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51 results for “arctic rivers”
Invertebrate Community Asemblage from the Arctic LTER Upper Kuparuk River Reference (2001-2012) and Fertilized Reach (2002-2016), Toolik Field Station, Alaska
Surber sampler (25 X 25 cm frame fitted with a 243 um mesh net) was used to sample invertebrates at on the Kuparuk River in Reference (2001-2012) and Fertilized Reach (2002-2016) reach.
RADIT: A Machine Learning-Reconstructed Dataset of River Discharge, Temperature, and Heat Flux into the Arctic Ocean
<p>The Reconstructed Arctic-draining river DIscharge and Temperature (RADIT) dataset provides daily records of river discharge, temperature, and heat flux for 25 major Arctic-draining rivers from 1950 to 2023. Using machine learning methods and ERA5-Land reanalysis data, we reconstructed these key hydrological variables with high accuracy (most NSEs > 0.8).</p> <p>Due to licensing restrictions and to encourage adherence to the stated licenses of the original input data, this dataset only provides the reconstructed (filled) values. Users can obtain the complete historical observational data from their original publicly available sources as detailed in our documentation. By combining these original observations with our reconstructed data, a comprehensive and continuous daily dataset from 1950 to 2023 can be assembled. Clear instructions and links for downloading the original observational data used in this study can be found at: <a href="https://github.com/zhwang24/RADIT-Reconstructed-Arctic-River-Data" target="_blank" rel="noopener">https://github.com/zhwang24/RADIT-Reconstructed-Arctic-River-Data</a>. Should you encounter any issues or have questions, please feel free to contact the first author, Zihan Wang (zhwang2018@163.com).</p>
Kuparuk River Whole Stream Metabolism Arctic LTER, Toolik Field Station Alaska 2012-2017
The Kuparuk River has been the central research location on the impact of added phosphorus to arctic streams. Additions of phosphorus occred since 1983. Today, 4 specific reaches show certain characteristics based on the years that they recieved fertilization. Whole Stream Metabolism is a way to quantify primary production of this stream system. Calculations were done using dissolved oxygen, discharge, stage, light and temperature measured by sondes and other equipment strategically deployed in the field at locations to quantify each of the unique stream reaches.
Kuparuk River stream temperature and discharge measured each summer, Dalton Road crossing, Arctic LTER Toolik Field Staion, Alaska 1978-2019
Stream temperature and discharge measured each summer for several streams in the Toolik area. In many years, temperature and stream height were recorded manually each day. In recent years, dataloggers have measured stream temperature and stream height at regular intervals. The Kuparuk River data was maintained by Doug Kane and the Water and Environmental Research Center at UAF through 2017 (http://ine.uaf.edu/werc/projects/NorthSlope/upper_kuparuk/upper_kuparuk....). Stream height is converted into stream discharge based on a rating curve calculated from manual discharge measurements throughout the season. The principal investigator in charge of the temperature and discharge measurements is Dr. Breck Bowden. Note: This file replaces older yearly files of discharge and temperatures
Concentration of dissolved inorganic carbon (DIC) and del 13C isotope value for lakes and rivers on North Slope from Brooks Range to Prudhoe Bay, Arctic LTER 1988 to 1989.
Concentration of dissolved inorganic carbon (DIC) and del 13C isotope value for lakes and rivers on North Slope from Brooks Range to Prudhoe Bay, Arctic LTER 1988 to 1989.
Supporting model output for article "Assessing the potential impact of river chemistry on Arctic coastal production"
<p>The following is a summary of processed model output data from a series of HiLAT model runs.<br> A description of the model runs and visualization of model output and analysis can be found in the<br> accompanying manuscript.</p> <p><br> Gibson G. A., Elliott, S., Piliouras, A. Clement Kinney, J., Jeffery, N. (2022) Assessing the potential<br> impact of river nitrate on coastal production in the Arctic. Frontiers in Marine Science: Coastal Ocean<br> Processes.</p> <p><br> This work was supported by the Regional and Global Model Analysis (RGMA) program of the US<br> Department of Energy’s Office of Science as a contribution to the HiLAT project. Additional support for<br> this project was provided by the National Science Foundation, under award #173886.<br> </p> <p><strong>River Nutrient Forcing</strong></p> <p>The experiments involved modifying the nutrient concentrations in the river nutrient forcing files.<br> The river nutrient files are specified during model setup. For use in the HiLAT model, GNEWS annual<br> river nutrient inputs were partitioned into twelve monthly forcing values. The nearest ocean grid point<br> to each of the GNEWS river mouth locations was identified and then, as with the runoff, the nutrient<br> inputs for each river basin were spatially mapped to surface ocean model grid cells, which are 10 meters<br> thick, such that the spatial pattern of river nutrient dispersion follows river water inputs to the oceans.</p> <p>The experiments were:<br> i) The baseline model simulation: The 12 monthly values for each grid cell were constant in time.<br> <strong>river_nutrients_GNEWS2000_gx1v6.nc</strong><br> ii) an experiment in which baseline Arctic River Nitrogen (NO 3 and NH 4 ) concentrations were doubled.<br> <strong>river_nutrients_GNEWS2000_gx1v6_x2Arctic.nc</strong><br> iii) an experiment in which baseline Arctic River Nitrogen (DON and DIN) concentrations were scaled to<br> the river volume discharge contained in <strong>runoff.daitren.iaf.20120419.nc</strong><br> <strong>river_nutrients_GNEWS2000_gx1v6_scaled_climatology.nc</strong><br> iv) an experiment in which the scaled river nutrient discharge (iii) was shifted earlier by two months.<br> <strong>river_nutrients_GNEWS2000_gx1v6_shifted2m_climatology.nc</strong><br> v) an experiment in which the scaled river nutrient discharge (iii) was shifted earlier by a month and<br> doubled in concentration.<br> <strong>river_nutrients_GNEWS2000_gx1v6_shifted_climatology_x2.nc</strong></p> <p>River nutrient fluxes are in units of nmol/cm2/s<br> Only concentrations within the domain TLONG>=60 &TLONG <=340 & TLAT >=60 were modified in<br> concentration/timing.</p> <p><br> Variables of interest:<br> din_riv_flux: dissolved inorganic nitrogen river flux<br> don_riv_flux: dissolved organic nitrogen river flux</p> <p>Each of the experiments is described in detail in Gibson et al (2022).</p> <p>---------------------------------------------<br> There are multiple versions of most output file types, corresponding to the river nutrient experiments that<br> were conducted.</p> <p><br> Many variables in the output files are <strong>regional averages</strong> where model regions are indicated by a number<br> *note - for aesthetics, the numbering used in the model output files differs slightly from the numbering<br> used in the accompanying manuscript. The numbers assigned in the analysis files aligns with the numbers<br> assigned to regions within the region mask provided in the grid file.</p> <p><strong>Grid File/region masks</strong><br> gx1v6_polar_mask_coast.5.22.20c.nc This file is an updated version of the standard grid file. It has been<br> updated to include the addition of a coastal Arctic region variable ‘Arctic_Coast_Mask’ which indicates<br> which grid cells are in the coastal regions used in the analysis and the Arctic_Region variable which<br> indicates which grid cells are in the broader regions.</p> <p><br> Variables contained in this file are:<br> Arctic_Coast_Mask: contains values 0-9 indicating which (if any) coastal region a grid cell is in<br> Arctic_Region Mask: contains values 0-11 indicating which (if any) region a grid cell is in</p> <p><br> TLAT: latitude of grid cell<br> TLONG: longitude of grid cell<br> TAREA: Area of grid cell<br> HT: Bathymetry of grid cell</p> <p> </p><table> <tbody> <tr> <td> </td> <td> <p><strong>Arctic_Region (seas)</strong></p> </td> <td> <p><strong>Arctic_Coast_Mask </strong><strong>(coast)</strong></p> </td> </tr> <tr> <td> <p><strong>Bering Sea</strong></p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p><strong>Chukchi Sea</strong></p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p><strong>East Siberian Sea</strong></p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p><strong>Laptev Sea</strong></p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p><strong>Beaufort Sea</strong></p> </td> <td> <p>5</p> </td> <td> <p>5</p> </td> </tr> <tr> <td> <p><strong>Barents Sea</strong></p> </td> <td> <p>6</p> </td> <td> <p>6</p> </td> </tr> <tr> <td> <p><strong>Canadian Basin</strong></p> </td> <td> <p>7</p> </td> <td> <p>-</p> </td> </tr> <tr> <td> <p><strong>Eurasian Basin</strong></p> </td> <td> <p>8</p> </td> <td> <p>-</p> </td> </tr> <tr> <td> <p><strong>Nordic Seas</strong></p> </td> <td> <p>9</p> </td> <td> <p>7</p> </td> </tr> <tr> <td> <p><strong>Labrador Sea</strong></p> </td> <td> <p>10</p> </td> <td> <p>8</p> </td> </tr> <tr> <td> <p><strong>Kara Sea</strong></p> </td> <td> <p>11</p> </td> <td> <p>9</p> </td> </tr> </tbody> </table> --------------<p></p> <p> </p><p>Model outputs that were analyzed in the manuscript are contained in three different kinds of output file.<br> For each file type a file exists for each river nutrient experiment.</p> <p></p> <p>The following series of files contains variables related to the particulate organic carbon flux to the<br> sediment, demineralization and remineralization rates.<br> bgc_T62_gx1GIF_nut-riv-BASELINE-coast_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-month-shiftx2-coast_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2xArcticN-coast_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-mon-clim-coast_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2mon-shift-coast_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv_2XDC-coast_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-BASELINE-seas_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-month-shiftx2-seas_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2xArcticN-seas_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-mon-clim-seas_region-sed-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2mon-shift-seas_region-sed-137-157.nc</p> <p><br> Variables contained in these are:<br> POCTOSED_AVG* : Particulate organic carbon flux to sediment<br> PONTOSED_AVG* : Particulate organic nitrogen flux to sediment<br> SEDDENITRIF_AVG* : Sediment denitrification rate<br> POC_PROD_AVG* : Production of Particulate organic carbon<br> POC_FLUX_AVG* : Particulate organic carbon flux into layer/cell<br> DON_REMIN_AVG* : Dissolved Organic Nitrogen remineralization rate<br> DOC_REMIN_AVG* : Dissolved Organic Carbon remineralization rate<br> DIAT_N_LIM_AVG* : Diatom nitrogen limitation<br> DIAT_N_LIM_AVG* : Diatom nitrogen limitation<br> DIAT_P_LIM_AVG* : Diatom phosphorous limitation<br> DIAT_FE_LIM_AVG* : Diatom iron limitation<br> DIAT_LIGHT_LIM_AVG*: Diatom light limitation<br> SP_N_LIM_AVG* : Small phytoplankton nitrogen limitation<br> SP_P_LIM_AVG* : Small phytoplankton phosphorous limitation<br> SP_FE_LIM_AVG* : Small phytoplankton iron limitation<br> SP_LIGHT_LIM_AVG* : Small phytoplankton light limitation<br> Where * represents the coastal region number.<br> ----------------------------------------</p> <p><br> The following series of files contains primary production for the small and large phytoplankton groups<br> and the zooplankton biomass.</p> <p>Coastal regional averages – based on regions marked in the Arctic_Coast_Mask variable<br> bgc_T62_gx1GIF_runoff-2xArcticN-region-prod-ACM-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-mon-clim-region-prod-ACM-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-month-shiftx2-region-prod-ACM-137-157.nc<br> bgc_T62_gx1GIF_riv-BASELINE-region-prod-ACM-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2mon-shift-region-prod-ACM-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2XDC-region-prod-ACM-137-157.nc</p> <p>Regional seas averages – based on regions marked in the Arctic_Region variable<br> bgc_T62_gx1GIF_runoff-2xArcticN-region-prod-seas-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-mon-clim-region-prod-seas-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-month-shiftx2-region-prod-seas-137-157.nc<br> bgc_T62_gx1GIF_riv-BASELINE-region-prod-seas-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2mon-shift-region-prod-seas-137-157.nc</p> <p>Variables contained in these files are:<br> TAREA_SUM* – total area of the region<br> PPSP_REGSUM* – sum of primary production by small phytoplankton in a region<br> PPDIAT_REGSUM*– sum of primary production by diatoms in a region<br> ZOOC_AVG*– sum of zooplankton biomass in a region</p> <p>----------------------------------------<br> The following series of files contains ice associated variables and mixed layer nutrients</p> <p>bgc_T62_gx1GIF_nut_riv-2xArcticN-ice_coastal-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-mon-clim-ice_coastal -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-month-shiftx2-ice_coastal -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-BASELINE-ice_coastal -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2mon-shift-ice_coastal -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2XDC-ice_coastal -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2xArcticN-ice_seas-137-157.nc<br> bgc_T62_gx1GIF_nut-riv-mon-clim-ice_seas -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-month-shiftx2-ice_seas -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-BASELINE-ice_seas -137-157.nc<br> bgc_T62_gx1GIF_nut-riv-2mon-shift-ice_seas-137-157.nc</p> <p>HI_REGAVG* : Regional averaged ice depth<br> HS_REGAVG* : Regional averaged snow depth<br> ICEAREA_REGSUM* : Regional sum ice area<br> ICEVOL_REGSUM*: Regional sum volume area<br> MLAM_REGAVG* : Regional average ammonium concentration in mixed layer<br> MLNIT_REGAVG* : Regional average nitrate concentration in mixed layer<br> PP_REGAVG* : Regional average primary production (ice algae)<br> PP_REGSUM* : Regional total primary production (ice algae)<br> TAREA_SUM* : Total area of region<br> TIME : time</p>
Supplemental tables for a study of the seasonal Impacts of the Physical Environment on Biogeochemical Cycles in Arctic Lakes of the Mackenzie River Delta
<p>submitted abstract</p> <p>We conducted two- and six-year-long deployments of continuous water samplers (OsmoSamplers) and sensors (Temperature, pressure, light level, dissolved oxygen (DO) and conductivity) in nine lakes within the mid- to outer-delta region of the Mackenzie River and documented biogeochemical fluctuations (Mn, Fe, sulfate, and DO), defined physical processes that that drive such fluctuations, and constrained the impact of lake solutes on annual riverine fluxes. Five lakes were in the mid-delta region near Inuvik, NT, two lakes were in the outer delta, and two lakes were on the Arctic coastal plain and were not impacted by the Mackenzie River. In general, temperature minima occurred in September/October, indicative of ice formation, and distinct hydrostatic pressure (water level) anomalies occurred in May/June associated with ice breakup, lasting for days to months and impacting lake levels up to 4.2 m higher than “normal”. Such anomalies coincide with a dramatic change in solute concentrations. Systematic changes in solute concentrations indicate redox-driven biogeochemical reactions, salt exclusion during ice formation, and continuous to sporadic exchange of river water. Redox reactions were regulated by DO inputs stemming from atmospheric, photosynthetic, and riverine sources. During ice-covered periods dissolved sulfate may be conservative but was generally removed. Manganese and iron concentrations showed phases of production and removal during ice-covered periods, but both were produced overall. Calculated solute fluxes from lake waters alone to the Arctic Ocean may only impact yearly riverine fluxes for solutes that exceed ten times the river concentration prior to ice breakup (e.g., Mn and Fe).</p>
Arctic Grayling Growth in the Kuparuk River; data from 1986-2003
Adult Arctic Grayling were caught and tagged in the Kuparuk River. A second fishing campaign occurred later in the summer, and any fish that was recaptured was remeasured to determine growth. Phosphorus addition has occurred since 1983; station sites are relative distance from the original 1983 phosphorus dripper. Stations include sites in a reference, recovery, and fertilized reach. Reaches were defined based on the location of phosphorous addition (see methods). Arctic Grayling were caught early in the field season, tagged, and recaptured late in the field season. During each capture, the grayling were measured for length and weight. With fish that were recaptured, growth of each grayling during specific seasons was calculated. Data is for 1986 to 2003.
Total numbers per square meter and taxa of insects taken from the Kuparuk River during the summer of 2001, Arctic LTER 2001.
A Surber sampler (25 X 25 cm frame fitted with a 243 um mesh net) was used to sample invertebrates at several different stations. Two replicates were taken from each station. The same sampling procedure was used for all dates. The stations were measured relative to the site of the dripper ("-" = upstream of the dripper). Samples were preserved in 4% formaldehyde and transported to Orono, Maine, where invertebrates were removed by hand under 15X magnification and then identified and counted. All values are converted to individuals per square meter.
Arctic Rivers Dissolved Organic Carbon River Export Analysis
<p>This repository has data for the estimation of dissolved organic carbon and colored dissolved organic carbon in the 6 Great Arctic Rivers. The data has been derived from the arcticgreatrivers.org repository for use in the USGS LOADEST model https://water.usgs.gov/software/loadest/ to predict river mass load as a function of measured discharge. The *_discharge.dat files contain the river discharge data from arcticgreatrivers.org and each *.tar directory with the river's name contain the output file from the LOADEST model with 100 model runs each for each parameter defined below. The netcdf file ArcticRivers_CarbonTrends.nc contains all of the LOADEST model prediction ensembles and mean/total seasonal values used in the trend analysis.</p> <p>DOC=Dissolved organic carbon (mg/L)</p> <p>CDOC=Colored dissolved organic carbon (mg/L)</p> <p>S1=CDOM absorption spectral slope between 275-295 nm (1/nm)</p> <p>S2=CDOM absorption spectral slope between 350-400 nm (1/nm)</p> <p>a300 = CDOM absorption at 300 nm (1/m)</p> <p>There is also a file River_CDOM_PUB.mat that is a MATLAB data structure with the data used to construct the LOADEST model input files.</p> <p>Dr. J. Blake Clark should be contacted at bclark@umbc.edu with any specific questions.</p>
Data published in manuscript "Effects of reversal of water flow in an Arctic floodplain river on fluvial emissions of CO2 and CH4" by Castro-Morales et al.
<p>This data is published in the manuscript<strong>:</strong></p> <p>Castro-Morales, K., Canning, A., Körtzinger, A., Göckede, M., Küsel, K., et al. (2022). Effects of reversal of water flow in an Arctic floodplain river on fluvial emissions of CO<sub>2</sub> and CH<sub>4</sub>. <em>Journal of Geophysical Research: Biogeosciences</em>, 127, e2021JG006485. <a href="https://doi.org/10.1029/2021JG006485">https://doi.org/10.1029/2021JG006485</a>.</p> <p>The data contains the water properties and gases data measured at a site in Ambolikha River, meteorological data measured at an eddy covariance tower located in the neighbor floodplain, and data from the analysis of dissolved organic matter in river water samples. The data was collected between 26 June, 2019 and 02 August, 2019.<strong> </strong></p> <p>This folder contains four data files and the file "README_Data_access_Castro-Morales_etal_Ambolikha_River.txt" should be read before accessing the data. The authors recommend downloading Version 2.0 because it is the most up to date data.</p> <p>For questions contact the main and corresponding author Dr. Karel Castro-Morales at: karel.castro.morales@uni-jena.de</p>
Data published in manuscript "Highest methane concentrations in an Arctic River linked to local terrestrial inputs"
<p>This data is published in the manuscript:</p> <p>Castro-Morales, K., Canning, A., Arzberger, S., Overholt, W.A., Küsel, K., Kolle, O., Göckede, M., Zimov, N. and Körtzinger, A. (2022). Highest methane concentrations in an Arctic River linked to local terrestrial inputs. <em>Biogeosciences.</em> XX, XXX-XXX. https://doi.org/10.5194/bg-XX-XXX-2022.</p> <p>The data contains the water properties, the dissolved gas concentrations and flux densities at 1-min resolution corresponding to two transects in the Kolyma River main channel and two tributaries (Ambolikha and Leonid). The data was collected between 15 and 17 June, 2019.<strong> </strong></p> <p>This folder contains four data files and the file "README_Data_access_Castro-Morales_etal_CH4_Kolyma_River.txt" provides more details on the data.</p> <p> </p> <p> </p>
Arctic 2006: Relative percent cover was measured for plant species on Arctic LTER experimental plots in moist acidic, dry heath and moist non-acidic tundra, and for Sagavanirktok River plots in tussock and heath tundra.
Relative percent cover was measured for plant species on Arctic LTER experimental plots at Toolik field station in moist acidic and moist non acidic tussock tundra, and dry heath tundra, and on Sagavanirktok River toposequence plots in tussock and heath tundra.
Relative percent cover was measured for plant species on Arctic LTER experimental plots in moist acidic, dry heath and moist non-acidic tundra, and for Sagavanirktok River plots in tussock and heath tundra, North Slope Alaska 2004.
Relative percent cover was measured for plant species on Arctic LTER experimental plots at Toolik field station in moist acidic and moist non acidic tussock tundra, and dry heath tundra, and on Sagavanirktok River toposequence plots in tussock and heath tundra.
Biomass from six vegetation types along a toposequence on a floodplain terrace of the Sagavanirktok River, Alaswka,1988, Arctic LTER.
Biomass was harvested from six vegetation types along a toposequence on a floodplain terrace of the Sagavanirktok River in the northern foothills of the Brooks Range , Alaska (68degrees 46' N, 148 degrees 51' W 50m). The vegetation sites are; upland tussock tundra, "hilltop heath", a "hillslope shrub-lupine", a "footslope Equisetum", a wet sedge tundra, and a "riverside willow".
Nitrogen mineralization was determined on Arctic LTERToolik and Sag River tussock tundra using the buried bag method, Toolik Field Station, Alaska, Arctic LTER 1989-2013.
Nitrogen mineralization was determined on LTER and Sag River tussock tundra using the buried bag method. Yearly bags have been deployed every August since 1990.
Plant available NH4, NO3, and PO4 was determined at sites near ARC LTER Toolik acidic tundra and at a toposequence along the floodplain of the Sagavanirktuk River using 2 N KCL and weak HCL extracts, Arctic LTER 1987 to 2002
Plant available NH4, NO3, and PO4 was determined at sites near ARC LTER Toolik acidic tundra and at a toposequence along the floodplain of the Sagavanirktuk River using 2 N KCL and weak HCL extracts. This file complies data collected at different times from 1987 through 2001 and includes initial extracts taken for buried bag method of net nitrogen mineralization.
Concentration of dissolved inorganic carbon (DIC), carbon and nitrogen concentrations, C:N ratios and del 13C isotope value for lakes and rivers on North Slope from Brooks Range to Prudhoe Bay, Arctic LTER 1988 to 2005
Composite file describing plant, animal, water, and sediment samples collected at various sites near Toolik Research Station (68 38'N, 149 36'W). Sample site descriptors include an assigned number specific to the file, a number that relates the samples to other samples collected on the same date and time (sortchem), site, date, time, and depth. Samples are identified by type, category, and a short description. Data include isotope values, carbon and nitrogen concentrations, and C:N ratios of samples.
Arctic Ocean freshwater dynamics: transient response to increasing river runoff and precipitation [dataset]
<p>This dataset contains the underlying data for the manuscript Brown et al., Arctic Ocean freshwater dynamics: transient response to increasing river runoff and precipitation, submitted to JGR-Oceans</p> <p>-----------------------------------<br> Descriptors in the filenames, shown below as *, correspond to the various simulations, as follows:</p> <p>Simulations forced with JRA-25 reanalysis data:<br> AR: Unperturbed control simulation<br> B1: Simulation involving a step change in river runoff of -30% <br> C1: Simulation involving a step change in river runoff of +30% <br> B7: Simulation involving a step change in precipitation of -30% <br> C8: Simulation involving a step change in precipitation of +30% </p> <p>Simulations forced with the CORE-II climatology:<br> AR_CORE: Unperturbed control simulation <br> P-30_CORE: Simulation involving a step change in precipitation of -30% <br> P+30_CORE: Simulation involving a step change in precipitation of +30% </p> <p>-----------------------------------<br> The files named as fwvolume_Sref35_*.nc contain the variables:</p> <p>freshwater: horizontally-integrated liquid freshwater volume in m^3<br> freshwater_pos: as before, but including only positive values in the integration<br> h_f: basin-mean freshwater height in m<br> h_f_pos: as before, but including only positive values in the integration</p> <p>The reference salinity used in each case is 35.</p> <p>-----------------------------------</p> <p>The files named as freshwater_h_f_*.nc contain horizontally-gridded, depth-integrated liquid freshwater heights in m. The integration is made to a depth of 276.68m.</p> <p>h_f_34p8: freshwater height, using a reference salinity of 34.8 <br> h_f_34p8_pos: as before, but including only positive values in the integration<br> h_f_35: freshwater height, using a reference salinity of 35 <br> h_f_35_pos: as before, but including only positive values in the integration</p> <p>The grid for these files is grid.nc</p> <p>-----------------------------------</p> <p>The files named as fluxes_ed3_*.nc contain strait-integrated volume fluxes (in m^3 s^-1) into and out of the Arctic domain: </p> <p>f: liquid volume flux<br> fw: freshwater, with variables numbered 1 using a reference salinity of 34.8 and those numbered 2 using a reference salinity of 35<br> ice: sea ice volume flux</p> <p>The first dimension, ngate, of the variables indicates the strait:</p> <p>1) Fram Strait<br> 2) Barents Sea Opening<br> 3) Bering Strait<br> 4) Amundsen Gulf<br> 5) McClure Strait<br> 6) Canadian Arctic Archipelago<br> 7) Nares Strait</p> <p>-----------------------------------</p> <p>Sea ice volumes (in m^3) for the JRA-25 forced simulations are contained in the files named area_int_*.nc with variable name "ivol"</p> <p>-----------------------------------</p> <p>Basin-integrated liquid freshwater volumes for a further series of JRA-forced runoff perturbation experiments are contained within the file FWLvol_AO_Sref35_runoff.mat:</p> <p>R_10: a step increase in runoff of 10%<br> R_60: a step increase in runoff of 60%<br> R_100: a step increase in runoff of 100%</p> <p>The reference salinity is 35 and depth of integration 276.68m</p>
Tracing the imprint of river runoff on Arctic water mass transformation [dataset]
<p>This dataset contains the underlying data for the manuscript Lambert et al., Tracing the imprint of river runoff<br> variability on Arctic water mass transformation, submitted to JGR-Oceans</p> <p>-----------------------------------<br> Both files contain variables with the general notation:<br> S..., which are the cumulative salt fluxes;<br> S..2, which are the salinity-transformation fluxes;<br> T..., which are the cumulative heat fluxes; and<br> T..2, which are the temperature-transformation fluxes.</p> <p>-----------------------------------<br> In the file crfdata.nc, the variable names contain:<br> slrx: surface salinity restoring term<br> emp: evaporation-precipitation, small en neglected in the manuscript<br> rnf: river runoff<br> ice: ice melt<br> brnx: brine rejection including the penetration into subsurface layers<br> qns: nonsolar surface heat flux<br> qswx: heat flux due to shortwave radiation including the penetration into subsurface layers<br> fsiso/ftiso: isopycnal diffusion of salt/heat<br> fsdia/ftdia: diapycnal diffusion of salt/heat<br> sec: advection across the collective Arctic gateways</p> <p>Each variable is of size [4,12,nS] or [4,12,nT] where nS is the number of salinity bins, equal to the length of variable S<br> and nT is the number of temperature bins, equal to the length of variable T</p> <p>The first dimension is ordered as follows:<br> 0: delta_s, the equilibrium response to a 30% increase in total Arctic river runoff<br> 1: tau_s, the e-folding time scale of this response in months<br> 2: std, the standard deviation of the control value<br> 3: ctrl, the average control value</p> <p>The second dimension indicates the calendar month</p> <p>-----------------------------------------<br> In the file pp2.nc, the variable names contain:<br> slrx: surface salinity restoring term<br> rnf: river runoff<br> ice: ice melt<br> brnx: brine rejection including the penetration into subsurface layers<br> qns: nonsolar surface heat flux<br> qswx: heat flux due to shortwave radiation including the penetration into subsurface layers<br> adv: advection across the collective Arctic gateways<br> dif: total isopycnal + diapyncal diffusion</p> <p>Each variable is of size [2,nS] or [2,nT]</p> <p>The first dimension is:<br> 0: explained model variance between 0 and 1<br> 1: explained model variance where correlations with p>.05 equal NaN</p>
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