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13 results for “hydrography”
Vertical hydrography profiles from CTD rosette downcasts during PolarFront cruise 2023-08
<p>PolarFront 2023-08 CTD profiles</p><p>Pressure, temperature, salinity, and other physical properties of seawater from 31 vertical profiles sampled during the PolarFront 2023-08 cruise. Only downcast values are used to avoid errors caused by turbulence on the upcast. Basic data processing were done using Sea-Bird Scientific software SBE Data Processing (v7.26): converting to physical units, filtering for outliers, and bin-averaging over 1 m bins. The final data accuracy is ±0.5 dbar for pressure, ±0.002˚C for sea water temperature and ±0.003 for sea water salinity.</p><p>Example final data `head -n3 stnr1085.xls`:</p><blockquote><p>scan: Scan Count depSM: Depth [salt water, m] prDM: Pressure, Digiquartz [db] t090C: Temperature [ITS-90, deg C] c0S/m: Conductivity [S/m] sal00: Salinity, Practical [PSU] sigma-t00: Density [sigma-t, kg/m^3 ] svCM: Sound Velocity [Chen-Millero, m/s] flSP: Fluorescence, Seapoint sbeox0PS: Oxygen, SBE 43 [% saturation] seaTurbMtr: Turbidity, Seapoint [FTU] par/sat/log: PAR/Logarithmic, Satlantic [umol photons/m^2/sec] sbeox0ML/L: Oxygen, SBE 43 [ml/l] depSM: Depth [salt water, m], lat = 74.9995 potemp090C: Potential Temperature [ITS-90, deg C] sal00: Salinity, Practical [PSU] sigma-é00: Density [sigma-theta, kg/m^3] svCM: Sound Velocity [Chen-Millero, m/s] oxsolML/L: Oxygen Saturation, Garcia & Gordon [ml/l] flag: flag 243 3.955 4.000 8.9775 3.708699 34.9575 27.0886 1486.13 7.9014e-01 105.842 1.003 2.0359e+01 6.8367 3.958 8.9771 34.9576 27.0886 1486.13 6.45936 0.0000e+00 327 4.945 5.000 8.9787 3.708880 34.9577 27.0885 1486.15 7.4764e-01 99.487 0.991 1.4706e+01 6.4261 4.948 8.9782 34.9578 27.0886 1486.15 6.45918 0.0000e+00</p></blockquote><p> File types</p><p>Each station number has multiple data files from various steps of processing: `ls stnr1085*`: </p><p>`stnr1085_bin.cnv stnr1085_bin.wmf stnr1085.bl stnr1085.btl stnr1085.btx stnr1085.cnv stnr1085.hdr stnr1085.hex stnr1085_RAW.cnv stnr1085.xls`</p><p>Notice that the *.xls are plain ascii text files with tab-separated values. These may be converted to utf-8 using `iconv -f iso8859-1 -t utf8`</p><ul><li>*.bl = Bottle log information. Output bottle file, containing bottle firing sequence number and position, data, time, and beginning and ending scan numbers for each bottle closure. Beginning and ending scan numbers correspond to approximately 1.5-second duration for each bottle.</li><li>*.btl = Bottle files. Averaged data for each bottle.</li><li>*.cnv = Data converted to engineering units.</li><li>*hdr = Header information.</li><li>.hex = Hexadecimal data file.</li><li>*.xls = Converted data binned to 1 m as ascii text (tsv).</li><li>*.xlmcon = Instrument configuration.</li><li>*_bin.cnv = Converted data binned to 1 m as ascii data.</li><li>*_bin.wmf = Graphic of converted and 1m-binned data. *_RAW.cnv = Raw data as text file.</li></ul>
Multiple years of Seaglider observations of hydrography, dissolved oxygen, chlorophyll a, and optical backscatter at Station ALOHA
<p><strong>File descriptions:</strong></p> <p>Seaglider missions are identified as GLIDER_MISSION<em> </em>(i.e. sg148_12 is glider 148, mission 12) and each have three files associated. For example:</p> <ol> <li><strong>sg148_12_qc_pass.xlsx</strong> contains only quality controlled (QC flags = 1) core data for an entire mission. Core data may include temperature, conductivity, salinity, potential density anomaly, calibrated dissolved oxygen concentrations, calibrated chlorophyll <em>a</em> concentrations, and the backscattering coefficient due to particles (bbp) at up to three wavelengths (470, either 650 or 660, and 700 nm) and spike flags. Bbp data is corrected with an <em>in situ</em> dark subtraction from near 200 m deep. Associated metadata (datetime, latitude, longitude, depth, dive number, and vertical profile direction) is also included.</li> <li><strong>sg148_12_alldata.nc </strong>contains all data (i.e. all QC flag levels) and associated quality control flags. In addition to core and metadata, factory-only calibrated observations (e.g. dissolved oxygen concentrations, chlorophyll <em>a</em> concentrations, and bbp) are listed. </li> <li><strong>sg148_12_qctests.nc</strong><em> </em>contains all quality control test values (pass: QC = 1, input flag: QC = 2, questionable data QC = 3, bad data: QC = 4). The maximum test QC flag value (e.g. out of range, density inversions, bioflouling, etc.) was passed to the variable QC flag (e.g chla_qcflag or salin_qcflag). . </li> </ol> <p> </p> <p><strong>Dataset description:</strong></p> <p>The SCOPE-ALOHA Seaglider dataset was designed to monitor the spatial and temporal variability of physical and biogeochemical properties around the long term sampling site Station ALOHA (22°45′N, 158°W). Seagliders are autonomous underwater vehicles that take high frequency (up to 0.2 Hz in our dataset), depth-resolved observations over several months and can be used to map large spatial features. The gliders depicted in this study were equipped with sensors to measure temperature, salinity, pressure, dissolved oxygen concentration (O2), chlorophyll a concentration (Chl a) from fluorescence (excitation/emission lambda = 470/695 nm), and the particulate backscattering coefficient (bbp) at three wavelengths (lambda = 470 nm, 700 nm, and either 650 or 660 nm depending upon mission). Vertical profiles down to at least 200 m were collected for all sensors over periods of several months per mission. This dataset comprises 18 missions between 2008 and 2023 centered on Station ALOHA, totaling over 20,000 depth profiles. Chlorophyll <em>a</em> and oxygen concentrations are calibrated with discrete observations. Particulate backscattering coefficients are corrected with an additional dark subtraction. This dataset is an improvement on the raw data files as they are quality controlled, calibrated, and corrected.</p> <p>Raw data files can be found at https://hahana.soest.hawaii.edu/seagliders/index.php.</p> <p>version notes:</p> <p>v1.0 original</p> <p>v1.1 Metaadata tab on xlsx files edited, no change to data</p> <p>v1.2 fixed error: variable qc flags added to alldata.nc files</p> <p>v1.3 Added error estimates and CF_standard_name to alldata.nc files</p> <p><strong>Methods:</strong></p> <p><em><strong>Code for all processing steps is on GitHub </strong></em><strong>(</strong><em><strong>https://github.com/cathygarcia/SeagliderDataprocessing</strong></em><strong>)</strong><em><strong>.</strong> The steps listed here are a brief summary. </em></p> <p><em>Temperature, Conductivity, Salinity, and Potential Density Anomaly</em></p> <ul> <li>Both temperature and conductivity profiles were lag corrected.</li> <li>Practical salinity was calculated using the Gibbs Seawater Toolbox (gsw_SP_from_C.m), and then converted to absolute salinity (gsw_SA_from_SP.m). </li> <li>Potential density anomaly was calculated with respect to a reference water pressure of 0 db using the Gibbs Seawater Toolbox (gsw_sigma0.m).</li> </ul> <p><em>Dissolved oxygen concentrations</em></p> <ul> <li>Raw optode phase values proceeded through a series of corrections to account for the effects of temperature, salinity, pressure, and time response in addition to sensor drift (Bittig et al., 2018, Barone et al., 2019).</li> <li> Optode phase values were converted to dissolved oxygen concentrations, and re-calibrated using discrete Winkler measurements. </li> </ul> <p><em>Chlorophyll</em> <em>a</em></p> <ul> <li>Factory-calibrated chlorophyll <em>a</em> observations were re-calibrated using discrete measurements of either HPLC chlorophyll <em>a </em>(16 missions) or fluorometric chlorophyll <em>a</em> (2 missions).</li> <li>Daytime chlorophyll <em>a</em> values are not quench corrected, and may be lower than actual values. It is recommended to use nighttime profiles near the surface. </li> <li>Additionally, a spike flag is included based on published protocol (Briggs et al., 2011).</li> </ul> <p><em>Backscattering coefficient due to particles (bbp)</em></p> <ul> <li>Factory-calibrated bbp values could have a large offset, that was not expected based on natural variability.</li> <li>A mission-specific deep dark correction (1st percentile of bbp at 190-200 m) was subtracted for each bbp dataset. Both the uncorrected and corrected data are available.</li> <li>Additionally, a spike flag is included based on published protocol (Briggs et al., 2011).</li> </ul> <p> </p>
Supporting data of: Hydrography and food distribution during a tidal cycle above a cold-water coral mound
<p>This file contains the raw data and data analyses scripts to:</p> <p>Hydrography and food distribution during a tidal cycle above a cold-water coral mound</p> <p>Evert de Froe, Sandra R. Maier, Henriette G. Horn, George A. Wolff, Sabena Blackbird, Christian Mohn, Mads Schultz, Anna-Selma van der Kaaden, Chiu H. Cheng, Evi Wubben, Britt van Haastregt, Eva Friis Moller, Marc Lavaleye, Karline Soetaert, Gert-Jan Reichart, Dick van Oevelen.</p> <p>Deep Sea Research Part I: Oceanographic Research Papers, 2022,<br> ISSN 0967-0637,<br> https://doi.org/10.1016/j.dsr.2022.103854.<br> <strong>Abstract: </strong>Cold-water corals (CWCs) are important ecosystem engineers in the deep sea that provide habitat for numerous species and can form large coral mounds. These mounds influence surrounding currents and induce distinct hydrodynamic features, such as internal waves and episodic downwelling events that accelerate transport of organic matter towards the mounds, supplying the corals with food. To date, research on organic matter distribution at coral mounds has focussed either on seasonal timescales or has provided single point snapshots. Data on food distribution at the timescale of a diurnal tidal cycle is currently limited. Here, we integrate physical, biogeochemical, and biological data throughout the water column and along a transect on the south-eastern slope of Rockall Bank, Northeast Atlantic Ocean. This transect consisted of 24-hour sampling stations at four locations: Bank, Upper slope, Lower slope, and the Oreo coral mound. We investigated how the organic matter distribution in the water column along the transect is affected by tidal activity. Repeated CTD casts indicated that the water column above Oreo mound was more dynamic than above other stations in multiple ways. First, the bottom water showed high variability in physical parameters and nutrient concentrations, possibly due to the interaction of the tide with the mound topography. Second, in the surface water a diurnal tidal wave replenished nutrients in the photic zone, supporting new primary production. Third, above the coral mound an internal wave (200 m amplitude) was recorded at 400 m depth after the turning of the barotropic tide. After this wave passed, high quality organic matter was recorded in bottom waters on the mound coinciding with shallow water physical characteristics such as high oxygen concentration and high temperature. Trophic markers in the benthic community suggest feeding on a variety of food sources, including phytodetritus and zooplankton. We suggest that there are three transport mechanisms that supply food to the CWC ecosystem. First, small phytodetritus particles are transported downwards to the seafloor by advection from internal waves, supplying high quality organic matter to the CWC reef community. Second, the shoaling of deeper nutrient-rich water into the surface water layer above the coral mound could stimulate diatom growth, which form fast-sinking aggregates. Third, evidence from lipid analysis indicates that zooplankton faecal pellets also enhance supply of organic matter to the reef communities. This study is the first to report organic matter quality and composition over a tidal cycle at a coral mound and provides evidence that fresh high-quality organic matter is transported towards a coral reef during a tidal cycle.</p> <p> </p>
Hubbard Brook Experimental Forest Hydrography: GIS Shapefile
Diazo copy of Hubbard Brook Watershed Map generated stereophoto- grammetrically based on May, 1956 aerial photography. Shows New Hampshire state plane coordinate system reference points which were projected into UTM Zone 19 and used as reference tics. The streams, ponds, and lakes were manually digitized. This shapefile contains only streams, see hbef_waterbodies for lake and pond polygons. Data distributed as shapefile in Coordinate system EPSG:26919 - NAD83 / UTM zone 19N
Alaska compendium of ocean profile data [ACOD]: Archival CTD and nutrient hydrography from NOAA's EcoFOCI, EMA, and predecessor programs
Open the record for dataset details and reuse information.
NHD Hydrography and Watershed Data for the Eastern Shore of Virginia 2013
This datasets contain GIS files related to the hydrology and watersheds of Accomack and Northampton Counties on the Eastern Shore of Virginia. Data include named and unnamed water bodies, rivers and streams (both center flowlines and area polygons showing bank-full width for larger features), wetlands and marshes, and shorelines. A static (2013-09-06) copy of the full USGS "National Hydrography Dataset (NHD) - High Resolution - Virginia" state-extracted dataset in original ESRI file-geodatabase format, downloaded on 2014-02-21 from nhd.usgs.gov, is included. For users who may not be able to read or make use of data in ESRI proprietary geodatabase formats, shapefiles of geographic feature classes contained within the HUC8 subbasins spanning Accomack and Northampton Counties (partly or wholly) are also provided. Note that the stream network nodal topology, which can be used to evaluate and analyze flow paths as part of a fully-functional hydrological network with GIS tools such as Arc Hydro and Network Analyst, are only available within the ESRI file-geodatabase file. The primary purpose of this dataset is to provide VCRLTER researchers and students with a convenient up-to-date set of GIS data layers in one location that can be used as base layers for various map products and for conducting research activities. A secondary purpose of this dataset is to extend hydrologic data coverage in the VCRLTER data catalog to include Accomack County and to supersede older USGS DLG data contained in the Northampton County GIS data package (VCRLTER dataset VCR14219).
CTD Hydrography HOT v2022
<p>“The majority of our sampling effort, approximately 60-72 h per standard HOT cruise, is spent at Station ALOHA. High vertical resolution environmental data are collected with a Sea-Bird CTD having external temperature (T), conductivity (C), dissolved oxygen (DO) and fluorescence (F) sensors and an internal pressure (P) sensor. A Sea-Bird 24-place carousel and an aluminum rosette that is capable of supporting 24 12-L PVC bottles are used to obtain water samples from desired depths. The CTD and rosette are deployed on a 3-conductor cable allowing for real-time display of data and for tripping the bottles at specific depths of interest. The CTD system takes 24 samples s-1 and the raw data are stored both on the computer and, for redundancy, on VHS-format video tapes. In February 2006, before cruise 178, we replaced our 24 aging 12-L PVC rosette bottles with new 12-L bottles fabricated at the University of Hawaii Engineering Support Facility, using plans and specifications from John Bullister (PMEL).” Time is in GMT. </p> <p>https://www.soest.hawaii.edu/HOT_WOCE/intro.html</p>
Hydrography profiles from ship CTD captured during PolarFront cruise 2024-01
<p>See the Cruise Report (Daase 2024) for details.</p> <p>Daase, M. (2024). PolarFront January 2024 Cruise Report. Zenodo. <a href="https://doi.org/10.5281/zenodo.10623810" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10623810</a></p>
Hydrography from LOPC-attached CTD during PolarFront cruise 2024-01
<p>See the Cruise Report (Daase 2024) for details.</p> <p>Daase, M. (2024). PolarFront January 2024 Cruise Report. Zenodo. <a href="https://doi.org/10.5281/zenodo.10623810" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10623810</a></p>
Vertical hydrography profiles from CTD rosette downcasts during PolarFront cruise 2022-05
<p>Hydrography data from CTD (SBE911plus, Seabird Inc.) profiles. Rosette equipped with the following sensors:</p> <ul> <li>Conductivity</li> <li>Temperature</li> <li>Pressure</li> <li>Fluorometer</li> <li>Turbidity</li> <li>PAR</li> <li>Oxygen</li> </ul> <p>Update December 2024</p> <p>The salinity and temperature sensors were calibrated against another CTD from a moored instrument by Ragnheid Skogseth at UNIS, the University Centre in Svalbard. A relatively large drift in temperature was observed. To convert temperature (T) and salinity (S) to calibrated values apply the following equations to e.g. data from stnrxxxx_bin.cnv</p> <p>T_new = T_old + 0.12<br>S_new = 1.0115 * S_old – 0.5343</p> <p>The following is quoted verbatim from chapter 1 in the cruise report (Basedow, 2022):</p> <blockquote> <p>Hydrographic data were collected by a variety of sensors mounted on vertical profiling platforms, towed platforms and autonomous gliders. Combined, these platforms provided detailed information at stations, high-resolution measurements across the polar front, and longer-term measurements by the gliders. During the cruise, hydrographic measurements were taken at stations using the main rosette equipped with 12 5-L Niskin bottles, CTD-F, PAR and other sensors (Table 1.1) and using a smaller rosette frame equipped with CTD-F, LOPC, LISST and WBAT (Table 1.2, Fig. 1.1). Both platforms were deployed vertically until 5-10 m above the bottom for the main platform and down to 300 m for the platform with the LOPC, this rosette sampling three profiles at selected stations.</p> <p>In total 14 vertical profiles were sampled by the rosette with the water bottles (Table 1.1) at our 6 main stations (PF1 to PF6). Water samples for biological analyses were taken from selected depths and a bottom water samples was collected at each station for calibration of the conductivity sensor ashore. Water samples for chlorophyll a will be used to calibrate the fluorescence sensor. CTD data from this rosette were processed using the SBEDataProcessing-Win32 software. Only the values from the CTD downcast were used to avoid turbulence caused by the rosette on the upcast. The data were converted<br>to physical units, filtered for outliers and bin-averaged over 1 m bins. </p> </blockquote> <p><strong>References</strong></p> <p>Sünnje Basedow, Nicolas Gosset, Torkel Granaas, Eva Leu (2022). Hydrography. In: Malin Daase (ed.) (2022). PolarFront May 2022 Cruise Report. Zenodo. https://doi.org/10.5281/zenodo.7128746</p>
LBA-ECO LC-01 Hydrography, Morphology, Edaphology Maps, Northern Ecuadorian Amazon
This data set provides map images of hydrographic, morphologic, and edaphic features for the northern Amazon Basin in eastern Ecuador. The hydrographic data are available at two scales based on the 1:50,000 and 1:250,000-scale topographic source maps that were generated in 1990 and 1993, respectively. Morphological and edaphological data were digitized from a 1:500,000 map published in 1983. There are 3 compressed (*.zip) data files with this data set.
Leeuwin Current Dynamics in the SE Indian Ocean and Implications for Regional Surface Hydrography since the Latest Miocene: Results from ODP Hole 763A
<p>The main findings of this research are based on comprehensive analyses, including planktic foraminiferal census counts and their stable isotope ratios, as well as XRF analysis of bulk sediments from Ocean Drilling Program Hole 763A in the southeastern Indian Ocean. We have documented valuable insights into the dynamics of the Leeuwin Current and West Australian Current, as well as changes in the surface hydrography and their implications for regional climate. The study established a teleconnection between the shallowing of the mixed layer in the southeast Indian Ocean and the aridity over Northwest Australia.</p>
SASSIE Arctic Field Campaign Drifter Hydrography Data Fall 2022 Version 2p
The Salinity and Stratification at the Sea Ice Edge (SASSIE) project is a NASA experiment that aims to understand how salinity anomalies in the upper ocean generated by melting sea ice affect sea surface temperature (SST), stratification, and subsequent sea-ice growth. SASSIE involved a field campaign that sampled the transition from summer melt to autumn ice advance in the Beaufort Sea during August-October 2022, making intensive in situ and remote sensing observations within ~200 km of the sea ice edge. This dataset contains ocean temperature and salinity data collected by surface drifting buoys (called UpTempO or Hydrobuoys, interchangeably) deployed in the Beaufort Sea. Each buoy has a different configuration of sensors, and records to a maximum of 60 m depth. Drifters were left at sea after the completion of the field deployment and are recording data into March 2023. Version 2p data has major quality control performed. Data are available in netCDF format.
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