the third observing run (O3b).We provide results for the 35 candidates that have a probability of astrophysical origin of over 0.5, plus <a href="https://doi.org/10.3847/2041-8213/ac082e">GW200105_162426</a>, which is a clear outlier from the noise background. There are two .h5 files per event</p> <ul> <li>Cosmologically reweighted (*cosmo.h5)</li> <li>Not cosmologically reweighted (*nocosmo.h5)</li> </ul> <p>The cosmologically reweighted posteriors are reweighted to have a luminosity-distance prior that has a uniform merger rate in the source's comoving frame. See the <a href="http://dcc.ligo.org/LIGO-P2000318/public">paper</a> appendices for further information. In addition to containing the posterior samples, the .h5 files also contain metadata about the analyses including the configuration files (which specify details such as the detector data analysed), noise power spectral densities (potentially for a superset of the detectors used in the analysis) and calibration uncertainty envelopes.</p> <p>The inference of the source parameters were performed with <a href="https://lscsoft.docs.ligo.org/bilby/">Bilby</a>, <a href="https://lscsoft.docs.ligo.org/parallel_bilby/">Parallel Bilby</a> and <a href="https://git.ligo.org/richard-oshaughnessy/research-projects-RIT/tree/temp-RIT-Tides">RIFT</a>. The results are formatted using <a href="https://lscsoft.docs.ligo.org/pesummary/">PESummary</a>.</p> <p><strong>A note about mixed samples:</strong> The samples provided here are produced using different waveform approximants. The Mixed label indicates that equal numbers of samples have been included from two different waveform approximants. For the binary black holes, these are IMRPhenomXPHM and SEOBNRv4PHM (for more details, see GWTC3p0PEDataReleaseExample.ipynb included in this data release and the paper). As different waveforms were analysed with different codes, there are sometimes differences in some parameters due to conventions in the codes. For example:</p> <ul> <li>As RIFT does not sample over time of coalescence as Bilby does, the RIFT time of coalescence results have a posterior distribution with a single spike, whereas the Bilby results have a distribution of peaks representing different sky positions for the source.</li> <li>There are different conventions for the range of the polarization angle (either 0 to π or 0 to 2 π). The parameter psi_wrapped maps all results to the range 0 to π, should consistency be important.</li> <li>The likelihood may show small differences when different sampling rates were used for Bilby and RIFT. The log-likelihood is expected to have a relative shift between the two runs of a few nats.</li> </ul> <p>Due to these differences, care must be taken when using Mixed samples, which will contain results using both codes' conventions. This should not impact the most interesting quantities, such as the masses, and so should only be rarely an issue.</p> <p>A <a href="https://doi.org/10.5281/zenodo.5117702">similar parameter-estimation release has been made to accompany GWTC-2.1</a> for results from the first part of the third observing run.</p> <p><strong>Sky localization data release</strong></p> <p>The sky localization tar file (IGWN-GWTC3p0-v2-PESkyLocalizations.tar.gz) contains candidate sky localizations corresponding to different parameter estimation configurations (.fits). Two waveforms are used for the majority of targets (IMRPhenomXPHM and SEOBNRv4PHM) and additional waveforms are used for possible neutron star--black hole mergers (see the <a href="https://dcc.ligo.org/LIGO-P2000318/public">paper</a> for further information). If you do not mind which waveform, the sky localizations labelled "Mixed" include posterior samples from both waveforms used. A machine readable list (skyLocalizationFileList.csv) of sky localization files is included within the .tar.gz file for ease of use, where the Mixed results are indicated as Default=True.</p> <p><strong>Contour data release</strong></p> <p>The contour tar file (IGWN-GWTC3p0-v2-PEContours.tar.gz) contains the contour files used to produce Figures 8 and 9 in the <a href="http://dcc.ligo.org/LIGO-P2000318/public">paper</a>. The python notebook (GWTC3p0PEPlotContourData.ipynb) explains how to reproduce these figures (and an interactive version of these plots can be accessed at <a href="https://gwtc3-contours.streamlit.app/">gwtc3-contours.streamlit.app/</a>).</p> <p><strong>Python notebook</strong></p> <p>The Python notebook (GWTC3p0PEDataReleaseExample.ipynb) explains how to read and use the posterior samples with a selection of examples.</p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5546662 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p> </p> <p>For more general background on gravitational-wave parameter estimation, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.</p>
Journey North - Hummingbird observations by volunteer community scientists across Central and North America (1996-2020)
This data package contains hummingbird migration data (1996 - 2020) across North and Central America collected by 30,703 community scientists for Journey North, a crowdsourced participatory science program of the University of Wisconsin-Madison Arboretum. The Journey North Hummingbird Project is an ongoing study of hummingbird phenology conducted at broad spatial and temporal scales. Since 1996, community scientists have tracked first arrival dates and breeding and feeding behavior as well as the onset of fall migration and presence of hummingbird species throughout the winter months in the United States. Focal species are the Ruby-throated Hummingbird (Archilochus colubris) and Rufous Hummingbird. However, observational data is also available for Broad-tailed Hummingbird (Selasphorus platycercus), Black-chinned Hummingbird (Archilochus alexandri), Calliope Hummingbird (Selasphorus calliope), Costa's Hummingbird (Calypte costae), Anna’s Hummingbird (Calypte anna), Allen’s Hummingbird (Selasphours sasin). Observers also provide estimates of the number of birds sighted. However, observers do not follow standardized methods for counting species observed. Observers do not observe at set times of the day, do not repeat observations regularly, and are not required to provide the length of time during which a specified number of species observed were counted. Therefore, it is recommended that this dataset be analyzed to indicate presence, not abundance. Additional contextual information is provided as text in the comments field of the dataset. The Journey North Hummingbird Project dataset is hosted by the University of Wisconsin-Madison Shared Web Hosting Service.
Journey North - Monarch Butterfly and Milkweed observations by volunteer community scientists across Central and North America (1996-2020)
This data package contains monarch migration data (1996 - 2020) across North America collected by 42,518 community scientists for Journey North, a crowdsourced participatory science program of the University of Wisconsin-Madison Arboretum. The Journey North Monarch and Milkweed project is an ongoing study of monarch migration phenology conducted at broad spatial and temporal scales. Since 1996, community scientists have tracked first arrival dates and breeding and feeding behavior as well as the onset of fall migration, fall roosts, and peak migration events. Community scientists have also tracked the first emergence of milkweed in the spring and the presence of milkweed across the landscape during the summer, fall-winter months. The focal species is the Monarch Butterfly, Danaus plexippus. Community scientists indicate when known milkweed species in submitted comments. Journey North data is observational and often opportunistic in nature. Observers do provide estimates of the number of adult monarch butterflies sighted during an observation. However, observers do not follow standardized methods for counting species observed. Observers do not observe at set times of the day; do not repeat observations regularly, and are not required to provide the length of time during which a specified number of species observed were counted. Therefore, it is recommended that this dataset be analyzed to indicate presence, not abundance. Additional contextual information is provided as text in the comments field of the dataset. The Journey North Monarch and Milkweed project dataset is hosted by the University of Wisconsin-Madison Shared Web Hosting Service.
Inventory and description of thermokarst features observed along the Umiat Corridor in July 2009.
Using a combination of aerial imagery and ~1m resolution airborne lidar (collected July, 2009), we use manual visual inspection of the two datasets to identify point locations of over 7000 thermal erosion features (thermokarst) of varying maturity. For each feature we report its x,y position, the facing direction of the feature, the local topographic setting, the geologic unit it occurs on, the relative age of the feature and the specific type of thermal erosion feature.
Tanana River Yearly Ice Break Up Observed at Nenana, AK (1917 - Present)
This is a Yearly observation of when the ice on the Tanana River breaks up. This data is hosted originally by the National snow and ice data enter(http://nsidc.org/). The data is located at http://nsidc.org/data/docs/daac/nsidc0064_nenana.gd.html.
Observational study of post-fire mycorrhizal communities associated with resprouting Betula nana shrubs across a fire-severity gradient in the Anaktuvuk River Fire burn scar, 2009
The dataset contains fungal community data from a sampling campaign in 2009, two growing seasons after the Anaktuvuk River Fire. We used molecular tools, including ARISA and fungal ITS sequencing, to characterize the mycorrhizal communities on resprouting Betula nana shrubs across a fire-severity gradient. Summarized data can be viewed by site and provide information on richness and abundance of basidiomycetes and ascomycetes andChao1 and MaoTau estimators of richness.
ARISA fungal community profiles for each resprouting Betula nana shrub sampled in an observational study of post-fire mycorrhizal communities across a fire-severity gradient in the Anaktuvuk River Fire burn scar, 2010
The dataset contains fungal community data from a sampling campaign in 2009, two growing seasons after the Anaktuvuk River Fire. We used molecular tools, including ARISA and fungal ITS sequencing, to characterize the mycorrhizal communities on resprouting Betula nana shrubs across a fire-severity gradient. ARISA profiles are provided for each shrub sampled in the study.
Flower and Leaf Phenology of Interior Alaska Forbs and Shrubs as Observed Near Fairbanks Alaska from 2013-2015
This dataset contains the dates of phenological phases for leaves and flowers of 42 species of forbs and shrubs (2 subspecies of one species) observed throughout the growing season in 2013, 2014 and 2015. Data were collected in three general areas: in the Bonanza Creek Experimental Forest, on the University of Alaska Fairbanks Campus, and in the woods near Pearl Creek Elementary School. Species are classified by origin (native or non-native), growth form (forb, dwarf shrub, or tall shrub), leaf habit (deciduous, wintergreen or evergreen), plant life history (annual, biennial, or perennial), and habitat (black spruce forest, mixed deciduous / coniferous forest, or disturbed habitat).
Lagrangian Water Age trajectories initiated from the coastal 500m isobath and derived from surface velocities obtained from satellite observations
We conduct a Lagrangian particle trajectory analysis of surface velocities. We define an “offshore water age” as the time taken by a water parcel to be advected backward in time from its current position along its trajectory until it crosses the 500 m isobath. The rationale of this diagnostic is to detect filaments of coastal water advected offshore by horizontal transport and to estimate the time for water parcels in the filament o leave the coastal area. For example, a value of “20 days” assigned to a pixel means that the water parcel in that area was in the coastal area approximately 20 days before, where it was likely enriched in nutrients.
Throw trap and electrofishing data collected during 1996–2022 from the Everglades, Florida, United States for the publication "Contrasting invasion histories and effects of three non-native fishes observed with long-term monitoring data"
This dataset was used to analyze the effects of three non-native fishes in the Florida Everglades for a publication in the journal Biological Invasions. The dataset incorporates plot-level mean densities (# of individuals per square meter) of common aquatic animals collected during 1996–2022 from 17 sites across three regions of the Everglades: Taylor Slough, Shark River Slough, and Water Conservation Area 3A. Prey species included are nine common small fishes and three common decapod species (two crayfish species and grass shrimp). The dataset includes throw trap data on three predator taxa: African Jewelfish (Hemichromis letourneuxi), Mayan Cichlids (Mayaheros uruphthalmus), and sunfishes (Lepomis spp.). Annual indices of mean wet season electrofishing catch-per-unit-effort of Asian Swamp Eels (Monopterus albus/javanesis), Mayan Cichlids, sunfishes, and the three other large 'top predator' fishes (Amia calva, Lepisosteus platyrhincus, Micropterus salmoides) are included for plots where electrofishing was performed from 1997-2021. Hydrologic measures used in analyses and R code used to conduct analyses are also included.
Annual summaries of daily climatological observations from the National Weather Service weather station at the UGA Marine Institute on Sapelo Island, Georgia for 1958 to 2004
Daily summaries of climatological observations from the National Weather Service weather station on Sapelo Island, Georgia, were obtained from the NOAA National Climatic Data Center (http://www.ncdc.noaa.gov/) covering the period 1958 through 2004. Records for incomplete years with more than one month of missing observations were deleted (i.e. 1964, 1969-1971), then missing values of daily minimum, maximum and mean temperature were estimated by cubic spline interpolation to fill in data gaps of five or fewer consecutive days. Annual summary statistics were then calculated for daily minimum, maximum and mean air temperature and total precipitation.
Annual summaries of daily climatological observations from the National Weather Service weather station at Brunswick, Georgia for 1915 to 2004
Daily summaries of climatological observations from the National Weather Service weather station in Brunswick, Georgia, were obtained from the NOAA National Climatic Data Center (http://www.ncdc.noaa.gov/) covering the period 1915 through 2004. Missing values of daily minimum, maximum and mean temperature were estimated by cubic spline interpolation to fill in data gaps of five or fewer consecutive days. Annual summary statistics were then calculated for daily minimum, maximum and mean air temperature and total precipitation.
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.