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396 results for “Surface water”
SBC LTER: Ocean: Time-series: Mid-water SeaFET pH and CO2 system chemistry with surface and bottom Dissolved Oxygen at Arroyo Quemado Reef(ARQ), 2012-2017
Calibrated pH (Total scale, SeaFET sensor) an disoolved oxygen (miniDOT)data were collected from Arroyo Quemado Reef in the Santa Barbara Channel (site ID: ARQ). pH data are accompanied by in situ temperature and associated carbonate chemistry parameters. The SeaFET instrument is located about 4 meters from the surface, with other moored instruments. Associated carbonate chemistry parameters were calculated with the CO2calc programs from USGS, and include: partial pressure and fugosity of CO2, concentrations of bicarbonate, carbonate and hyrdroxide ion, Omega (saturation state) of calcite and aragonite. Dissolved oxygen sensors (miniDOT, PME) were added in 2014, and are mounted near the ocean surface and near the seafloor, and also report temperature. All data have been interpolated to a 20 minute time interval for compatibility with other SBC LTER moored instrument data. Data coverage is 2012-07-30 to 2017-03-10.All data from this site have been concatenated with the pH data from the other sites and merged into one data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=6005
SBC LTER: Ocean: Time-series: Mid-water SeaFET pH and CO2 system chemistry with surface and bottom Dissolved Oxygen at Mohawk Reef(MKO), 2012 - 2017
Calibrated pH (Total scale, SeaFET sensor) an disoolved oxygen (miniDOT)data were collected from Mohawk Reef in the Santa Barbara Channel (site ID: MKO). pH data are accompanied by in situ temperature and associated carbonate chemistry parameters. The SeaFET instrument is located about 4 meters from the surface, with other moored instruments. Associated carbonate chemistry parameters were calculated with the CO2calc programs from USGS, and include: partial pressure and fugosity of CO2, concentrations of bicarbonate, carbonate and hyrdroxide ion, Omega (saturation state) of calcite and aragonite. Dissolved oxygen sensors (miniDOT, PME) were added in 2014, and are mounted near the ocean surface and near the seafloor, and also report temperature. All data have been interpolated to a 20 minute time interval for compatibility with other SBC LTER moored instrument data. Data coverage is 2012-01-11 to 2017-12-19.The update of this dataset was terminated in 2019. All data from this site have been concatenated with the pH data from the other sites and merged into one data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=6005
SBC LTER: Ocean: Time-series: Mid-water SeaFET pH and CO2 system chemistry with surface and bottom Dissolved Oxygen at Santa Barbara Harbor/Stearns Wharf(SBH), 2012-2017
Calibrated pH (Total scale, SeaFET sensor) an disoolved oxygen (miniDOT)data were collected from Santa Barbara Harbor/Stearns Wharf in the Santa Barbara Channel (site ID: SBH). pH data are accompanied by in situ temperature and associated carbonate chemistry parameters. The SeaFET instrument is located about 4 meters from the surface, with other moored instruments. Associated carbonate chemistry parameters were calculated with the CO2calc programs from USGS, and include: partial pressure and fugosity of CO2, concentrations of bicarbonate, carbonate and hyrdroxide ion, Omega (saturation state) of calcite and aragonite. Dissolved oxygen sensors (miniDOT, PME) were added in 2014, and are mounted near the ocean surface and near the seafloor, and also report temperature. All data have been interpolated to a 20 minute time interval for compatibility with other SBC LTER moored instrument data. Data coverage is 2012-09-15 to 2016-09-14. The update of this dataset was terminated in 2019. All data from this site have been concatenated with the pH data from the other sites and merged into one data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=6005
GFDL CM2.1 Partially-Coupled Simulations Data for "Understanding Lead Times of Warm-Water-Volumes to ENSO Sea Surface Temperature Anomalies"
<p>GFDL CM2.1 partially-coupled idealized simulations:</p> <p>Two sets of idealized experiments with prescribed EP and CP ENSO SST anomaly patterns. Each set of experiments has a prescribed idealized sinusoidal ENSO oscillation with periodicities of 48, 36, and 24 months, respectively.</p> <p>For the details please refer to our paper;<br> Zhao, S., Jin, F.-F., & Stuecker, M. F. (2021). Understanding Lead Times of Warm Water Volumes to ENSO Sea Surface Temperature Anomalies. <em>Geophysical Research Letters</em>, <em>48</em>(19), e2021GL094366. <a href="https://doi.org/10.1029/2021GL094366">https://doi.org/10.1029/2021GL094366</a></p> <p> </p> <p> </p> <p> </p>
Distance from available surface water of mammals in Ruaha National Park
<p>In Africa, burgeoning human populations promote agricultural expansion and the associated demand for water. Water abstraction for agriculture from perennial rivers can be detrimental for wildlife, particularly when it reduces water availability in protected areas. Ruaha National Park (Ruaha NP) in southern Tanzania, one of the largest parks in Africa, contains important wildlife populations, including rare and endangered species. The Great Ruaha River (GRR) is the main dry-season water source for wildlife in the Park. Water offtake from this river for large-scale irrigation and livestock production up-stream of the Park has caused large expanses of this formerly perennial river within the Park to dry out during the dry season. The dry season distribution of a species in relation to surface water is considered an indicator of its dependence on water and ability to cope with the loss of surface water. We investigated how diminishing surface water availability during three dry seasons (2011–2013) affected herbivores' distance to water in Ruaha NP. The distance held by herbivores to water is shaped by a range of factors including dietary category. We determined changes in the locations of available surface water throughout the dry season using standardized ground transects, close to and leading away from the GRR, to map the locations of nine herbivore species. Functional responses of herbivores, i.e. their change in distance to water between early and late dry season, indicated that distance to water was (i) shortest in buffalo and waterbuck (grazers), (ii) similar for plains zebra (grazer), elephant and impala (mixed feeders), (iii) larger in giraffe and greater kudu (browsers) and (iv) largest in generalist feeders (warthog, common duiker). The substantial species' differences in surface water dependence broadly fit predicted species differences in their ability to cope with anthropogenic reduction in surface water in Ruaha NP.</p>
Operating diagram of hatching module in Zoug jars, this system consists of a 300-litre temperature-controlled isothermal enclosure containing 10 one-litre Zoug jars, each able to accommodate several hundred eggs. An ascending current holds the eggs in suspension and carries the larvae to the surface. Another bottle connected to this device collects the larvae. The water circulating in the jars is independent of that used in the filtration circuit. A cooling unit and UV sterilizer complete the installation. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Operating diagram of hatching module in Zoug jars, this system consists of a 300-litre temperature-controlled isothermal enclosure containing 10 one-litre Zoug jars, each able to accommodate several hundred eggs. An ascending current holds the eggs in suspension and carries the larvae to the surface. Another bottle connected to this device collects the larvae. The water circulating in the jars is independent of that used in the filtration circuit. A cooling unit and UV sterilizer complete the installation.
Рис. 1. Среднемесячная температура воды в б. Новгородская на поверхности: 1 – За период 1931–1973 гг.; 2 – За 1977 г.; 3 – За 1978 г.; 4 – За 1979 г.; 5 – За 1980 г.; 6 – За 1981 г.; 7 – температура нереста (18ºС). Fig. 1. Average monthly sea surface water temperature in Novgorodskaya Bay: 1 – for the period 1931–1973; 2 – for 1977; 3 – for 1978; 4 – for 1979; 5 – for 1980; 6 – for 1981; 7 –spawning temperature (18ºC). in Review of methods for the forecast of mollusk's spat productivity in sea-farms of Primorye and probable ways of their enhancement
Рис. 1. Среднемесячная температура воды в б. Новгородская на поверхности: 1 – За период 1931–1973 гг.; 2 – За 1977 г.; 3 – За 1978 г.; 4 – За 1979 г.; 5 – За 1980 г.; 6 – За 1981 г.; 7 – температура нереста (18ºС). Fig. 1. Average monthly sea surface water temperature in Novgorodskaya Bay: 1 – for the period 1931–1973; 2 – for 1977; 3 – for 1978; 4 – for 1979; 5 – for 1980; 6 – for 1981; 7 –spawning temperature (18ºC).
Regional relationship between total alkalinity and salinity in the surface waters of the western South Atlantic margin
<p><span><span>Surface</span><span> seawater </span><span>data</span><span> considered </span></span><span><span>in the surface waters </span><span>of</span><span> the western South Atlantic margin</span></span><span><span>: cruise, year, month, day, hour, minute, station, latitude, longitude, pressure (</span><span>dbar</span><span>), </span></span><span><span>surface temperature (SST</span><span>; </span><span>°C)</span><span>,</span><span> sea surface salinity (SSS) and total alkalinity (A</span></span><span><span>T</span></span><span><span>; µmol kg</span></span><span><span>-1</span></span><span><span>)</span><span>.</span></span><span> </span></p>
Global LAke Surface water Temperature (GLAST): Compound thermal extremes in lakes
<p>This database contains daily maximum temperature, daily minimum temperature, and daily mean temperature for 92,245 lakes globally from 1981 to 2020. These daily time series were derived from hourly simulation data.</p> <p>The database also includes annual statistics of six types of thermal extreme events calculated from the daily lake temperature time series:</p> <ul> <li>daytime hot extreme events (hot day–mild night)</li> <li>nighttime hot extreme events (mild day–hot night)</li> <li>compound hot extreme events (hot day–hot night)</li> <li>daytime cold extreme events (cold day–mild night)</li> <li>nighttime cold extreme events (mild day–cold night)</li> <li>compound cold extreme events (cold day–cold night)</li> </ul> <p> </p> <p>The annual statistics provided for these events include metrics such as frequency, intensity, duration, and total days. Additionally, annual statistics of extreme air temperature events over the lakes are included.</p> <p>Details about the hourly-scale lake temperature simulation methodology can be found in the paper <em>"Global lakes are warming slower than surface air temperature due to accelerated evaporation"</em> (Tong et al., 2023, Nature Water). Definitions and calculation methods for thermal extreme events in lakes and atmosphere are provided in <em>"Day-night compound thermal extremes in lakes"</em> (Tong et al., 2025).</p> <p>For detailed information about the contents of each data file, please refer to the accompanying <strong>readme.docx</strong> file.</p> <p>For more datasets on global aquatic environments, please visit the official website of the Global Aqua Remote Sensing (GARS) Laboratory, led by Prof. Lian Feng: <a href="https://garslab.com/?cat=1">https://garslab.com/?cat=1</a>.</p>
Global hydrology and water quality data from 1980-2019, derived from the dynamical surface water quality model (DynQual) at 5 arcmin spatial resolution
<p>Global ~10km (5 arcmin) output data from the dynamical surface water quality model (DynQual) from 1980-2019, with annual and monthly temporal resolution. Simulations are made following the ISIMIP3a protocol (https://protocol.isimip.org/#/ISIMIP3a).</p> <p>Output data includes:</p> <ul> <li>Discharge (m3 s-1)</li> <li>Channel storage (m3) </li> <li>Water temperature (K)</li> <li>Total dissolved solids (TDS) load (g s-1)</li> <li>Biological oxygen demand (BOD) load (g s-1)</li> <li>Fecal coliform (FC) load (million cfu s-1)</li> <li>Salinity; as indicated by TDS concentrations (mg l-1)</li> <li>Organic pollution; as indicated by BOD concentrations (mg l-1)</li> <li>Pathogen/bacterial pollution; as indicated by FC concentrations (cfu 100ml-1)</li> </ul> <p>Note. a minimum discharge threshold of 0.1 m3 s-1 was used when computing salinity (TDS), organic (BOD) and pathogen (FC) concentrations, as uncertainties in absolute values of water availabilities have large impacts on resulting in-stream concentrations. Thus, if the the average discharge for the month was below 0.1 m3 s-1, concentrations are not calculated (assigned as NA).</p> <p>In-stream water quality aggregated to 0.5 degree (i.e. 30 arcmin) spatial resolution (daily, monthly and annual) can be found at: <a href="https://zenodo.org/records/14675270">https://zenodo.org/records/14675270</a>. </p>
Global surface water quality data from 1980 - 2019, derived from the dynamical surface water quality model (DynQual) at 30 arcmin spatial resolution
<p>Global ~50km (30 arcmin) surface water quality data from the dynamical surface water quality model (DynQual) from 1980-2019, with annual, monthly and daily temporal resolution. Simulations are made following the ISIMIP3a protocol (https://protocol.isimip.org/#/ISIMIP3a).</p> <p>Output data includes:</p> <ul> <li>Salinity; as indicated by TDS concentrations (mg l-1)</li> <li>Organic pollution; as indicated by BOD concentrations (mg l-1)</li> <li>Pathogen/bacterial pollution; as indicated by FC concentrations (cfu 100ml-1)</li> </ul> <p>Simulations were originally made at 5-arcmin resolution and aggregated to 30 arcmin 0.5 degree by summing the in-stream (routed) loadings and channel storage over the aggregated area (at daily, monthly and annual timesteps), and subsequently calculating in-stream concentrations. Please note the aggregation technique is provisional and thus the data is subject to change.</p> <p>Note. A minimum discharge threshold of 0.1 m3 s-1 was used when computing TDS, BOD and FC concentrations, as uncertainties in absolute values of water availabilities have large impacts on resulting in-stream concentrations. Concentrations in these gridcells are assigned as NA.</p> <p>Hydrology and water quality simulations made at DynQuals native spatial resolution (5 arcmin) can be found at: <a href="https://zenodo.org/records/14673871">https://zenodo.org/records/14673871</a>.</p>
Global surface water quality datasets under uncertain climate and socio-economic change, derived from the dynamical surface water quality model (DynQual) at 5 arcmin spatial resolution
<pre>Global ~10km (5 arcmin) surface water quality data from the dynamical surface water quality model (DynQual) from 2005-2100, with annual and monthly temporal resolution. Simulations are made under three combined climate and socio-economic scenarios (SSP1-RCP2.6; SSP3-RCP7.0 and SSP5-RCP8.5) and using five general circulation model (GFDL-ESM4; UKESM1-0-LL; MPI-ESM1-2-hr; IPSL-CM6A-LR and MRI-ESM2-0), following the ISIMIP3b protocol (<a href="https://protocol.isimip.org/#/ISIMIP3b">https://protocol.isimip.org/#/ISIMIP3b</a>). Output data are provided at annual and monthly temporal resolution over WorldClim time periods (2005-2020; 2021-2040; 2041-2060; 2061-2080; 2081-2100). Output data includes: - Discharge (m<sup>3</sup> s<sup>-1</sup>) - Water temperature (K)<br>- Total dissolved solids (TDS) load (g s<sup>-1</sup>)<br>- Biological oxygen demand (BOD) load (g s<sup>-1</sup>)<br>- Fecal coliform (FC) load (million cfu s<sup>-1</sup>) - Salinity; as indicated by TDS concentrations (mg l<sup>-1</sup>) - Organic pollution; as indicated by BOD concentrations (mg l<sup>-1</sup>) - Pathogen/bacterial pollution; as indicated by FC concentrations (cfu 100ml<sup>-1</sup>)<br><br>Note. A minimum discharge threshold of 0.1 m<sup>3</sup> s<sup>-1</sup> was used when computing TDS, BOD and FC concentrations, as uncertainties in absolute values of water availabilities have large impacts on resulting in-stream concentrations. Concentrations in these gridcells are assigned as NA.<br><br>Full time series of these variables at 30 arcmin (0.5 degree) can be found at: <a href="https://zenodo.org/records/14677534">https://zenodo.org/records/14677534</a>.</pre>
Surface Water Area Variations of Global Lakes and Reservoirs
<p>Monthly surface area timeseries of large lakes and reservoirs generated from Sentinel-1 SAR backscatter data from January 2017 through December 2019.</p>
Visualizing Eigen/Zundel cations and their interconversion in monolayer water on metal surfaces
<p>Here lies the experimental and theoretical data for the manuscript titled " Visualizing Eigen/Zundel cations and their interconversion in monolayer water on metal surfaces" to be published in Science.</p>
Visualizing Eigen/Zundel cations and their interconversion in monolayer water on metal surfaces
<p>Here lies the tabulated data used to create the Figures for the Science manuscript abo0823 titled "Visualizing Eigen/Zundel cations and their interconversion in monolayer water on metal surfaces".</p>
Surface Water Maps of Pune District in India
<p>Many applications that target water resource management requires detection, monitoring and assessment of water for quantity and quality on regular basis. The advancement in remote sensing have led in new era in the detection of surface water with its changing dynamics. We processed cloud free images for year 2016 acquired by Landsat 8 OLI (Path : 147, Row: 47) as available from from <a href="http://earthexplorere.usgs.gov/">http://earthexplorere.usgs.gov</a>. The processing includes calculation of Top of Atmospheric reflectance (ToA) and derived Modified Normalized Differential Water Index (MNDWI) images. We have generated in-land surface water maps for all months excluding rainy seasons for the Pune district in India. The derived water maps were compared with a reference surface water map, Global Surface Water Explorer (GSWE), prepared by The European Commission’s Joint Research Centre in the framework of the Copernicus Programme. The kappa coefficient between derived maps and GSWE image were found to be in the range of 0.52 to 0.96 with an average agreement of 0.82 indicating strong level of agreement.</p>
An integrated dataset of daily lake surface water temperature over Tibetan Plateau
<p>A dataset for daily surface temperature of 160 lakes over Tibetan Plateau for period from 1978 to 2017. The new dataset was developed based on combination of remote sensing (MODIS) and model (slightly modified <em>air2water </em>model).</p>
Data of Water Vapor Flux-Profile Relationship in the Stable Boundary Layer over the Sea Surface
<p>data and code for paper 'Water Vapor Flux-Profile Relationship in the Stable Boundary Layer over the Sea Surface'</p>
GLOBMAP SWF: a global annual surface water cover frequency dataset since 2000 for change analysis of inland water bodies
<p>The extent of surface water has been changing significantly due to climatic change and human activities. However, it is challenging to capture the interannual changes and trends of inland water bodies due to their high seasonal variation and abrupt change. We generated a global annual surface water cover frequency dataset (GLOBMAP SWF) from the MODIS land surface reflectance products to describe the seasonal and interannual dynamics of surface water. Surface water cover frequency (SWF) was proposed as the percentage of the time period when a pixel is covered by water in a year. Instead of determination of the water observations directly, the SWF was estimated indirectly by identifying land observations among annual clear-sky observations to reduce the influence of clouds and variability of water body and surface background characteristics, which helps to improve the applicability of the algorithm for different regions across the globe. Regional analysis demonstrates that our estimation results show reasonable performances on frozen water, saline lake, bright surface and cloud-frequent regions. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water body extent with consideration of its seasonal variation.</p> <p>The GLOBMAP SWF dataset is provided in Version 1.0 (https://zenodo.org/record/6462883#.YxC16HZBw2w). Here we provide the number of MOD09A1 (MODIS 8-day composite land surface reflectance) clear-sky snow/ice-free observations (<em>N<sub>Clear</sub></em>) data as a quality dataset of GLOBMAP SWF product. The clear-sky observation refers to the valid MOD09A1 observation that not covered with clouds and snow/ice. The more available clear-sky observations, the more reliable the estimated SWF.</p> <p>The <em>N<sub>Clear </sub></em>dataset is provided by 296 1200 km × 1200 km tiles at annual temporal and 500 m spatial resolutions in the sinusoidal projection with Geotiff format for each year during 2000-2020. The file is named as "GLOBMAPClearCount. AYYYY001.hHHvVV.V01.tif", where “YYYY” refers to the year of the file, and “HH” and “VV” explains the number of tiles that are the same with MODIS standard tile. The valid range is 0-46, scale factor is 1.0. The <em>N<sub>Clear </sub></em>of permanent water (land obervation count of 46), permanent snow/ice and terrain shadows are set to 50.</p>
The Meltwater Pulse1A Triggered an Extreme Cooling Event: Evidence From Southern China. Meltwater Pulse Cooling Event (MCE). Winter temperature data during the last deglacial of Huguangyan Maar lake, Surface water temperature and seasonal diatom assemblage data of Huguangyan and Yunlong Lake.
<p>Here we present results of The lake averaged monthly mean surface water temperature over the period from September 2013 to August 2015 from Yunlong Tianchi Lake(YL)(25°52.2′N, 99°16.8′E, altitude: 2551 m a.s.l), southwestern China. The dataset include sediment trap main diatom percentages over the period from September 2013 to August 2015 from YL. Lake water temperature profiles at different depths (1, 3, 6, 9, 11, 13, 16 m) from November 2008 to May 2009 in Huguang Maar Lake (HML)(21°9′N, 110°17′E), Southern China. AMS radiocarbon dates of plant remains and bulk sediment samples for Huguangyan Maar Lake over the last ~17 cal ka BP. The main diatom assemblage percentages (%) from 17 to 10 cal ka BP at Huguangyan Maar Lake. Diatom-based reconstruction of winter temperature (WT) from 17 to 10 cal ka BP at Huguangyan Maar Lake.</p>
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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)
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DANDI Archive for NWB datasets
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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.