Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,762
datasets available to search
ShareScore release 0.9.0
Dataset results
2,762 results for “Heating”
Global Ocean Heat Content Anomalies and Ocean Heat Uptake based on mapping Argo data using local Gaussian processes
<p>Monthly Ocean Heat Content Anomalies (OHCA) in the top 2000 dbar of the ocean are calculated (during 2004-2024, equatorward of 65 degree latitude) subtracting the mean over the period 2004-2024 from the monthly time series of OHC. Yearly OHCA time series are then calculated that include 1. one point per year, i.e., from averaging Jan to Dec (see files ending in “yearly.nc”), and 2. two points per year, i.e., from averaging Jan to Dec and Jul to Jun, respectively (see files ending in “yearly2.nc”). OHC fields are mapped using locally stationary Gaussian processes (defined over space and time) with data-driven decorrelation scales (Kuusela and Stein, 2018). A linear time trend was included in the estimate of the mean field (along with spatial terms and harmonics for the annual cycle). Mapping is done separately for different vertical sections: 15-20 dbar, 15-300 dbar, 300-700 dbar, 700-1850 dbar, 1800-1850 dbar. The 15-20 dbar (1800-1850 dbar) section is used to estimate OHCA for 0-15 dbar (1850-2000 dbar), where observations are sparser. Different vertical sections are combined to estimate global OHCA time series for 0-2000 dbar, 0-700 dbar, 700-2000 dbar (as indicated in the file names). The attribute "area" is included in the netcdf files and it tells the corresponding surface area for the estimates. Regions of the ocean that are shallower than 300 m or are not sufficiently well sampled by the Argo array are not included. Maps of the ocean masks used for the different vertical sections can be found in the .png files (blue shading indicates the area used for the horizontal integral); the bathymetry mask by Roemmich and Gilson (included in the file RG_ArgoClim_Temperature_2019.nc at https://sio-argo.ucsd.edu/RG_Climatology.html) is also used to define the ocean mask. Ocean Heat Uptake is calculated from the monthly OHCA and then averaged as described above to produce yearly time series included in the files for the different layers.</p> <p>For the uncertainty at each time point, the standard deviation of each OHCA/OHU value in the time series is included. When plotting a time series, the user may consider, e.g., shading plus/minus 1* or 1.96*standard deviation (corresponding to a confidence level of 68% or 95% respectively). These standard deviations in the files are estimated using spatially and temporally dependent conditional simulations of monthly gridded anomalies. When combining different layers, the standard deviation of the sum is conservatively estimated as the sum of the standard deviations. </p> <p>Finally, OHCA/OHU trends are estimated via a least-squares fit and reported in the variable metadata with uncertainties (confidence level of 68%). Trend uncertainties are estimated by repeating the fit for each member of the conditional simulation ensemble described above.</p> <p> </p>
Datasets for "A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models"
<p>This repository contains the post-processed model outputs from HAMSTER v1.2.0 as used in the following paper: </p> <p>Keune, J., Schumacher, D. L., and Miralles, D. G.: A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models, Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, 2022.<br> <br> The data set contains (1) global validation statistics for the three fluxes (evaporation, precipitation, sensible heat), and (2) the climatological source regions of precipitation and heat for Denver, Beijing and Windhoek. The former are found in the directory 'validation/global', and the latter are found in the directories '1001' (Denver), '3001' (Beijing) and '5002' (Windhoek). Multiple experiments were performed to assess the uncertainty of the source regions. Thus, multiple files exist, that show the same variables but for multiple experiments (indicated by the names "ALLPBL", "RH-10-20", "SOD08-SCH19", "SCH20", "FAS19" in the file name). For the moisture source regions, the uncertainty of the attribution methodology was assessed; these are indicated by the different folders, i.e. 'linear_upscaled' and 'random2_upscaled'. For each city and each experiment, the climatologically averaged source regions ('_mean.nc') and the climatologically averaged individual backward day contributions ('_bwmean.nc') are provided. Data sets are in the netCDF format and contain metadata following the CF convention.</p>
Scenarios of technical and useful ground-source heat pump potential for building heating and cooling in Western Switzerland
<p>This dataset contains an estimation of the useful and technical potential of shallow ground-source heat pumps (GSHPs) for Western Switzerland, at a spatial resolution of 400 x 400 m<sup>2</sup>. The <strong>technical potential</strong> is hereby defined as the maximum energy that could be extracted from GSHP systems in case of their dense deployment, such as to <em>avoid the over-exploitation</em> of the heat capacity of the ground. We consider GSHPs with <em>vertical closed-loop borehole heat exchangers</em> (BHE) installed at depths of 50 - 200 m. The <strong>useful potential</strong> is defined as the potential that could be delivered to building heating and cooling systems via a water-to-water heat pump.</p> <p>The datasets contains future scenarios of heating and cooling demand, space cooling equipment deployment (service sector only) and climate change models and considers the potential use of DHC. The dataset covers around 80,000 property units (parcels) in the Swiss Cantons of Vaud and Geneva, excluding only the areas of the Alps and the Jura mountains.</p> <p>The data package contains information on the available area for GSHP systems, the heating and cooling demand as well as the resulting technical and useful potentials for all simulated scenarios of future cooling demand (200 Monte Carlo runs), for the case of <strong>direct heat supply</strong> (per pixel of 400 x 400 m<sup>2</sup>) as well as for <strong>district heating and cooling</strong> (DHC). In scenarios without DHC (direct heat supply), the results are summarized by pixel of 400 x 400 m<sup>2</sup>. In scenarios with DHC, the results of potentials <em>within</em> DHCs are summarized by DHC (see <em>*_in_dhc.csv</em>) while potentials <em>outside</em> of DHCs are summarized by pixel (see <em>*_outside_dhc.csv</em>).</p> <p>For details on the methodology applied to obtain the results provided in the data package, please refer to the above-mentioned research articles. A description of all files is provided in<em> Dataset documentation.pdf</em> and metadata is provided in <em>Datapackage.json.</em></p>
Experimental HIL datasets of a heat pump controlled by MPC or rule-based controllers for energy flexibility
<p>Hardware-in-the-loop experiment performed in the SEILAB laboratory of IREC<br> Air-to-water heat pump including a DHW tank for production of SH and DHW, which external unit is placed in a climate chamber that reproduces the desired weather conditions dynamically<br> Control is MPC or rule-based, both triggered either by a signal of price or CO2 intensity from the grid (4 series of experiments)<br> Connected to virtual residential building (flat) in Spanish Mediterranean climate<br> More information:<br> https://doi.org/10.1109/ACCESS.2019.2903084</p>
Heat balance of selected Brayton cycle
<p>The dataset provides the heat balance of the selected Brayton cycle among the 10 cycles considered. Simulations of several cases defined by a different supercritical CO2 cycle type were performed with Ebsilon software in order to assess the net power block efficiency of the cycle and the Levelized Cost of Electricity (LCOE) of the plant. Due to its highest efficiency among the 10 envisaged Brayton cycle options, it is the Partial Cooling with Intercooling and Reheating cycle that is selected.</p> <p>The datasets could help other people design a sCO2 Brayton cycle.</p> <p>For detailed analysis, please refer to Deliverable 1.1 (Process Parameters of Solar sCO2 Brayton Cycle) to be downloaded at: <a href="https://www.compassco2.eu/wp-content/uploads/2021/02/D1.1_Process-parameters-of-solar-sCO2-Brayton-cycle.pdf">https://www.compassco2.eu/wp-content/uploads/2021/02/D1.1_Process-parameters-of-solar-sCO2-Brayton-cycle.pdf</a></p>
Geothermal heat source estimations through ice flow modelling at Mýrdalsjökull, Iceland - Datasets
<p>This repository contains data used in the study "<em>Geothermal heat source estimations through ice flow modelling at</em><br><em>Mýrdalsjökull, Iceland", </em>to be published in <strong>The Cryosphere. </strong>A detailed reference will be added after publication.</p> <p>Details on processing of the data and the creation of the simulated data can be found in the aforementioned publication.</p> <p><strong>Data Specifications:</strong></p> <ul> <li>Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, <a href="http://https/epsg.io/3057">https://epsg.io/3057</a>)</li> <li>Origin of Elevation: meters above GRS80 ellipsoid (WGS84)</li> <li>Raster data format: GeoTIFF</li> <li>Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.</li> </ul> <p><strong>File descriptions:</strong></p> <ul> <li><em><strong>bedrock_Magnusson_etal_2021.tif: </strong></em>contains bedrock data published by Magnússon et al. 2021 for the simulation domain used in the paper. See reference below.</li> <li><em><strong>surface_27092016_pleiades.tif: </strong></em>contains glacier surface data from September 27th, 2016 which is used as a starting geometry for the simulations described in the paper. This data is based on Pléiades satellite images.</li> <li><em><strong>surface_01092017_pleiades.tif: </strong></em>contains glacier surface data from September 1st, 2017 which is used as a reference target geometry for the simulations described in the paper. This data is based on Pléiades satellite images.</li> <li><em><strong>HM_run04.tif:</strong></em> contains the best fitting simulation based surface which was compared to <em><strong>surface_01092017_pleiades.tif </strong></em>in the paper.</li> <li><em><strong>HM_run04_hillshade.png: </strong></em>a simple hillshade image for preview purposes.</li> </ul> <p> </p>
Supplementary data for- Heat-evolved microalgae (Symbiodiniaceae) are stable symbionts and influence thermal tolerance of the sea anemone Exaiptasia diaphana
<p>Raw data and R codes for - Heat-evolved microalgae (Symbiodiniaceae) are stable symbionts and influence thermal tolerance of the sea anemone <em>Exaiptasia diaphana</em>. DOI: 10.1111/1462-2920.70011</p>
EU-27 Country Mapping of Financing Schemes to decarbonize Buildings, Heating and Cooling
<p>This dataset contains the mapping of all public and private financing instruments currently available to support the decarbonization of the building stock. The mapping is divided into two sheets: Public Schemes and Private Schemes. Each scheme is classified per country, level (European, National, Regional, Local), Name in English and in the local language, sectors (Y= directly covered, (Y)= indirectly covered, that is not explicitly mentioned, but reasonably applicable, blank= not covered), type of instrument, main and additional links, a short description and the last time the page was visited. Additional socio-economic, climate and energy indicators and a correlation matrix are provided.</p>
Sensible heat fluxes control cloud trail strength
<p>This dataset contains a minimal set of data used to create figures in Johnston et al. (2023) Sensible Heat Fluxes Control Cloud Trail Strength, Quarterly Journal of the Royal Meteorological Society. Additional liquid water path data from the control experiment (H250E250) is also provided to better visualise the cloud field in this central experiment.</p>
Soil and meteorological data, and finite element simulation framework for heat transfer through shrubs in winter near Lautaret pass, French Alps
<p>The data allow the calculation using finite element modeling of heat transfer through shrub branches and snow between the atmosphere and the soil. The shrubs are green alders (Alnus viridis). The site where they are found is called Alnus-Nivus (45.034750°N, 6.413630°E, 2034 m asl) near Col du Lautaret, French Alps. The soil data consist in temperature and volumetric liquid water content at 5 and 15 cm depths. One spot is near the alder collar (ALNUS), the other spot is 6 m away, under grass (GRASS).</p> <p>The meteorological data were obtained from the FR-Clt station, 750 m away (45.041278°N, 6.410611°E, 2046 m asl). See (Gupta et al., 2023) for details. Only the data relevant for heat transfer simulations are given.</p> <p>The simulation framework gives the alder mesh used in the heat transfer simulations. Typical simulations use a wood thermal conductivity of 1 W m<sup>-1</sup> K<sup>-1</sup> and a snow thermal conductivity of 0.1 W m<sup>-1</sup> K<sup>-1</sup>. Based on observations, the snow height at Alnus-Nivus is likely to be at least twice the value at FR-Clt. Forcing uses the snow surface temperature, derived from upwelling longwave radiation using an emissivity of 1. The data allow testing thermal bridging through shrub branches. These data are used in a publication in preparation: Domine, Fourteau, Choler, Exploration of Thermal Bridging Through Shrub Branches in Alpine Snow.</p> <p>Reference</p> <p>Gupta, A., Reverdy, A., Cohard, J. M., Hector, B., Descloitres, M., Vandervaere, J. P., Coulaud, C., Biron, R., Liger, L., Maxwell, R., Valay, J. G., and Voisin, D.: Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment, Hydrol. Earth Syst. Sci., 27, 191-212, 2023.</p>
Regional Heat Vulnerability Map and Cooling Solutions: A webtool of the Healthy Urban Environments Initiative
## Regional Heat Vulnerability Map and Cooling Solutions The regional heat vulnerability map and cooling solutions webtool offers two data sources for equitable heat mitigation. The dashboard layers vulnerability data onto land surface temperature regional rankings to identify areas with high and low heat exposure and vulnerability as well as the existing assets in each census block group. Additional layers can be added into the heat vulnerability map to highlight how heat affects critical infrastructures including schools, mobile home parks, parking lots, public transportation stops, pedestrian thoroughfares, and bikeways. The solutions tab showcases a variety of heat mitigation solutions and the research behind them. Heat-related solutions and resources from urban Maricopa County are included, including solutions funded through the Healthy Urban Environment Initiative. The data catalogued here are the underlying data that populate the webtool. ## Healthy Urban Environment (HUE) Initiative - Overview HUE is a solutions-focused research, policy and technology incubator to create healthier communities across Maricopa County (central Arizona, USA) through collaboration between researchers, practitioners and community members. As such, HUE funded rapid development, testing and deployment of heat-mitigation and air-quality improvement strategies and technologies. Heat emerged as the urgent focus, as urban centers across the desert Southwest continue to grow in size and density, aggravating existing challenges posed by the expansion of the built environment. In Phoenix, AZ, this expansion of the built environment creates conditions which magnify the intensity and duration of heat – making it difficult for residents to achieve thermal comfort throughout the day and night. Further, the legacies of urban sprawl and transportation planning in the Phoenix, Arizona metropolitan area have contributed to challenges with atmospheric pollutants. Importantly, urban heat and air qua
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Peak growing season aboveground biomass 2011-2017. (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bnz/502/16. The abstract below was extracted from the Level 0 data package and is included for context: 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 warmign 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 achieve using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. Above ground plant biomass was surveyed non-destructively using a point-intercept method for all vascular and moss species at peak growing season.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Aboveground plant biomass, 2009-2017. (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bnz/501/17. The abstract below was extracted from the Level 0 data package and is included for context: 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 set includes aboveground plant biomass from winter warming, summer warming, and control treatment plots at CiPEHR.
Public Transit Infrastructure and Heat Perceptions in Hot and Dry Climates (June-July, 2018; Phoenix, Arizona, USA)
Increasing the use of public transit is an important sustainability goal targeted by many cities worldwide. However, cities in hot and warming climates risk to compromise residents’ health and thermal comfort by incentivizing public transit use and, thus, subjecting them to prolonged heat exposure. This dataset contains data collected during a study on the relationships between public transit infrastructures, microclimate and heat perceptions in the hot and dry city of Phoenix, Arizona. A field campaign at six Phoenix bus stops was held between June 6 and July 27, 2018. Filed campaign consisted of surveying bus riders at bus stops and measuring microclimate variables at sun exposed and shaded locations at bus stops. Standard, advertising and art bus stop types along an arterial Phoenix road in South Mountain Village neighborhood were sampled. Standard and advertising bus stop shelters were metal with no landscaping, art stops had a larger polycarbonate canopy, integrated artwork, trees and landscaping features. Eighty-three participants filled out the survey, 241 microclimate measurements and 1003 surface temperatures at bus stops were taken. Data were collected at three intervals: 7:00-9:00am, 12:00-2:00pm, and 3:00-5:00pm. Differences between sun and shade, as well as heat perceptions were analyzed using statistical methods. The research team has found that certain infrastructure types are more effective in reducing particular microclimate variables, for instance, trees were most effective in reducing air temperature by as much as 1.3°C on average, and shade from vertical advertising sign was most effective in reducing mean radiant temperature by an average of 11°C. Many surface temperatures of sun exposed materials sampled at bus stops exceeded skin burn thresholds. Study participants perceived stops with improved infrastructure and landscaping as slightly cooler. Data collected in this study gives a glimpse of current microclimate conditions at Phoenix bus stops
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Peak growing season aboveground biomass 2011-2017. (Reformatted to a Darwin Core Archive)
This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/264/3, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bnz/502/16. The abstract below was extracted from the Level 0 data package and is included for context: 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 warmign 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 achieve using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. Above ground plant biomass was surveyed non-destructively using a point-intercept method for all vascular and moss species at peak growing season.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Half-hourly soil moisture and temperature data, 2008-2024
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 set includes half-hourly values of surface moisture content (gravimetric, 0-5cm), depth-integrated soil moisture (volumetric, 0-20 cm), and soil temperature in winter warming, summer warming, and control treatment plots at CiPEHR.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Weekly thaw depth data, 2009-2024
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 set includes weekly thaw depth measurements collected from winter warming, summer warming, and control treatment plots at CiPEHR. Additional measurements from on-plot gas flux wells, water table monitoring wells, and off-plot locations are also reported. Note that the experimental warming portion of this experiment concluded in 2022. These data are a continuation of measurements taken at previously warmed plots but plots were not actively manipulated after 2022.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Weekly thaw depth data, 2011-2022
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 weekly ground thaw measurements.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Seasonal water table depth data, 2011-2022
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 includes water table depth measurements collected from the drying experiment (dry and control) at DryPEHR and winter warming and control treatment plots at CiPEHR for the ice-free period of 2011-2020.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Aboveground plant biomass, 2009-2017, 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 set includes aboveground plant biomass from winter warming, summer warming, and control treatment plots at CiPEHR.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.