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684 results for “Water temperature”
High-frequency water and sediment temperature from the Seagrass Recovery Experiment, South Bay, VA 2020-2022
To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). To further characterize differences between the meadow interior and edge, water and sediment temperatures were collected continuously. Water temperature was monitored at fixed positions 20 cm above the sediment surface at the center of each plot, while sediment temperature was monitored at 5 cm depth at the center of two sites within the central and northern edge South Bay locations.
Water Temperatures and Climatology for Wachapreague, VA, 1982-2021
Daily average measured near-surface water temperature from 1982-2021 constructed for the site in the Virginia coastal bays where the NOAA Wachapreague station is located (Site CBW (Coastal Bay Wachapreague); 37.61N, 75.69W; water depth 1m) and for a site in the coastal ocean just outside the bays (Site COC (Coastal Ocean CHLV2); 36.91N, 75.71W; water depth 15m). Daily climatological mean temperature and marine heatwave threshold (90th percentile) calculated using 30 years of the record (1987-2016) are also provided.
Summaries of temperature and water table depth prior to peat sampling in Stordalen Mire, 2011-2017
<div> <p>This dataset provides summaries of temperature (T) and water table depth (WTD) conditions prior to the collection of peat samples from Stordalen Mire, Sweden, in July of 2011-2017. These summaries include the following files:</p> <h2><strong>t_wtd_summaries_July2011-2017samplings.csv</strong></h2> </div> <p>This file gives summary statistics over various time intervals for the following environmental measurements:</p> <ul> <li><strong>AirTemperature</strong>: Mean daily air temperature (°C), obtained from automatic sensors at the nearby Abisko Scientific Research Station (ANS) (station ID 188790; the source file [ANS_Daily_Wx_Jul84_Dec17.txt] is not included due to sharing restrictions).</li> <li><strong>WTD</strong>: Water table depths (cm), obtained from <a href="https://doi.org/10.5281/zenodo.10420396">Manual active layer and and water table depth measurements from the autochamber sites at Stordalen Mire, northern Sweden (2003-2017)</a> (from Patrick Crill et al.).</li> </ul> <p>The time intervals for these summaries are defined relative to the peat sampling date at each site (see <a href="https://doi.org/10.5281/zenodo.12827096">EMERGE Sample Metadata Sheet for Samples with Microbiomes</a>), which varies by site and year. The specific intervals are defined as follows:</p> <ul> <li><strong>7d</strong>: 7 days prior to the sampling date, plus the sampling date itself.</li> <li><strong>14d</strong>: 14 days prior to the sampling date, plus the sampling date itself.</li> <li><strong>21d</strong>: 21 days prior to the sampling date, plus the sampling date itself.</li> <li><strong>28d</strong>: 28 days prior to the sampling date, plus the sampling date itself.</li> <li><strong>growing</strong>: Time from beginning of growing season (defined as June 1) until (and including) the sampling date.</li> <li><strong>all_growing</strong>: Entire growing season (June 1 – Sept. 30).</li> </ul> <p>For clarity, the start and end dates for each time interval (inclusive) are also given under the columns <strong>Start_Date</strong> and <strong>End_Date</strong>, where End_Date=<strong>Sampling_Date</strong> for all intervals except all_growing.</p> <p>Summary statistics for each interval include: measurement count (<strong>n</strong>), median (<strong>median</strong>), mean (<strong>mean</strong>), and standard deviation (<strong>sd</strong>), and are given under the column names beginning with these statistic labels.</p> <p><em>IMPORTANT NOTE: </em>For temperature, these statistics are calculated based on the average temperature measured on each day, meaning that<strong> </strong><em>the standard deviations do NOT account for within-day temperature variation.</em> To provide short-term (1 day) temperature variation context for each sampling date, the within-day mean, minimum, and maximum air temperatures for the sampling date only (taken directly from the corresponding row & columns in the source ANS data file) are provided in the columns <strong>samplingdate_mean_AirTemperature</strong>, <strong>samplingdate_min_AirTemperature</strong>, and <strong>samplingdate_max_AirTemperature</strong>.</p> <div> <div> <h2><strong>wtd_summaries_July2011-2017samples.csv</strong></h2> </div> <p>This file gives the percentage of time that each peat sample's depth midpoint (<strong>DepthAvg__</strong>) was at or below the water table depth (WTD), over each of the longer time intervals (≥21 days) defined above for the temperature & WTD summaries. (Intervals <21 days are not included due to the lower frequency of WTD measurements, which results in low <em>n</em> for shorter intervals.)</p> <p>The first few columns are taken directly from the <a href="https://doi.org/10.5281/zenodo.12827096">EMERGE Sample Metadata Sheet for Samples with Microbiomes</a>, for the samples collected in July of 2011-2017 from the MainAutochamber sites. The last set of columns include the following, with the time interval labels (defined as in the above temperature summaries) appended at the end of each column name:</p> <ul> <li><strong>n_WTD_*</strong>: Number of WTD measurements used in the calculation.</li> <li><strong>pct_time_below_WTD_*</strong>: Fraction (relative to 1) of measured WTDs over the given time interval that were at or above the DepthAvg__ for each sample, which equates to the fraction of measurement timepoints during which the given sample was at or below the WTD. This is the same method used for calculating "% Time below water table" in Figure 6 of <a href="https://doi.org/10.1038/s41396-018-0065-5">Singleton et al. (2018)</a>. For palsa sites, this value is automatically set to 0 based on the lack of a water table at all timepoints in the analysis.)</li> </ul> <p>As above, the WTD values used for these calculations were obtained from <a href="https://doi.org/10.5281/zenodo.10420396">Manual active layer and and water table depth measurements from the autochamber sites at Stordalen Mire, northern Sweden (2003-2017)</a> (Patrick Crill et al.).</p> <h1>Funding acknowledgments</h1> <p>This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.</p> <p>This research was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440.</p> <p>The temperature summary has been made possible by data provided by Abisko Scientific Research Station and the Swedish Infrastructure for Ecosystem Science (SITES).</p> <p>We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.</p> </div>
Imaging Temperature and Thickness of Thin Planar Liquid Water Jets in Vacuum - data
<p>Data set pertaining to the article "Imaging Temperature and Thickness of Thin Planar Liquid Water Jets in Vacuum", published in <em>Struct. Dyn.</em> 10, 034901 (2023), <a href="https://doi.org/10.1063/4.0000188" target="_blank" rel="noopener">https://doi.org/10.1063/4.0000188 </a>.</p> <p>The following data are provided:</p> <table> <tbody> <tr> <td>(zip-)file/Folder</td> <td>Description</td> <td>Format</td> <td>Extension</td> </tr> <tr> <td>IR_images/calibration_data/vacuum</td> <td> <p>Snapshots from a thermographic movie of our flat jet running in vacuum, at thirty different background temperature. (A snapshot shown in Fig. 3a, rhs.)</p> </td> <td> <p>temperature values per camera pixel (°C), 640 row * 480 columns, semicolon-separated ascii data</p> </td> <td>.asc</td> </tr> <tr> <td>IR_images/calibration_data/1atm</td> <td>As above, for our flat jet running in atmosphere. (Three snapshots shown in Fig. 2a.)</td> <td>as above</td> <td>.asc</td> </tr> <tr> <td>IR_images/calibration_data/chipnozzle</td> <td>As above, for a flat jet produced from a chip nozzle, and running in atmosphere.</td> <td>as above</td> <td>.asc</td> </tr> <tr> <td>IR_images/raw_data</td> <td>As above, for various conditions of the flat jet environment as detailed in table exp_settings.csv.</td> <td>as above</td> <td>.asc</td> </tr> <tr> <td>IR_video</td> <td>Two thermographic movies recorded of our flat jet at varied conditions of the jet environment detailed in table chamber_pressure.pdf.</td> <td>Radiographic image stream, suitable for opening with free software Optris Pix Connect.</td> <td>.ravi</td> </tr> <tr> <td>FJ_cooling_2D.mph</td> <td>Input file for 2D finite element simulation of our flat jet.</td> <td>Input file suitable for Comsol software, proprietary format.</td> <td>.mph</td> </tr> <tr> <td>Y_Z_Temp_Comsol.txt</td> <td>Ascii representation of our simulated temperature profile (Fig. S7 (SI)).</td> <td>List of (y,z,T) tupels, with (y,z) in m and T in °C.</td> <td>.txt</td> </tr> </tbody> </table> <p> </p> <p>In case you have any questions regarding this data set please contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
Marcell Experimental Forest 30-minute water table elevation and temperature from transects of wells in the S2 and S6 peatlands, 2018-ongoing
This data publication contains 30-minute water table elevation and temperature data collected along bog to lagg transects within two watersheds at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. The bog to lagg transects are located on the north and south sides of S2 and S6 peatlands and contain three surface water wells each. The water table elevations provide information to calculate the hydraulic gradients that drive flow to and from the bogs. The collection of these data was funded by the US Department of Energy. The research program at Marcell Experimental Forest is managed by the USDA Forest Service Northern Research Station.
Daily water temperature (C) in the Yolo Bypass and Sacramento River, 1998-2019
This data is an integration of raw logger data as well as relevant California Data Exchange Center (CDEC) data (Pien et al. 2020, hourly) and water quality data collected during the Yolo Bypass Fish Monitoring Program’s (YBFMP) fish collection (Pien and Kwan 2022) to produce a daily water temperature dataset for the Yolo Bypass and Sacramento River at Sherwood Harbor and Rio Vista Bridge. The raw YBFMP’s water temperature data was collected by loggers attached to the rotary screw trap (STTD) and Sherwood Harbor (SHR). Logger data ranged from daily means (1998) to a fifteen-minute collection interval (2013-2017 for the Yolo Bypass, 2009-2019 for Sherwood Harbor). A daily mean, maximum, minimum, standard deviation and coefficient of variation in water temperature was produced as well as columns for sample size (n, number of measurements per day), method (data collection or estimation), category, length (number of consecutive missing dates) and site. Daily water temperature data for the full extent of the YBFMP’s fish collection is valuable for a variety of purposes. For example, variation in water temperature during inundation and comparisons between temperatures in the Sacramento River and Yolo Bypass have been used as metrics of habitat complexity and linked to life history diversity in salmon (Goertler et al. 2017).
Discrete water temperature, flow, solar radiation, chlorophyll-a and inundation, Sacramento-San Joaquin Delta, CA, 1999-2019
The objective of our study is to better understand the factors affecting chlorophyll-a production within a floodplain and its transport downstream to determine how lateral connectivity influences longitudinal connectivity. The Yolo Bypass is an engineered floodplain of the Sacramento River that inundates during periods of high outflow via overtopping weirs. Water traveling through the Yolo Bypass flows parallel to the Sacramento River and re-connects to the mainstem at the southern extent of the floodplain. Several monitoring programs in the Sacramento San-Joaquin Delta and Yolo Bypass collect discrete and continuous water quality data, including chlorophyll measurements. For this study, we synthesized available flow, water temperature, chlorophyll and inundation data between March 1999 to December 2019 and modeled the effects of environmental variables and inundation on chlorophyll-a production in the floodplain, the mainstem, and downstream of the floodplain/mainstem.
Water temperature in the hidden, subglacial lake at Uruguay Island, Antarctic Peninsula region, 2020-2021, and additional data sets.
The dataset contains temperature measurements in a small subglicer (hidden) lake of Antarctic Peninsula region at several levels of depth. The measurements cover almost a full year and provide an understanding of the temperature and hydrological regime of the water body. Weather measurement data and statistics is provided additionally.
Littoral and Pelagic Water Temperatures and Light in Escanaba, McDermott, and Sparkling Lakes, Wisconsin USA 2023-2024
This dataset contains high-frequency temperature (°C) and light (lux) measurements from three north-temperate lakes collected during the summers of 2023 and 2024, as well as locations of sensors in each lake. HOBO (HOBO Pendant temp/light®, Onset Brands, MA) sensors recorded at hourly intervals. Measurements were collected at 0.5m and 1m depth in all lakes (McDermott, Escanaba, and Sparkling) and at select 3m sites in Sparkling Lake. Sampling included pelagic and littoral zones. Each lake contained two pelagic sites instrumented using subsurface buoys. The number of littoral sites varied by lake and year (see Methods). At littoral sites, macrophyte presence or absence was assessed weekly, with presence defined as macrophytes occupying more than 50% of the water column. In Sparkling Lake 3m littoral sites were paired, with sensors placed inside and outside macrophyte beds less than 10m apart. These data were used to quantify thermal habitat breadth (daily temperature range) and to compare estimates based on (1) pelagic-only measurements and (2) combined pelagic + littoral measurements, allowing evaluation of the littoral zone’s contribution to lake thermal assessments. The dataset also supports analyses of macrophyte effects on thermal habitat in littoral zones. Data collection presented in this data package represents a subset of the larger "Walleye Bright Spots" project data.
High-frequency winter water temperature and dissolved oxygen at Lake Sunapee, New Hampshire, USA, 2014-2023
The Lake Sunapee Protective Association (LSPA) has been monitoring water quality in Lake Sunapee, New Hampshire, USA, since the 1980s. Beginning in the winter of 2014-2015, the LSPA deployed a string of HOBO temperature sensors at a location near Loon Island (43.391N, 72.058W, where their instrumented buoy is located during the summer months) for under-ice water temperature profile monitoring. A HOBO U26 dissolved oxygen sensor was added to this monitoring string during the winter of 2017-2018 through the winter of 2019-2020. All sensors record data in 15-minute intervals over the winter and are downloaded after ice-off. All data have been QAQC'd to remove obviously errant readings and artifacts of maintenance and flag highly suspicious readings.
Hourly water temperature from the San Francisco Estuary, 1986 - 2019
Projected temperature increases due to global climate change are likely to have localized impacts on the San Francisco Estuary (SFE). Increased water temperature in the SFE will lead to challenges for managing water resources. Many native species, such as salmon and smelt, rely on cooler water, and will be further stressed by increased water temperature. While real-time water temperature is collected by several state and federal agencies in the San Francisco Estuary, a landscape-scale synthesis of available water temperature data has not been conducted for the SFE. For this dataset, we compiled continuous water temperature data and associated metadata from the SFE to generate an integrated and usable dataset of known quality for climate and ecological analysis. Data were obtained from the California Data Exchange Center (CDEC; https://cdec.water.ca.gov/) for consistency (data are untreated) and efficiency (existing code to download data directly from CDEC). Data were integrated and standardized to hourly water temperature data in degrees Celsius. A series of quality control (QC) checks were then applied in a consistent manner to all stations. Datasets included in this package include raw hourly data, flagged data, and filtered data (where flagged data are removed). Additionally, information regarding current and historical sensors used for water temperature data collection was obtained from station managers for each station, and compiled in a metadata table.
Water Depths and Water Temperatures near Soil Surface from Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, October 2000 - ongoing
Water depth (from October 2000 to present) and water temperature (from September 2021 to present) are recorded at least hourly at SRS1c (not active), SRS1d, SRS2, SRS3, SRS4, SRS5, and SRS6. Water depth is measured with pressure water level loggers (Infinities USA or HOBO) that record water height relative to the local soil surface. Water temperature near soil surface is measured with HOBO loggers. Note by IM (2021): The water meters at some of the SRS sites have been moved over the years as boardwalks have been reconstructed. There is no set survey datum for these sites, so it is impossible to correct the data to an actual datum. For hydrologic applications, it may be better to use water level data from USGS stations.
Water Depths and Water Temperatures near Soil Surface from Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, August 1999 - ongoing
Water depth (from August 1999 to present) and water temperature (from May 2021 to present) are recorded hourly at TS/Ph1a, TS/Ph2 and TS/Ph3 and every 30 minutes at TS/Ph6a and TS/Ph7a. Water depth is measured with pressure water level loggers (Infinities USA or HOBO) that record water height relative to the local soil surface. Water temperature near soil surface is measured with HOBO loggers. Note by IM (2021): The water meters at some of the TS sites have been moved over the years as boardwalks have been reconstructed. There is no set survey datum for these sites, so it is impossible to correct the data to an actual datum. For hydrologic applications, it may be better to use water level data from USGS stations.
Bull shark catches, water temperatures, salinities, and dissolved oxygen levels in the Shark River Slough, Everglades National Park (FCE) , from May 2005 to May 2009
This dataset provides information on the catches of bull sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected from 2005-2007 indicate that distance from the Gulf of Mexico and dissolved oxygen concentrations have the largest effects on bull shark catch rates. Data are presented for both young of the year sharks, which are concentrated in areas away from the main channel approximately 20km upstream, and older juvenile sharks which are found along the main channel at similar distances upstream. Salinity has a surprisingly weak impact on catches over the time frame initially investigated.
Water Levels and Porewater Temperature data from the Shark River and Taylor River Slough mangrove sites, Everglades National Park (FCE LTER), South Florida, USA: May 2001 - ongoing
Water levels for SRS4 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at Tarpon Bay. Water levels for SRS5 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS6 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS7 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for TS/Ph6a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph7a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 60 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph8 are recorded at 1h intervals. Water level recorder is located in the mangrove forests 40 m inland at the Joe Bay area. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. All water level data are measured by Florida International University.
Subsurface Water Temperatures taken in Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, May 2010 - December 2015
At each site, two vertical columns of temperature sensors (107-L Temperature Probes, Campbell Scientific, Logan, Utah) were installed and connected to data loggers (CR1000 Dataloggers, Campbell Scientific, Logan, Utah). At each, one temperature sensor in a heat shield was installed 2 m above the ground surface. The remaining temperature sensors were installed at or below the ground surface, with the depths and depth intervals depending upon the total depth of the column. The data were collected hourly between May 19, 2010 and December 1, 2015.
Shark catches (longline), water temperatures, salinities, and dissolved oxygen levels, and stable isotope values in the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, May 2005 - ongoing
This dataset provides information on the catches of sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected suggest that distance from the Gulf of Mexico and dissolved have the largest effects on shark catch rates, with most juvenile bull sharks being caught in Tarpon Bay. This dataset includes all sharks caught on longline gear, their morphometric data, and CNS stable isotope analysis for selected individuals.
Continuous groundwater well temperature, salinity and water level measurements at the GCE-LTER Seawater Addition Long-Term Experiment (SALTEx) site from May 2014 to February 2018
The Georgia Coastal Ecosystems LTER Seawater Addition Long-Term Experiment (SALTEx) is a large-scale field experiment designed to simulate saltwater intrusion in a tidal freshwater wetland to predict how chronic (Press) and acute (Pulse) salinization will affect this and other tidal freshwater ecosystems. In order to characterize groundwater salinity, temperature, and plot flooding following experimental manipulation, unvented water pressure, temperature and conductivity were continuously measured in a PVC groundwater well installed at the SALTEx site. Measurements were made at the bottom of the well using a submerged Schlumberger CTD-Diver logger every 15 minutes from 30-May-2014 to 14-Feb-2018. In February 2016 a second CTD-Diver was deployed near the top of the well. Data were downloaded from the loggers using Diver Office communication software, then imported into MATLAB for post-processing, quality control and documentation. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings, then water level, salinity and density were calculated from the measured variables using UNESCO algorithms. These data were collected as part of the Georgia Coastal Ecosystems LTER SALTEx project (http://gce-lter.marsci.uga.edu/public/app/send_project_eml.asp?id=73), and will be updated annually.
Globally distributed lake surface water temperatures collected in situ and by satellites; 1985-2009
Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global dataset of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985-2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues. This dataset accompanies a data publication in the journal Scientific Data
North Temperate Lakes LTER: High Frequency Water Temperature Data - Lake Mendota Pier 2006 - 2008
Water temperature was measured on the pier at 1 and 2 m water depth at a frequency of 1 minute.
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