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460 results for “flux data”
Hubbard Brook Experimental Forest: Flux Tower Data, 2016-2024
Data collected from the Hubbard Brook Flux Tower starting in August 2016 that is also uploaded to the Ameriflux website under site name US-HBK. These data are from a suite of sensors installed on the 110 ft. tower and in the ground below the tower. Fast data is collected at 10Hz and is processed into 30min time steps using Licor’s Eddy Pro software. Slow data are averaged at 30 minute intervals and are included with this dataset. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Sap-flux and associated environmental data from ash tree monitoring at four urban parks in St. Paul, Minnesota, USA, from May to November of 2023.
We measured the sap flux density of eighteen ash trees (Fraxinus spp.) of varying health and canopy conditions across four urban parks in the City of St. Paul, MN, USA in summer 2023 with a low-cost, compact data logger system we designed in-house. Although many ash trees in the city have either been killed or removed to control the spread of Emerald Ash Borer, chemical insecticide treatments are available for trees that are in early stages infestation. The trees selected for the research have all been receiving insecticide treatment for a few years, but their health and canopy conditions vary. We also have collocated temperature, soil moisture, and precipitation measurements at the same site for summer 2023.
Flux Tower Data for Fowling Point Marsh at the Virginia Coast Reserve 2007-2008
This dataset contains measurements of CO2 and H2O concentrations, temperature and wind speed made every 1/10th of a second. Important note: due to the high frequency of measurements, this dataset is very large (>25 GB) and may take a long time to download. For this reason the main vcrflux_cpole.csv file is provided as well in compressed (.gz and .zip) forms which are only about 6 GB. There are two additional files. Tide_PPT_temp_2007_2008.csv contains 1-per-minute data on tide level, temperature at different heights on the tower and precipitation. Wind_light_temp_2007_2008.csv contains 1-minute summaries of wind, light, and temperature. The research was conducted at the Virginia Coastal Reserve Long Term Ecological Research (VCR LTER) site on the Eastern Shore of Virginia, USA. The flux tower site (37deg 24'39.85"N, 75deg 50'0.53"W) a lagoonal salt marsh which is located near the area of Fowling point. The site is located at about 2.2 kilometers away from the mainland and 10.7 kilometers away from Hog Island, the nearest barrier island. The flux tower is situated at about 80 meters away from the creek edge, on the lagoonal salt marsh.
Fowling Point Marsh Flux Tower Data, 2014-2017
A flux tower was operated on Fowling Point Marsh near Nassawadox, VA from 2014-2017. The flux tower is located about 2 km from the mainland and about 85 m away from a major creek edge. The marsh soil is tidally inundated on a semi-diurnal cycle, with extreme levels of inundation reaching 1.0 m above the mean marsh surface. Continuous meteorological and eddy covariance measurements were made on a 7-m flux tower located in the salt marsh. An eddy covariance unit was mounted at 3.7 m above the sediment surface. Data for BioMet sensors are provided as a table. BioMET data consists of 1min averaged meteorological data. Proprietary LiCOR .ghg files at 20Hz are included in Tape ARchive (TAR) files. Individual GHG files can be renamed as .zip files and uncompressed to reveal an internal metadata file and the data itself. A PDF file identifies the instrumentation and the wiring used to connect them. A summary file contains statistical summaries of the original GHG files.
Data and software: Stress and heat flux via automatic differentiation
<h4><strong>glp-archive</strong></h4><h2><strong>Code and Data for "Stress and heat flux with automatic differentiation"</strong></h2><p>This repository contains data, code, and related artefacts supporting the following publication (<a href="https://arxiv.org/abs/2305.01401">preprint</a>):</p><p>Stress and heat flux via automatic differentiation</p><p>by Marcel F. Langer, J. Thorben Frank, and Florian Knoop</p><p><i>J. Chem. Phys.</i> 159, 174105 (2023) <a href="https://doi.org/10.1063/5.0155760">doi:10.1063/5.0155760</a></p><p>This repository is available at <a href="https://github.com/sirmarcel/glp-archive">https://github.com/sirmarcel/glp-archive</a>. Selected versions are archived on Zenodo, under <a href="https://doi.org/10.5281/zenodo.7852529">doi:10.5281/zenodo.7852529</a>.</p><h2><strong>Overview</strong></h2><p>Each subfolder in this repository contains a README.md with additional information. The subfolders are:</p><ul><li>results/: Data and code that produced the figures in the manuscript</li><li>work/: Computational workflows, models, etc.</li><li>infra/: Project-specific infrastructure code</li><li>meta/: Scripts for assembling this archive; can be ignored but is retained for transparency.</li></ul><h2><strong>Related external code</strong></h2><p>The work in this repository relies on a few tools that the authors maintain separately:</p><ul><li><a href="https://github.com/sirmarcel/glp">glp</a> implements the quantities discussed in the manuscript</li><li><a href="http://github.com/thorben-frank/mlff">mlff</a> implements the so3krates model</li><li><a href="https://github.com/flokno/tools.mlff">tools.mlff</a> provides tools for the equation of state experiments</li></ul><p>These tools were developed during the work in the manuscript. The following versions/tags reflect what was used to obtain results:</p><ul><li>glp @ v0.1.0 (tag)</li><li>mlff @ v1.0 (branch)</li><li>mlff.tools @ v0.0.1</li></ul><p>We additionally note that the GK-MD functionality has been factored out into <a href="https://github.com/sirmarcel/gkx">gkx</a>.</p><h2><strong>Versions</strong></h2><ul><li>v1.1: published version, archived at <a href="https://doi.org/10.5281/zenodo.8406532">doi:10.5281/zenodo.8406532</a></li><li>v1.0: arXiv submission v1, archived at <a href="https://doi.org/10.5281/zenodo.7852530">doi:10.5281/zenodo.7852530</a></li></ul>
Data for Table S10 of the article "Source-to-sink aeolian fluxes from arid landscape dynamics in the Lut Desert"
<p>Exhaustive list of the 227 individual denudation rates in arid areas compiled to estimate median denudation rate and sediment discharge for the internal river system of the Lut watershed.</p>
Quality-checked horizontal particle flux data collected using a snow particle counter on board the R/V Akademik Tryoshnikov in the Southern Ocean during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Flux of particles (snow, rain and other particles including sea spray) were recorded passing through a photo-electric snow particle counter installed on board the R/V Akademik Tryoshnikov as part of the Antarctic Circumnavigation Expedition (ACE). Data were recorded from January to March 2017 in the Southern Ocean. Here we present the finalised, quality-checked, horizontal particle flux data where counts have been averaged over a one-minute period.</p> <p><strong>Dataset contents</strong></p> <ul> <li>SPC_HPF_windtrue_1min.csv, data file, comma-separated values</li> <li>SPC_HPF_windtrue_1min.png, metadata, portable network graphics</li> <li>SPC_HPF_windtrue_saveplot.py, script, Python code</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This quality-checked horizontal particle flux dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Intermediate processing stage of horizontal particle flux data collected using a snow particle counter on board the R/V Akademik Tryoshnikov in the Southern Ocean during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Flux of particles (snow, rain and other particles including sea spray) were recorded passing through a photo-electric snow particle counter installed on board the R/V Akademik Tryoshnikov as part of the Antarctic Circumnavigation Expedition (ACE). Data were recorded from January to March 2017 in the Southern Ocean. Here we present an intermediate step in data processing, with relative horizontal particle flux of particles with a size between 36 – 2000 μm averaged over one-minute periods. Data are presented in daily files.</p> <p><strong>Dataset contents</strong></p> <ul> <li>SPC_HPF_1min_YYYY_MM_DD.csv, data files, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This one-minute averaged horizontal particle flux dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux -- Supplemental Data Set: Sea Level Sensitivity Kernels
<p><strong>Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux<br> SUPPLEMENTAL DATA SET: SEA LEVEL SENSITIVITY KERNELS</strong></p> <p>To accompany</p> <p> Jerry X. Mitrovica, Carling C. Hay, Robert E. Kopp, Christopher Harig, and<br> Konstantin Laytchev (2018). Quantifying the Sensitivity of Sea Level Change<br> in Coastal Localities to the Geometry of Polar Ice Mass Flux. Journal of<br> Climate. doi: 10.1175/JCLI-D-17-0465.1.</p> <p>We provide sea level kernels for ~740 tide gauge sites in the Permanent Service for Mean Sea Level (PSMSL) database (Holgate et al., 2013). Kernels associated with sensitivities to Greenland and Alaskan glacier melt are given on a spatial grid covering the globe, with 512 latitude rows (i=1,512) and 1024 longitude (j=1,1024) columns.</p> <p>Longitude values are evenly spaced moving eastward from Greenwich (the jth grid point has an east longitude value of (j-1)×360°/1024). Latitude values are Gauss-Legendre points beginning close to the North Pole and ending near the South Pole. Kernels associated with sensitivities to Antarctic melt are given on a spatial grid covering the globe, with 256 (Gauss-Legendre) latitude rows (i=1,256) and 512 longitude (j=1,512) columns. Longitude values are evenly spaced moving eastward from Greenwich.</p> <p>The format of the files is: </p> <p> grid_sitenumber_region.txt</p> <p>where “region” is either “green” (Greenland), “ant” (Antarctic) or “Alaska” (Alaska). The list of sites (and site numbers) is provided in the sites.txt file. The first 8 sites in this list were test sites and can be ignored.</p>
Dissolved Cr concentration and stable isotope data presented in "Release from biogenic particles, benthic fluxes, and deep water circulation control Cr and δ53Cr distributions in the ocean interior" (Janssen et al., 2021, EPSL).
<p>This dataset presents all of the dissolved Cr data included and discussed in “Release from biogenic particles, benthic fluxes, and deep water circulation control Cr and δ<sup>53</sup>Cr distributions in the ocean interior” (Janssen et al., 2021, EPSL). Three primary datasets are included:</p> <ol> <li>Dissolved [Cr], [Cr(III)] and d53Cr in samples from shipboard particle regeneration incubations conducted in the subantarctic Southern Ocean.</li> <li>Dissolved [Cr] in porewater samples from a sediment core collected in the Tasman Sea in primarily calcareous sediments, along with [Cr] and δ<sup>53</sup>Cr in overlying bottom waters.</li> <li>3. A compilation of intermediate and deep water dissolved [Cr] and δ<sup>53</sup>Cr from seawater samples from the Southern, Pacific and Atlantic Oceans</li> </ol>
CO2 Flux and Temperature Data for Estimating Thermal Acclimation in Ecosystem Respiration
We have compiled an extensive dataset of long-term, hourly CO2 flux measurements from 93 global eddy covariance sites to estimate the thermal response strength in nighttime ecosystem respiration. Flux data was sourced from AmeriFlux (https://ameriflux.lbl.gov/), FluxNet (https://fluxnet.org/), and ICOS (https://www.icos-cp.eu/). The processed data product encompasses five categories. (1) Long-term, directly measured, Ustar-filtered, hourly or subhourly nighttime ecosystem respiration, along with corresponding air temperature, soil temperature, and soil water content at the 93 sites. (2) Long-term gap-filled data, including hourly or subhourly net ecosystem exchange, air temperature, and soil temperature at these sites. (3) Annual topsoil (< 0.1 m) temperature and nighttime ecosystem respiration curves during the growing season, designed for calculating thermal response strength. (4) Estimated thermal response strength across these sites, detailed with geographic, climatic, soil, and vegetation conditions for each site. (5) An R script to calculate thermal response strength using the data product (3).
Climate data from the former Arctic LTER Toolik Inlet Wet Sedge Flux site, Toolik Field Station, Alaska 2017 to 2025.
One-minute averages of air temperature and relative humidity, soil temperature and moisture, and solar radiation from 2017 to 2025 for the former Arctic LTER Toolik wet sedge eddy covariance flux site. This site was originally set up for seasonal eddy covariance flux measurements during the summers of 2010–2015 and partially during winters starting in 2014, until 15 June 2016. Flux data are reported in Eugster et al.(2020)(doi:10.5194/amt-2019-402). IMPORTANT NOTE: The data has only been checked for obvious outliers. Use with caution since most of the data has not been carefully checked. It was decided to release this version instead of waiting until there were resources for a complete check.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Half-hourly growing season, chamber-based, CO2 flux data, 2009-2021
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data contains CO2 fluxes measured using an automated chamber system that measures net ecosystem CO2 exchange (NEE). Measurements are made every ~1.5 hours and modeled half-hourly. Half hour ecosystem respiration is modeled using an exponential Q10 relationship when light conditions are low (PAR<5umol/m2/s) and using a hyperbolic light relationship when PAR>5umol/m2/s. GPP is calculated as the difference between NEE and Reco.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Growing season, chamber-based, CO2 flux data, 2009-2021
This drying and warming experiment addresses the following questions: 1) Does ecosystem drying, warming and permafrost thaw cause a net release or uptake of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss? 3) How do drying and warming affect plant communities and ecosystem properties? We are answering these questions using a combined warming and drying experiment (DryPEHR), which is situated with the Carbon in Permafrost Experimental Heating Research (CiPEHR) project and located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. Warming treatment here refers to growing season air temperature warming (~1C) using open top chambers (OTC) combined with soil 'warming' using snow fences during the snow covered months. Drying is achieved using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. This data set includes measured values of CO2 fluxes during the growing season.
APEX beta greenhouse gas flux data from both the permafrost plateau area and the active thaw margin, from 2017 on
This dataset contains greenhouse gas flux data for the bog and permafrost plateau sites at the Alaskan Peatland Experiment (APEX) from 2017 on. Includes some environmentals, raw gas concentrations, and derived gas flux rates.
Long-term Atmospheric, Soil and Water Sensor Data from the GCE-LTER Eddy Covariance Flux Tower on Sapelo Island, Georgia
Long-term measurements of various atmospheric, soil and water properties were made using electronic sensors attached to the GCE-LTER eddy covariance flux tower deployed in a Spartina alterniflora salt marsh on Sapelo Island, Georgia. Variables measured include air and water temperature, relative humidity, precipitation, wind speed and direction, soil temperature, water pressure and solar radiation components (i.e. incident and reflected photosynthetically available, total, long-wave and shortwave radiation). Measurements were logged at 5 minute intervals using multiple Campbell Scientific Instruments CR3000 data loggers, and then combined into a single monotonic time series data set. Quality control analyses were performed to remove values deemed invalid due to sensor failure or miscalibration and to assign Q/C qualifiers to values outside expected ranges or failing various sanity and quality checks of the data. Note that some measurements were spatially replicated with multiple sensors deployed in different micro-habitats (e.g. at the tower and in a nearby marsh platform or creek). Sensors were also added to the tower at various times after the initial installation, therefore some variables do not span the entire period of record. Measurements at this site are ongoing, and the data set will be updated annually to include additional observations.
Long-term Meteorological Data from the GCE-LTER Eddy Covariance Flux Tower on Sapelo Island, Georgia
Long-term measurements of key meteorological variables were made using electronic sensors attached to the GCE-LTER eddy covariance flux tower deployed in a Spartina alterniflora salt marsh on Sapelo Island, Georgia. Variables measured include air temperature, relative humidity, precipitation, wind speed, wind direction, photosynthetically-available and total solar radiation. Measurements were logged at 5 minute intervals using a Campbell Scientific Instruments CR3000 data logger then re-scaled to 15 minute and daily interval data sets. Quality control analyses were performed to remove values deemed invalid due to sensor failure or miscalibration, and to assign Q/C qualifiers to values outside expected ranges or failing various sanity and quality checks of the data. Measurements began in 2013; however, the total solar pyranometer was not installed until 2018 and minimum and maximum 5 minute air temperature were not added until 2019 so not all variables span the complete period of record. Measurements are continuing at this site and this data set will be updated annually to include additional observations.
Soil nitrous oxide and carbon dioxide flux data for Niwot Ridge and Loch Vale watershed, 1994.
Fluxes of carbon dioxide and nitrous oxide from snow-covered alpine soils were measured at Niwot Ridge. Six sites characterized by relatively shallow snowpacks were sampled in 1993. A total of 27 sites were sampled in 1994. Nine of the 1994 sites were located in the naturally shallow snowfield sampled in 1993, 9 sites were located in a formerly shallow snowpack site where snow depth was augmented by the construction of a 2.8-m high, 60-m long snowfence, and the 9 remaining sites were located in a naturally deep snowpack. Concentrations of N2O and CO2 at the soil surface were measured monthly from January until March, biweekly through April, and weekly until snowmelt was complete. Elevated levels of CO2 under the snowpack, suggesting microbial activity, were first observed under the shallow snowpacks in early March of 1993. N2O production under snow was first observed in April 1993, when soil temperatures had warmed above -3 degrees C. In 1994 shallow snowpack sites exhibited diminished and sporadic production of both CO2 and N2O, apparently due to the inconsistent snow cover compared to 1993. The snowfence sites exhibited increased CO2 and N2O fluxes beginning in February 1994. Both CO2 and N2O fluxes from the snowfence site were similar to those measured under the naturally deep snowpack. These data suggest that the timing and depth of snow cover during the alpine winter control microbial activity by insulating soils from extreme air temperatures. To obtain a regional perspective on subnivean trace gas fluxes, both CO2 and N2O samples were determined at sites below treeline on Niwot Ridge and at Loch Vale in Rocky Mountain National Park.
Biome Transition Along Elevational Gradients in New Mexico (SEON) Study: Flux Tower Seasonal Biomass and Seasonal and Annual NPP Data at the Sevilleta National Wildlife Refuge, New Mexico
The varied topography and large elevation gradients that characterize the arid and semi-arid Southwest create a wide range of climatic conditions - and associated biomes - within relatively short distances. This creates an ideal experimental system in which to study the effects of climate on ecosystems. Such studies are critical given that the Southwestern U.S. has already experienced changes in climate that have altered precipitation patterns (Mote et al. 2005), and stands to experience dramatic climate change in the coming decades (Seager et al. 2007; Ting et al. 2007). Climate models currently predict an imminent transition to a warmer, more arid climate in the Southwest (Seager et al. 2007; Ting et al. 2007). Thus, high elevation ecosystems, which currently experience relatively cool and mesic climates, will likely resemble their lower elevation counterparts, which experience a hotter and drier climate. In order to predict regional changes in carbon storage, hydrologic partitioning and water resources in response to these potential shifts, it is critical to understand how both temperature and soil moisture affect processes such as evapotranspiration (ET), total carbon uptake through gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange of carbon, water and energy across elevational gradients. We are using a sequence of six widespread biomes along an elevational gradient in New Mexico -- ranging from hot, arid ecosystems at low elevations to cool, mesic ecosystems at high elevation to test specific hypotheses related to how climatic controls over ecosystem processes change across this gradient. We have an eddy covariance tower and associated meteorological instruments in each biome which we are using to directly measure the exchange of carbon, water and energy between the ecosystem and the atmosphere. This gradient offers us a unique opportunity to test the interactive effects of temperature and soil moisture on ecosystem proces
TWINS ENA flux and ion temperature data for interval on August 3, 2016
<p>This is a dataset for TWINS ENA flux and calculated ion temperatures used to prepare Figure 1 for a submission to GRL of a paper by A. M. Keesee, N. Buzulukova, C. Mouikis and E. E. Scime "Mesoscale structures in Earth's magnetotail observed using energetic neutral atom imaging". The dataset has 56 files in .csv format.</p> <p>Files containing the ion temperature (in keV) arrays in the GSM equatorial plane used for Fig. 1a-d have names with format 'temp_YYYYMMDDHHMM.csv'</p> <p>Also included in the dataset are the ENA fluxes projected to the GSM equatorial plane that were used to calculate the ion temperatures. These files have names with formal 'flux[energy]_YYYMMDDHHMM.csv' where [energy] is in keV. The IDL scripts used to create the projections as well as the fitting algorithms used to calculate the ion temperatures are included in Keesee, Amy; Scime, Earl; Zaniewski, Anna; and Katus, Roxanne (2019). 2D Ion Temperature Maps from TWINS ENA data: IDL scripts. UNH Scholars’ Repository <a href="https://dx.doi.org/10.34051/c/2019.1">https://dx.doi.org/10.34051/c/2019.1</a></p>
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International Brain Laboratory public data
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OpenNeuro
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