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172 results for “temperature profile”

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edi56/100

Secchi depth data and discrete depth profiles of water temperature, dissolved oxygen, conductivity, specific conductance, photosynthetic active radiation, oxidation-reduction potential, and pH for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2025

Discrete depth profiles of water temperature, dissolved oxygen, oxidation-reduction potential, conductivity, specific conductance, and pH were collected with multiple handheld water quality probes and discrete depth profiles of photosynthetically active radiation (PAR) were collected with a LI-COR underwater light meter from 2013 to 2025 in five drinking water reservoirs in southwestern Virginia, USA. These reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the Town of Pulaski, Virginia. All discrete depth profiles were collected on approximately 1-meter intervals. The data package consists of two datasets: 1) Secchi depth data; and 2) discrete depth profiles of multiple water quality variables measured by handheld sensors. The Secchi data and discrete depth profiles were measured at the deepest site of each reservoir adjacent to the dam, as well as other in-reservoir sites. Handheld sensor measurements were also collected at a gauged weir on the primary inflow tributary, other inflows, and outflows at Falling Creek Reservoir; inflows and outflows at Beaverdam Reservoir; and inflows at Carvins Cove Reservoir. In 2021, YSI handheld data were also collected from a littoral site in Beaverdam Reservoir. In 2025, YSI handheld data were collected monthly from June to October from nine littoral sites around the perimeter of Falling Creek Reservoir. From 2024 - 2025, additional within-reservoir depth profiles were collected in Carvins Cove Reservoir and multiple sites. Data were collected approximately fortnightly in the spring months (March - Ma

openCC (other)Jan 2026View details →
edi56/100

Time series of high-frequency profiles of depth, temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, turbidity, pH, oxidation-reduction potential, photosynthetically active radiation, colored dissolved organic matter, phycocyanin, phycoerythrin, and descent rate for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2025

Depth profiles of water biogeochemical properties were collected with SeaBird Electronics (SBE) Conductivity, Temperature, and Depth (CTD) profilers from 2013-2025 at five drinking water reservoirs in southwestern Virginia, USA. The study reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of CTD depth profiles measured at the deepest site of each reservoir adjacent to the dam as well as other upstream reservoir sites. The profiles were collected approximately fortnightly in the spring months, weekly in the summer and early autumn, and monthly in the late autumn and winter. Beaverdam Reservoir, Carvins Cove Reservoir, and Falling Creek Reservoir were sampled every year in the dataset (2013-2025); Spring Hollow Reservoir was only sampled 2013-2017 and 2019; and Gatewood Reservoir was only sampled in 2016. Data availability differs across years due to additional sensors that have been added or replaced over time. From 2013-2016, profiles were taken with a CTD equipped with an SBE 43 Dissolved Oxygen sensor and an ECO FLNTU sensor for turbidity and chlorophyll. From 2017-2025, profiles were taken with a CTD equipped with an SBE 43 Dissolved Oxygen sensor, an ECO FLNTU sensor for turbidity and chlorophyll, a PAR-LOG ICSW sensor for photosynthetically active radiation, and a SBE 27 pH and ORP (oxidation-reduction potential) sensor. In 2022 and 2023, profiles were also taken with an additional CTD equipped with an SBE 43 Dissolved Oxygen sensor; an ECO Triplet Scattering Fluorescence sensor for

openCC (other)Jan 2026View details →
edi52/100

Temperature and dissolved oxygen profiles for three Swiss lakes: 1972-2016

Understanding change through time in dissolved oxygen (DO) in lakes requires the use of long-term historical monitoring data. The data contained herein include historical temperature and dissolved oxygen profiles from three Swiss lakes collected between the years 1972 to 2017. These three lakes are a subset of a larger set of lakes that were used to examine the relationship between long-term changes in the timing of lake stratification and changes in the amount of oxygen-depleted water present in the water column.

openCC (other)Nov 2022View details →
zenodo48/100

Shipboard Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data collected during hypoxia surveys along six hydrographic sampling lines within Olympic Coast National Marine Sanctuary, 2004–2015

<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State&rsquo;s outer coast within Olympic Coast National Marine Sanctuary (OCNMS). Measurements were made along six cross-shelf hydrographic sampling lines during a series of hypoxia survey cruises from 2004 &ndash; 2015. The 398 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific&rsquo;s SBE Data Processing application using six of the modules in the following order: Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average. These processing steps and associated methods are the same as those used to process CTD data collected during OCNMS mooring maintenance cruises (<a href="https://www.sciencedirect.com/science/article/pii/S2352340924001422">Risien et al., 2024</a>) and along the Newport Hydrographic Line (<a href="https://www.sciencedirect.com/science/article/pii/S2352340922001342">Risien et al., 2022</a>) located off the central Oregon coast.</p> <table> <tbody> <tr> <td><strong>Station Name &nbsp;&nbsp;</strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>CA010</td> <td>48.1661oN</td> <td>124.7540oW</td> <td>10</td> </tr> <tr> <td>CA020</td> <td>48.1661oN</td> <td>124.7598oW</td> <td>20</td> </tr> <tr> <td>CA030</td> <td>48.1659oN</td> <td>124.7783oW</td> <td>30</td> </tr> <tr> <td>CA040</td> <td>48.1659oN</td> <td>124.7852oW</td> <td>40</td> </tr> <tr> <td>CA045</td> <td>48.1659oN</td> <td>124.8335oW</td> <td>45</td> </tr> <tr> <td>CA050</td> <td>48.1658oN</td> <td>124.8578oW</td> <td>50</td> </tr> <tr> <td>CA060</td> <td>48.1659oN</td> <td>124.8843oW</td> <td>60</td> </tr> <tr> <td>CA070</td> <td>48.1655oN</td> <td>124.9011oW</td> <td>70</td> </tr> <tr> <td>CA080</td> <td>48.1657oN</td> <td>124.9141oW</td> <td>80</td> </tr> <tr> <td>CA090</td> <td>48.1659oN</td> <td>124.9247oW</td> <td>90</td> </tr> <tr> <td>CA100</td> <td>48.1658oN</td> <td>124.9319oW</td> <td>100</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>TH030</td> <td>47.8759oN</td> <td>124.6481oW</td> <td>30</td> </tr> <tr> <td>TH035</td> <td>47.8761oN</td> <td>124.7024oW</td> <td>35</td> </tr> <tr> <td>TH040</td> <td>47.8760oN</td> <td>124.7281oW</td> <td>40</td> </tr> <tr> <td>TH050</td> <td>47.8761oN</td> <td>124.7567oW</td> <td>50</td> </tr> <tr> <td>TH060</td> <td>47.8765oN</td> <td>124.7822oW</td> <td>60</td> </tr> <tr> <td>TH070</td> <td>47.8765oN</td> <td>124.8084oW</td> <td>70</td> </tr> <tr> <td>TH080</td> <td>47.8768oN</td> <td>124.8415oW</td> <td>80</td> </tr> <tr> <td>TH090</td> <td>47.8769oN</td> <td>124.8868oW</td> <td>90</td> </tr> <tr> <td>TH100</td> <td>47.8769oN</td> <td>124.9182oW</td> <td>100</td> </tr> <tr> <td><strong>Hoh Head (HH)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>HH025</td> <td>47.7688oN</td> <td>124.5605oW</td> <td>25</td> </tr> <tr> <td>HH042</td> <td>47.7688oN</td> <td>124.6428oW</td> <td>42</td> </tr> <tr> <td>HH065</td> <td>47.7688oN</td> <td>124.7401oW</td> <td>65</td> </tr> <tr> <td><strong>Raft River (RR)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>RR015</td> <td>47.4632oN</td> <td>124.3748oW</td> <td>15</td> </tr> <tr> <td>RR020</td> <td>47.4644oN</td> <td>124.4510oW</td> <td>20</td> </tr> <tr> <td>RR042</td> <td>47.4632oN</td> <td>124.5199oW</td> <td>42</td> </tr> <tr> <td>RR065</td> <td>47.4629oN</td> <td>124.6074oW</td> <td>65</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>CE010</td> <td>47.3541oN</td> <td>124.3347oW</td> <td>10</td> </tr> <tr> <td>CE020</td> <td>47.354oN</td> <td>124.3608oW</td> <td>20</td> </tr> <tr> <td>CE030</td> <td>47.3538oN</td> <td>124.3913oW</td> <td>30</td> </tr> <tr> <td>CE040</td> <td>47.3534oN</td> <td>124.4678oW</td> <td>40</td> </tr> <tr> <td>CE050</td> <td>47.3532oN</td> <td>124.5064oW</td> <td>50</td> </tr> <tr> <td>CE060</td> <td>47.3529oN</td> <td>124.5510oW</td> <td>60</td> </tr> <tr> <td>CE070</td> <td>47.3528oN</td> <td>124.5823oW</td> <td>70</td> </tr> <tr> <td>CE080</td> <td>47.3527oN</td> <td>124.6158oW</td> <td>80</td> </tr> <tr> <td>CE090</td> <td>47.3526oN</td> <td>124.6491oW</td> <td>90</td> </tr> <tr> <td>CE100</td> <td>47.3522oN</td> <td>124.6754oW</td> <td>100</td> </tr> <tr> <td><strong>Moclips (MO)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>MO010</td> <td>47.2214oN</td> <td>124.2394oW</td> <td>10</td> </tr> <tr> <td>MO015</td> <td>47.2214oN</td> <td>124.2599oW</td> <td>15</td> </tr> <tr> <td>MO020</td> <td>47.2214oN</td> <td>124.2791oW</td> <td>20</td> </tr> <tr> <td>MO030</td> <td>47.2195oN</td> <td>124.3347oW</td> <td>30</td> </tr> <tr> <td>MO042</td> <td>47.2195oN</td> <td>124.3958oW</td> <td>42</td> </tr> </tbody> </table>

opencc-by-4.0May 2024View details →
zenodo48/100

Snowpack temperature profile dataset from a boreal forest watershed in eastern Canada.

<p>This dataset presents snow temperature profiles from nine different boreal forest sites in eastern Canada collected over two consecutive winters, 2016-17 and 2017-18. The dataset includes snowpack temperature profiles,&nbsp;snow depth, air temperature, and soil temperature. In addition, the two flux towers provided us with the additional heat and water vapour fluxes.&nbsp;We also present&nbsp;data extracted from intensive snow coring and snowpit surveys, conducted on a weekly and bi-weekly basis. Additionally, stable water isotope data collected from individual snowpack are presented here.&nbsp;</p> <p>To learn more about the additional information about the data, please read the &quot;Readme.txt&quot; file.&nbsp;</p>

opencc-by-4.0Mar 2023View details →
edi48/100

Hourly time series of Ives Lake (Huron Mountains, Marquette County, MI) Water Temperature-Depth Profiles, 2013-2022 (continuing study)

Long-term measurements of lake temperatures are essential to providing insights into local and regional changes in climate since large, still water bodies effectively act as a high-frequency filter. Ives Lake is a 30.7 m deep water body in northern Marquette County, in Michigan's Upper Peninsula. Beginning in 2013, temperature readings have been collected hourly from a string of twelve sensors located near the deepest point of the lake (approximately 46.84874 N lat, 87.84895 W long; identified by sonar survey in 2010 by first author). Measurements are continuing. The purpose of the project is to collect a data record of sufficient duration to determine if water temperatures are warming, and if the dates of autumn lake turnover are shifting toward later in the year.

openCC (other)Nov 2023View details →
edi48/100

Missouri reservoir profile data including temperature, depth, and oxygen profiles (1989-2022)

This dataset of limnological profiles starts in 1989 and is from 250 reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. After 2017, sondes were upgraded to Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), phycoerythrin (PE), and turbidity. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few profiles were taken from bridges and docks. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into a single file for 1989-2016 and then annual compiled datasets for 2017 and beyond. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.

openCC (other)Jan 2026View details →
edi48/100

Missouri reservoir profile data including depth, temperature, oxygen, photopigments, conductivity, pH, turbidity, and oxidative-reductive potential starting in 2023

This dataset of annual limnological profiles starts in 2023 and is from reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. Sondes used were Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), and turbidity. After May 2024, the turbidity sensor was replaced with a phycoerythrin (PE) sensor. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into single files for each year. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.

openCC (other)Jan 2026View details →
edi48/100

Limnological data from nearly 400 lakes across the Americas and New Zealand with a focus on vertical profiles of temperature, UV radiation, and optical properties

Two and a half decades of limnological data have been collected from nearly 400 lakes, encompassing a wide range of systems and a broad range of geography. This data set comprises one of the largest and most complete sets of measurements of underwater ultraviolet (UV) transparency available in the world. The data include a suite of 36 variables, with a focus on the optical characteristics. Lakes range from pristine natural lakes to manmade reservoirs. The systems represented in this data set are largely located in North America, from the northeastern United States to Alaska, and alpine and subalpine lakes in the Rocky Mountains of the United States and Canada. Lakes included range from iconic Lake Tahoe, and Castle Lake in northern California, to lakes in the South American Patagonian region, as well as New Zealand. Data were most often collected during the summer, and in some lakes span multiple years (with year-round data since 2006 in Lake Tahoe). The data here are contained in four files, including LakeData.csv, SiteInformation.csv, Methods.csv, and Variables.csv. The main data are in LakeData.csv. SiteInformation.csv, Methods.csv, and Variables.csv support the main data file with descriptions of the sampling sites, methods by which samples were processed, and descriptions of the variables that were measured, respectively. This data set complements the site-intensive limnological data that we published in EDI on 30+ years of data from 3 lakes in the Poconos Mountains region of Pennsylvania, USA. This complementary data set can be accessed at https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=186

openCC0Dec 2023View details →
edi48/100

Keswick Reservoir Temperature Profile Data (2017-2019)

This dataset contains the Keswick Reservoir temperature profile data collected by using remote logging thermistors (temperature loggers) attached to a cable system at the log boom above Keswick Dam in three monitoring seasons in 2017, 2018 and 2019. Field data monitoring installation was performed by U.S. Bureau of Reclamation (Reclamation), with support from Watercourse Engineering, Inc. (Watercourse) as part of the Shasta Lake and Keswick Reservoir Flow and Temperature Modeling study conducted by Watercourse in cooperation with Reclamation. All data were collected using HOBO Water Temperature Pro v2 Data Loggers and reported to 0.01oF.

openCC0Dec 2020View details →
edi48/100

Global data set of long-term summertime vertical temperature profiles in 153 lakes

Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change.

openCC0Sep 2022View details →
edi48/100

Monthly vertical profiles of salinity, temperature, pressure, oxygen and photosynthetically-available radiation in Sapelo River, Doboy Sound, Duplin River and Altamaha River transect surveys from April 2008 to April 2015

Monthly hydrographic surveys were performed along the Sapelo River, Doboy Sound, Duplin River and Altamaha River from April 2008 to April 2015. Vertical CTD profiles were collected from the surface to bottom during low and high tide phases at fixed stations chosen to coincide with long-term GCE-LTER moorings. Conductivity, temperature, pressure, photosynthetically-available radiation (PAR) and oxygen concentration were measured at 8 Hz using a SeaBird Electronics SBE-37 instrument, and depth, salinity and sigma-t and oxygen saturation were calculated using UNESCO algorithms. Data values collected during the upcast were deleted. This data set was collected as part of the Georgia Coastal Ecosystems LTER monthly hydrographic monitoring program, and will be updated approximately annually to include the latest observations.

openCustomJan 2020View details →
edi48/100

Conductivity, temperature, and depth (CTD) vertical profiles from Lake Joyce, McMurdo Dry Valleys, Antarctica, November 2014

Vertical profiles of conductivity, temperature, and depth (CTD) were collected from Lake Joyce, a perennially ice-covered lake in the McMurdo Dry Valleys of Antarctica. Water column observations were made in November 2014 using a YSI 6600 multiparameter probe in the deepest region of the lake, as identified by Mackey et al. (2018). The water column was accessed by drilling a 10-inch wide hole through the perennial ice cover using a Jiffy drill. This data package includes CTD profiles, as well as measurements of salinity, total dissolved solids (TDS), dissolved oxygen (DO), pH, and pressure.

openCC (other)Apr 2025View details →
edi48/100

Lake Fryxell under-ice conductivity, temperature, and depth (CTD) profiles, McMurdo Dry Valleys, Antarctica, January 2025

To characterize the upper ~2 m of the water column beneath the ~3 m ice cover in Lake Fryxell, located in the McMurdo Dry Valleys of Antarctica, 27 CTD (conductivity, temperature, depth) profiles were collected at ~5 m horizontal spacing along a transect spanning the dive hole to the shoreline. Measurements were made using a YSI Castaway CTD mounted on a 1 m mast atop a remotely operated vehicle (ROV), profiling upward from ~2 m below the ice-water interface. Using an ROV rather than drilling a hole through the ice was intended to minimize artifacts associated with ice openings. Sampling late in the austral summer targeted conditions during maximum seasonal ice melt.

openCC (other)Dec 2025View details →
edi48/100

Elevational Transects (ET): Soil temperature depth profiles from Garwood, Miers, and Taylor Valley, McMurdo Dry Valleys, Antarctica (2019-2024, ongoing)

As part of the McMurdo Dry Valleys Long Term Ecological Research (LTER) project, the Elevational Transects (ET) study was established in 1993 to investigate how elevation and topographic variation influence soil biotic communities and associated soil properties in the McMurdo Dry Valleys of Antarctica. Transects consisting of low-, mid-, and high-elevation sites were initially established in the Bonney, Hoare, and Fryxell basins of Taylor Valley, with additional transects added in Garwood and Miers Valleys during the 2012-2013 austral summer. This data package contains year-round soil temperature measurements recorded at four depths (0, 5, 10, and 20 cm) by HOBO dataloggers installed at the mid-elevation sites of each valley during the 2018–2019 austral summer.

openCC (other)May 2025View details →
edi48/100

Ground temperature profiles from DVDP borehole 11 at Explorers Cove, McMurdo Dry Valleys, Antarctica (2020-2025, ongoing)

The Dry Valley Drilling Project (DVDP) drilled multiple boreholes throughout Antarctica’s McMurdo Dry Valleys in the early 1970s, several of which remain open and accessible. DVDP borehole 11, with a total depth of 327.86 m, is located adjacent to the Explorers Cove Meteorological Station (EXEM), operated by the McMurdo Dry Valleys Long Term Ecological Research program (MCM LTER). In January 2020, the MCM LTER instrumented this borehole with a string of thermistors to monitor ground temperatures through the permafrost. Sensors were installed at depths of 1, 2, 3, 4, 5, 10, 20, and 30 m, providing ongoing measurements of subsurface thermal conditions at Explorers Cove.

openCC (other)Jan 2026View details →
edi48/100

Conductivity, temperature, and depth (CTD) vertical profiles collected from lakes in the McMurdo Dry Valleys, Antarctica (1993-2025, ongoing)

As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a series of Taylor Valley lakes have been monitored for conductivity, temperature, and depth (CTD). A Seabird instrument was used to record CTD profiles in these perennial ice covered lakes.

openCC (other)Oct 2025View details →
zenodo44/100

Fiber-optic Distributed Temperature Sensing and Wind Profiler Data during the Shallow Cold Pool Experiment

<p>The <a href="https://www.eol.ucar.edu/field_projects/scp">Shallow Cold Pool (SCP) experiment</a> was an <a href="https://www.eol.ucar.edu/observing_facilities/isfs">Integrated Surface Flux System (ISFS)</a> deployment conducted by the <a href="https://ncar.ucar.edu/">National Center for Atmospheric Research (NCAR)</a>, the <a href="https://ceoas.oregonstate.edu/">College of Earth, Ocean and Atmospheres (CEOAS)</a>, the <a href="https://bee.oregonstate.edu/">Department of Biological &amp; Ecological Engineering (BEE)</a>, and the <a href="https://ctemps.org/">Center for Transformative Environmental Monitoring Programs (CTEMPS)</a> of <a href="https://oregonstate.edu/">Oregon State University</a>, in a shallow gully within the Pawnee Grasslands, Coloradp, USA. The primary goal of SCP was to examine the formation and maintenance of common shallow cold pools. These cold pools had not been previously examined with turbulence measurements and very little was known about their dynamics and interaction with gravity waves and other submesoscale motions.</p> <p>SCP consisted of a dense network of ultrasonic anemometers with 19 units being installed at 1m above ground level (agl) and 8 being mounted at different heights on a 20m high tower. In addition, air temperature, humidity, and carbon dioxide concentrations measurements were taken. This data can be found on <a href="https://data.eol.ucar.edu/project/SCP">https://data.eol.ucar.edu/project/SCP</a>.</p> <p>The unique observational technique featured in SCP was a cross-valley transect of the innovative active and passive fiber-optic distributed sensing technique (FODS) using a Distributed Temperature Sensing (DTS) unit (Model Ultima SR, Silixa, London, UK) as well as a ground-based acoustic wind profiler (SODAR, PCS2000-24, Metek GmbH, Elmshorn, Germany) in addition to the classical sonic anemometer network. The data archived in this submission publishes the FODS data and contains data for nine (9) nights between 16th November until 27th November between the hours of 19:00 and 05:00 MST (Local time). Details of the FODS setup are contained in <a href="https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3508?af=R">Pfister et al. (2019)</a> and <a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015GL066729">Sayde et al. (2015</a>).<br> The fiber-optic cross-valley transect was 240m long and stretched from the North to the South shoulder of the gully and contained FODS observations at three heights (0.5m, 1m, 2m agl). By combining passive and active FODS, air temperatures and wind speeds were measured spatially continuously with a temporal and spatial resolution of 5s and 25cm, respectively. Air temperatures were measured with an unheated white-PVC jacketed optical glass fiber cable with an outer diameter of 0.9mm, while for the wind speed measurements an additional actively heated stainless-steel uncoated fiber-optic cable (1.3mm outer diameter) was deployed. Wind speeds were derived from the difference between the heated and unheated fiber-optic pair similar to a hotwire anemometer (<a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015GL066729">Sayde et al. 2015</a>).<br> The acoustic wind profiler (Sound Detection and Ranging, SODAR) was installed at the gully bottom about 200m down the gully from the fiber-optic transect (between station A18 and A19) and measured with a 5-min resolution, a 10-m gate range, and 17000 Hz, see map in <a href="https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3508?af=R">Pfister et al. (2019)</a>. The observational range was between 10m to 320m agl. The data provided is the cluster data output of the wind profiler, which is quality-controlled by the internal data processing software. The published data include horizontal wind speed (speed), wind direction (direction), unrotated along-wind component (u_unrot), unrotated cross-wind component (v_unrot), and unrotated vertical-wind component (w_unrot).</p> <p>By combining the fiber-optic distributed sensing, the sensor network, and the wind profiler, we were able to investigate specific class of submeso-scale motions in detail. The submeso-scale motion occurred frequently during SCP, significantly impacted air temperature, wind speed and direction, as well as the near-surface turbulence within less than a few minutes. These motions are not described or categorized by existing boundary layer regimes or concepts. Consequently, further research on submeso-scale motions using continuous FODS measurements is necessary to better understand the stable boundary layer.</p> <p>&nbsp;</p> <p>Pfister, L., Sayde, C., Selker, J., Mahrt, L., &amp; Thomas, C. K. (2019). Classifying the Nocturnal Atmospheric Boundary Layer into Temperature and Flow Regimes. <em>Quart. J. Roy. Meteorol. Soc.</em>, <em>145</em>(721), 1515&ndash;1534. <a href="https://doi.org/10.1002/qj.3508">https://doi.org/10.1002/qj.3508</a></p> <p>&nbsp;</p> <p>Sayde, C., Thomas, C. K., Wagner, J., &amp; Selker, J. S. (2015). High-resolution wind speed measurements using actively heated fiber optics. <em>Geophys. Res. Lett.</em>, <em>42</em>(22), 10,064&ndash;10,073. <a href="https://doi.org/10.1002/2015GL066729">https://doi.org/10.1002/2015GL066729</a></p>

opencc-by-4.0Dec 2020View details →
zenodo44/100

Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data from shipboard surveys collected within Olympic Coast National Marine Sanctuary, 2005-2023

<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State&rsquo;s outer coast within Olympic Coast National Marine Sanctuary towards the northernmost extent of the California Current System. Measurements were made at fourteen hydrographic stations during mooring deployment, recovery, and maintenance cruises between the months of May and October from 2005&ndash;2023. The 792 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific&rsquo;s SBE Data Processing application using six of the modules in the following order: <em>Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average</em>. These processing steps and associated methods are the same as those used to process CTD data that make up the&nbsp;<a href="../records/5814071">Newport Hydrographic Line time series</a> located off the central Oregon coast thus allowing for a direct comparison between the two regions.</p> <table> <tbody> <tr> <td><strong>Station Name &nbsp;&nbsp;</strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Makah Bay (MB)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>MB015</td> <td>48.3254oN</td> <td>124.6768oW</td> <td>15</td> </tr> <tr> <td>MB042</td> <td>48.3240oN</td> <td>124.7354oW</td> <td>42</td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>CA015</td> <td>48.1663oN</td> <td>124.7568oW</td> <td>15</td> </tr> <tr> <td>CA042</td> <td>48.1660oN</td> <td>124.8234oW</td> <td>42</td> </tr> <tr> <td>CA065&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</td> <td>48.1659oN</td> <td>124.8949oW</td> <td>65</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>TH015</td> <td>47.8761oN</td> <td>124.6195oW</td> <td>15</td> </tr> <tr> <td>TH042</td> <td>47.8762oN</td> <td>124.7334oW</td> <td>42</td> </tr> <tr> <td>TH065&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</td> <td>47.8767oN</td> <td>124.7967oW</td> <td>65</td> </tr> <tr> <td><strong>Kalaloch (KL)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>KL015</td> <td>47.6008oN</td> <td>124.4284oW</td> <td>15</td> </tr> <tr> <td>KL027</td> <td>47.5946oN</td> <td>124.4971oW</td> <td>27</td> </tr> <tr> <td>KL050&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</td> <td>47.5933oN</td> <td>124.6112oW</td> <td>50</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> <tr> <td>CE015</td> <td>47.3568oN</td> <td>124.3481oW</td> <td>15</td> </tr> <tr> <td>CE042</td> <td>47.3531oN</td> <td>124.4887oW</td> <td>42</td> </tr> <tr> <td>CE065&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</td> <td>&nbsp;47.3528oN</td> <td>124.5669oW</td> <td>65</td> </tr> </tbody> </table>

opencc-by-4.0Jan 2024View details →
zenodo44/100

Air/Snow temperature vertical profiles at different nodes of the 'Limnopolar Lake' CALM site, in Byers Península Livingston Island, Antarctica (2013-2022)

<div> <div>&nbsp;</div> </div> <div> <p>Air or seasonal snow temperature data were collected at different heights above the ground between 2013 and 2022 using an array of temperature micro-loggers (iButton models by Maxim) mounted on vertical wooden masts. These measurements were conducted at various nodes within the 100x100 m 'Limnopolar Lake' CALM site (A25) grid of the PERMATHERMAL network, managed by the University of Alcal&aacute;, Madrid, Spain, to monitor active layer thickness on Byers Peninsula, Livingston Island, South Shetland Islands, Antarctica.</p> <p>In 2013, nine arrays were installed at nodes with relative coordinates (00,00), (00,05), (00,10), (05,00), (05,05), (05,10), (10,00), (10,05), and (10,10). Measurements were taken at heights of 2.5, 5, 10, 15, 20, 25, 30, and 40 cm above the ground surface using DS1921G iButton loggers, which recorded air/snow temperatures every 4 hours. This experiment, referred to as 'Mini', was active for only one year and is now discontinued.</p> <p>Between 2017 and 2022, three arrays were installed at nodes (00,00), (05,05), and (10,10). These arrays measured air/snow temperatures at heights of 2.5, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, and 160 cm above the ground surface using DS1922L iButton loggers, which recorded temperatures every 3 hours. This experiment, referred to as 'HR', has also been discontinued.</p> </div>

opencc-by-4.0Nov 2024View details →

ScienceDex guides

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record