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94 results for “eddy covariance”
Coral Reef Eddy Covariance Data
<p>Eddy covariance data collected over the reef flat on Heron Island during February 2010</p>
An Excel spreadsheet including 7-year eddy covariance-based evapotranspiration and auxilary data at Yunxiao mangrove flux tower
<p>An Excel spreadsheet including 7-year eddy covariance-based evapotranspiration and auxilary data at Yunxiao mangrove flux tower required to reproduce key results in the main text of a manuscript (each figure corresponds to a single sheet). Contact Xudong Zhu at Xiamen University (xdzhu@xmu.edu.cn) if you have any question.</p>
Resampling code with sample data for: Eddy-covariance with slow-response greenhouse gas analyser on tall towers
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An Excel spreadsheet including eddy covariance and meteorological data measured at Nanji Island flux tower, Southern China.
<p>The data was measured using an open-path eddy covariance system in a subtropical island forest located in the Nanji Islands National Marine Protected Area in southern China. The results will support for a paper entitled "Carbon sink potential and its driving mechanisms in an island forest nature reserve in southern China". Contact Xianglan Li at Beijing Normal University (xlli@bnu.edu.cn) if you have any question.</p>
Data associated with article "Bulk Transfer Coefficients Estimated from Eddy-Covariance Measurements Over Lakes and Reservoirs" by Guseva et al., 2022
<p>The data includes <strong>(a)</strong> the general information about the lakes and reservoirs under study (e.g., lake surface area, lake mean and maximum depth); <strong>(b)</strong> the publications and data repository references for each individual lake or reservoir where we took the original datasets from (for details, see the article); <strong>(c)</strong> the number of data points (for the estimated bulk transfer coefficients) and filters applied to each dataset. ('<em>Table_Data_Bulk_Transfer_Coeff.docx</em>')</p> <p>In addition, we attach the derived quantities for each lake and reservoir that we analyzed in our manuscript: the neutral bulk transfer coefficients of <strong>(a)</strong> momentum (the drag coefficient); <strong>(b)</strong> heat (the Stanton number); <strong>(c)</strong> water vapor (the Dalton number). ('<em>Data_Bulk_Transfer_Coeff.xlsx</em>')</p> <p><strong><em>Update 22.11.2022</em></strong>: After the first round of revisions we upload the new version of the data since we had to recalculate the transfer coefficients. <strong>(1)</strong> We added the median values of the transfer coefficients; <strong>(2)</strong> we added the transfer coefficients accounting for gustiness. ('<em>Data_Bulk_Transfer_Coeff.xlsx</em>')</p>
Response of ecosystem productivity to high vapor pressure deficit and low soil moisture: lessons learned from the global eddy-covariance observations
<p>The generated datasets for conducting the analysis are available from the dataset of the FLUXNET2015 Tier one (https://fluxnet.org/data/download-data/), the AmeriFlux ONEFlux (https://ameriflux.lbl.gov/data/download-data/), and the ICOS Drought-2018 (https://www.icos-cp.eu/data-products/YVR0-4898). The FLUXNET2015 Tier one, the AmeriFlux, and the ICOS are all licensed under the Creative Commons Attribution 4.0 International license (CC-BY-4.0) (<a href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</a>).</p>
Scalar flux profiles in the unstable atmospheric surface layer under the influence of large eddies: Implications for eddy covariance flux measurements and the non-closure problem
<p>This dataset contains the data used in the submitted manuscript of Liu, Liu, Huang, Desai, Zhang, Ghannam, and Katul 2023. Please refer to the manuscript for the detailed description of the dataset.</p>
Software code for simulations and analyses concerning the calculation of canopy stomatal conductance at eddy covariance sites
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Data from: Seasonal ecosystem metabolism across shallow benthic habitats measured by aquatic eddy covariance
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Technical note: Estimating light-use efficiency of benthic habitats using underwater O2 eddy covariance
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Eddy covariance data measured at the CAP LTER flux tower located in the west Phoenix, AZ neighborhood of Maryvale from 2011-12-16 through 2012-12-31
The CAP LTER maintains a flux tower to facilitate neighborhood-scale investigations of atmospheric processes in a Phoenix, AZ suburb. Capitalizing on comprehensive measurements of energy (heat and radiation) and matter (water and carbon dioxide) exchanges between the atmosphere and the urban surface, this project adds significantly to research investigating how urbanization affects local weather, climate, and air quality. An antenna-mounted array of sophisticated sensors measuring temperature, humidity, and wind speed and direction at high temporal resolutions facilitates the calculation of energy and material fluxes. The residential setting where the tower is positioned was selected on account of the homogeneous building design (single-story, single-family, detached dwellings) representative of many neighborhoods throughout the greater Phoenix metropolitan area. To avoid the influence of localized turbulence and material fluxes created by anomalous surface objects, the antenna extends vertically approximately 75 ft to sample neighborhood-scale fluxes. This dataset contains 30-minute post-processed eddy covariance data measured at the CAP LTER tower located in the west Phoenix neighborhood of Maryvale from Dec 16 2011 to Dec 31 2012.
Lorentzian filter correction of turbulence measurements on oscillating floating platforms: impact on wind spectra and eddy covariance fluxes
<p class="MsoTitle">Turbulence and eddy covariance measurements on a floating platform over water surfaces can be contaminated by platform oscillations, which may affect the calculated air–water exchange. The conventional method for decontamination of the platform oscillations from the wind velocity measurements requires the installation of an additional sensitive, and often costly, motion sensor. This paper examines a new mathematical decontamination method, termed Lorentzian filter, which avoids the need for such an instrument. The method, based on the Lorentzian function, capitalizes on the pseudo-harmonic behavior of the platform oscillations and reduces the amplitude of turbulent wind velocity data detected as artifacts at the specific natural frequencies of the platform. The Lorentzian filter was applied to wind velocity data measured by sonic anemometer and eddy covariance system over the Dead Sea, Israel, for 30 days. We examined three approaches of dealing with motion contamination: Lorentzian filter decontamination, motion sensor decontamination, and non-filtered raw wind velocity. Using the 3D wind velocity series, we examined the wind spectra, the co-spectra of water vapor concentration and horizontal wind speed with vertical wind speed and H2O and momentum fluxes. The Lorentzian filter performed very well in decontaminating the wind spectrum, meaning that it efficiently identified the contamination in the natural oscillation frequency and returned a decontaminated wind velocity time series. The co-spectra and fluxes were less prone to the contamination of platform oscillations, presumably due to low correlations between the spurious wind velocity components and other measured scalars, such as water vapor.</p>
Barro Colorado Island - eddy covariance flux data (2012-2017)
<p>This dataset contains CO2/H2O eddy covariance fluxes and other microclimatic observations observed on Barro Colorado Island (Panama) from 2012 to 2017. Data were acquired and processed using standard routines (see Methods). Data are organized in a spreadsheet with each variable in a column.</p>
Barro Colorado Island - eddy covariance flux data (2012-2017)
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Lorentzian filter correction of turbulence measurements on oscillating floating platforms: impact on wind spectra and eddy covariance fluxes
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CARAFE: Regional Airborne Greenhouse Gases Eddy Covariance Measurements, 2016-2017
This dataset provides airborne eddy covariance (EC) fluxes of carbon dioxide, methane, sensible heat, and latent heat at high spatial resolution collected during the NASA Carbon Airborne Flux Experiment (CARAFE) airborne 2016 and 2017 campaigns. CARAFE utilized the NASA C-23 Sherpa aircraft with a suite of commercial and custom instrumentation. Deployment occurred across the Mid-Atlantic Region for the period 2016-09-07 through 2016-09-26 and 2017-05-03 through 2017-05-26. The data also include downwelling radiation, water vapor, pressure, temperature, wind, and aircraft navigation data. Airborne EC can quantify surface fluxes at local to regional scales, potentially helping to bridge gaps between top-down and bottom-up flux estimates and offering novel insights into biophysical and biogeochemical processes.
Land Surface Phenology, Eddy Covariance Tower Sites, North America, 2017-2021
This land surface phenology (LSP) dataset provides spatially explicit data related to the timing of phenological changes such as the start, peak, and end of vegetation activity, vegetation index metrics and associated quality assurance flags. The data are for the growing seasons of 2017-2021 for 10-km x 10-km windows centered over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. The dataset is derived at 3-m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. These LSP data can be used to assess satellite-based LSP products, to evaluate predictions from land surface models, and to analyze processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes. The data are provided in NetCDF format along with geospatial area-of-interest information and visualizations of the analysis window for each site in GeoJSON and HTML formats.
Data for "Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide"
<p>The final data set used in manuscript "Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide" by Kohonen et al. (2020). The data set contains carbonyl sulfide (COS), carbon dioxide (CO2), carbon monoxide (CO) and water vapor (H2O) fluxes, together with flux ancillary data, measured at Hyytiälä forest in Juupajoki, Southern Finland, from July 2015 to October 2015. Hyytiala_COS_ECflux_2015.csv includes the quality screened flux data without u* filtering or storage correction. Final_ECfluxes_2015.dat includes the final data set of quality screened, u* filtered, storage corrected and gap-filled flux data. Raw data and data processed with other processing options are available upon request from the author.</p>
Measured wave, eddy-covariance and energy budget data
<p>Measurement data of wave, eddy-covariance and energy budget in Lake Balaton, Hungary</p> <p>May - Oct 2019</p>
A Dataset for Applying Machine Learning and Eddy Covariance Approaches to Model Mangrove Carbon Production (ML-MCP)
<p>The Mangrove Carbon Production (ML-MCP) dataset (daily time scale) encompasses comprehensive measurements of carbon production in mangrove ecosystems from four EC tower station in the USA and China, derived using advanced machine learning models and eddy covariance techniques. This dataset includes various variables such as carbon fluxes, environmental factors. By integrating machine learning algorithms, the dataset enhances the accuracy of carbon productivity estimations, facilitating better understanding and management of mangrove ecosystems' role in carbon sequestration and climate regulation.</p>
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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.
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.
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.
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.
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.