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3,517 results for “Weeks”
ERA5-Land weekly: Surface temperature, weekly time series for Europe at 1 km resolution (2016 - 2020)
<p>Overview:<br> ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.</p> <p>Surface temperature:<br> Temperature of the surface of the Earth. The skin temperature is the theoretical temperature that is required to satisfy the surface energy balance. It represents the temperature of the uppermost surface layer, which has no heat capacity and so can respond instantaneously to changes in surface fluxes.</p> <p>Processing steps:<br> The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically:<br> 1. spatially aggregate CHELSA to the resolution of ERA5-Land<br> 2. calculate difference of ERA5-Land - aggregated CHELSA<br> 3. interpolate differences with a Gaussian filter to 30 arc seconds<br> 4. add the interpolated differences to CHELSA</p> <p>The spatially enhanced daily ERA5-Land data has been aggregated on a weekly basis (starting from Saturday) for the time period 2016 - 2020. Data available is the weekly average of daily averages, the weekly minimum of daily minima and the weekly maximum of daily maxima of surface temperature.</p> <p>File naming:<br> Average of daily average: <code>era5_land_ts_avg_weekly_YYYY_MM_DD.tif</code><br> Max of daily max: <code>era5_land_ts_max_weekly_YYYY_MM_DD.tif</code><br> Min of daily min: <code>era5_land_ts_min_weekly_YYYY_MM_DD.tif</code></p> <p>The date in the file name determines the start day of the week (Saturday).</p> <p>Pixel values:<br> °C * 10 Example: Value 302 = 30.2 °C</p> <p>The QML or SLD style files can be used for visualization of the temperature layers.</p> <p>Coordinate reference system:<br> ETRS89 / LAEA Europe (EPSG:3035) (EPSG:3035)</p> <p>Spatial extent:<br> north: 82N<br> south: 18S<br> west: -32W<br> east: 61E</p> <p>Spatial resolution:<br> 1 km</p> <p>Temporal resolution:<br> weekly</p> <p>Time period:<br> 01/01/2016 - 12/31/2020</p> <p>Format: GeoTIFF</p> <p>Representation type: Grid</p> <p>Software used:<br> GRASS 8.0</p> <p>Original ERA5-Land dataset license:<br> <a href="https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf">https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf</a></p> <p>CHELSA climatologies (V1.2):<br> Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. <a href="http://dx.doi.org/doi:10.5061/dryad.kd1d4">http://dx.doi.org/doi:10.5061/dryad.kd1d4</a><br> Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. <a href="https://doi.org/10.1038/sdata.2017.122">https://doi.org/10.1038/sdata.2017.122</a></p> <p>Other resources:<br> https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/601ea08c-0768-4af3-a8fa-7da25fb9125b</p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Contact:<br> mundialis GmbH & Co. KG, info@mundialis.de</p>
ERA5-Land weekly: Air temperature at 2 meter above surface, weekly time series for Europe at 1 km resolution (2016 - 2020)
<p>Overview:<br> ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.</p> <p>Air temperature (2 m):<br> Temperature of air at 2m above the surface of land, sea or in-land waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.</p> <p>Processing steps:<br> The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically:<br> 1. spatially aggregate CHELSA to the resolution of ERA5-Land<br> 2. calculate difference of ERA5-Land - aggregated CHELSA<br> 3. interpolate differences with a Gaussian filter to 30 arc seconds<br> 4. add the interpolated differences to CHELSA</p> <p>The spatially enhanced daily ERA5-Land data has been aggregated on a weekly basis starting from Saturday for the time period 2016 - 2020.<br> Data available is the weekly average of daily averages, the weekly minimum of daily minima and the weekly maximum of daily maxima of air temperature (2 m).</p> <p>File naming:<br> Average of daily average: <code>era5_land_t2m_avg_weekly_YYYY_MM_DD.tif</code><br> Max of daily max: <code>era5_land_t2m_max_weekly_YYYY_MM_DD.tif</code><br> Min of daily min: <code>era5_land_t2m_min_weekly_YYYY_MM_DD.tif</code></p> <p>The date in the file name determines the start day of the week (Saturday).</p> <p>Pixel value:<br> °C * 10<br> Example: Value 44 = 4.4 °C</p> <p>The QML or SLD style files can be used for visualization of the temperature layers.</p> <p>Coordinate reference system:<br> ETRS89 / LAEA Europe (EPSG:3035) (EPSG:3035)</p> <p>Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E</p> <p>Spatial resolution:<br> 1km</p> <p>Temporal resolution:<br> weekly</p> <p>Time period:<br> 01/01/2016 - 12/31/2020</p> <p>Format: GeoTIFF</p> <p>Representation type: Grid</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)</p> <p>Lineage:<br> Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used.</p> <p>Original ERA5-Land dataset license:<br> <a href="https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf">https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf</a></p> <p>CHELSA climatologies (V1.2):<br> Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. <a href="http://dx.doi.org/doi:10.5061/dryad.kd1d4">http://dx.doi.org/doi:10.5061/dryad.kd1d4</a><br> Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. <a href="https://doi.org/10.1038/sdata.2017.122">https://doi.org/10.1038/sdata.2017.122</a></p> <p>Other resources:<br> <a href="https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/601ea08c-0768-4af3-a8fa-7da25fb9125b">https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/601ea08c-0768-4af3-a8fa-7da25fb9125b</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Contact:<br> mundialis GmbH & Co. KG, info@mundialis.de</p>
Weekly plots of Great Britain's half-hourly electrical system weather dependent generation, net imports and overall demand from 2008-11-10
<p>Plots that show the electrical system transition of Great Britain, they were created to form the individual frames for a video of the transition.</p>
BTO Garden BirdWatch: Weekly butterfly abundance data for modelling trends in UK gardens
<p>Dataset used to estimate annual abundance indices and trends for UK butterflies in gardens, covering the period 2007 to 2020.</p> <p>Data have been collected as part of the British Trust for Ornithology (BTO) Garden BirdWatch (GBW) survey. GBW is a structured, citizen science monitoring programme whereby volunteers record weekly abundances of various bird, invertebrate, mammal, reptile and amphibian species in (predominantly suburban and rural) gardens. See <a href="http://www.bto.org/gbw">www.bto.org/gbw</a> for further information about the survey. </p> <p>This dataset has been pre-filtered to meet criteria for inclusion in the modelling of butterfly species trends, as described by <a href="https://doi.org/10.1111/icad.12645">Plummer et al 2023</a>. Please refer to the 'readme' file for further details.</p> <p>We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Twice weekly monitoring of a Microtus ochrogaster population and social behavior in alfalfa in eastern Illinois, 1982-1987.
These data were obtained as part of a field study on social behavior of the prairie vole, Microtus ochrogaster in alfalfa. The study was conducted in two adjacent 1-ha alfalfa (Medicago sativa) fields within the University of Illinois Biological Research Area (Phillips Tract). Social groups were monitored over a 63-month period, from March 1982 through July 1984 in field 1 and from October 1983 to May 1987 in field 2, by locating underground and surface nests and subsequent trapping, twice weekly. 4-5 live traps were set around the entrances to underground nests and runways leading to a surface nest of social groups. Each month the study sites were also trapped at a 10-m grid interval as a part of an ongoing 25-year trapping study (Getz, L.L. 2024. Environmental Data Initiative. https://doi.org/10.6073/pasta/2dae8f08578ce31e7817c92a0f6acc87).
Week-long continuous noise levels measured by an IoT-based device - EcoDecibel, in Sanzhi District, Taiwan, Aug 12 2021 - Aug 18 2021.
Noise pollution is a growing concern in urban and rural environments, impacting public health and quality of life. We conducted a study to check the validation of an IoT based, low cost, noise sensor - EcoDecibel as compared to traditional Class 1 and Class 2 noise meters in indoor as well as outdoor environments. Data was collected continuously over a seven-day period at various sites, including arterial roadways, county highways, and environmental areas. The primary objective was to evaluate the performance of the EcoDecibel device in comparison to the gold standard noise meters which was conducted in different settings in indoor and outdoor environments and then the EcoDecibel device was set up in field to analyse the real world noise measurements.Despite its lower cost, the EcoDecibel device demonstrated a high degree of accuracy with an R2 value of 0.9 when compared to the standard devices. This dataset provides valuable insights into noise pollution levels across different environments and highlights the potential of low-cost noise measurement devices for widespread monitoring and research. The metadata accompanying this dataset includes detailed information on the experimental setup, data collection methods, and analysis procedures. The dataset is openly available for further research and validation, promoting transparency and reproducibility in environmental noise studies.
Marcell Experimental Forest weekly or biweekly streamwater chemistry at the S1 catchment, 2007 - ongoing
This data set is a record of water chemistry for the stream draining the S1 catchment and bog at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. Stream water samples were usually collected every one or two weeks since 2007 as part of the long-term monitoring program of the S1 catchment. Some samples were collected weekly as part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) project, with monitoring starting during 2011 prior to initiation of experimental warming in that study (during and after 2014). Samples are measured for pH, specific conductivity, anions (chloride, sulfate), cations (calcium, magnesium, potassium, sodium, aluminum, iron, strontium), silicon, nutrients (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon. Occasionally, stable water isotopes and concentrations of ferrous and ferric iron have been measured. More values will be added as additional water samples are collected and analyzed (concentrations and isotopes), or archived water samples are analyzed (mostly for stable water isotopes). The MEF is operated and maintained by the USDA Forest Service, Northern Research Station. The SPRUCE experiment is a multi-year cooperative project among scientists of the Oak Ridge National Laboratory operated by UT-Battelle, LLC and the USDA Forest Service, Northern Research Station, with funding from the US Department of Energy, Biological and Environmental Research Program.
Weekly Normalized Difference Vegetation Index (NDVI) data from Roche Moutonnee, Toolik Field Station, Imnavait, and Sag river DOT sites, in the northern foothills of the Brooks Range, Alaska, summer 2010-2014.
Weekly Normalized Difference Vegetation Index (NDVI) data from Roche Moutonnee, Toolik Lake Field Station, Imnavait Creek and Sagavanirktok River DOT sites in the northern foothills of the Brooks Range, Alaska. Located south of the Arctic LTER and Toolik Lake Field Station. Data collected from May to July 2010-2014. Methods and further data published in Ecography by Rich, et al. 2013.
Arthropod pitfall trap biomass captured (weekly) and pitfall biomass model predictions (daily) near Toolik Field Station, Alaska, summers 2012-2016.
This data set contains information about the per pitfall trap arthropod biomass captured (or modeled using GAM modelling approaches) near Toolik Field Station from 2012 to 2016 under National Science Foundation (NSF) Office of Polar Programs ARC 0908444 (to Laura Gough), ARC 0908602 (to Natalie Boelman), and ARC 0909133 (to John Wingfield). It is associated with publication DOI: 10.1111/jav.01712.
Air Temperature, Soil Temperature, Precipitation, Snow Depth at Long Term Tree Growth Sites; 1968-Present : Weekly
Part of the Long Term Tree Growth study. This dataset is an accumulation of various manual measurements made on a weekly to monthly basis. It originally included snow stakes, rain buckets, max/min thermometers and a series of soil temperature sensors. Over the years equipment has changed. The soil temperature sensors exceeded their field life during the 1990's and were dropped from the study. In 2001 logging air temperature and relative humidity sensors were installed and those measurements were discontinued. In 2002 logging rain gauges were installed to replace the manual buckets. Both styles were during that growing season and the manual buckets were removed before the 2003 field season. All that remains active in this dataset are the snow stake measurements.
Ground Water Depth Readings at BCEF/LTER Floodplain Sites, 1991-Present: Weekly
Ground water depth readings were collected at BCEF/LTER floodplain sites beginning in 1991. Wells were visited and measured weekly during the growing season.
Soil Moisture taken with a neutron probe 1969-1974 from 11 sites: Weekly
These original basic fertilization experiments were started to give preliminary information for designing future experiments and to study basic long term fertilization responses in a range of age classes for the dominant forest types of interior Alaska. In addition, the instrumentation of the control plots provide long term information on various environmental parameters. No fertilization or growth measurements were done in the black spruce stands.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (CiPEHR and DryPEHR): Weekly 13C Keeling Plot Signatures of Ecosystem Respiration from CiPEHR, DryPEHR and vegetation removal plots, and auxilliary data, 2015
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. How does warming and water table change impact the phenology of dominant plant species? 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 and OTC air warming on CIPEHR plots began in 2008; OTCs and drying on DryPEHR in 2011, though the soil warming effect had legacy since 2008. Vegetation removal was done outside the CiPEHR footprint, in July 2012. All vegetation was clipped at the surface and plots were trenched to 30cm, regrowth was prevented by frequent weeding and by 2015 very little new growth was observed in the plots. Vegetation removal plots were paired with undisturbed, vegetated plots. The data presented here specifically addresses the questions, 1) What is the seasonal signal of ecosystem respiration 13C during the growing season, from snow melt to snow fall, 2) How
Weekly grab samples and manual specific conductivity, temperature, and turbidity measurements of streams at the LTER intensive and hillslope sites located in Macon County, North Carolina, within the Little Tennessee River Basin
Weekly grab samples and manual specific conductivity, temperature, and turbidity measurements were taken at 21 streams and rivers in Macon County, NC. Nine intensive sites were monitored weekly in 2010-2011, nine hillslope sites were monitored biweekly in 2012-2013, and three river sites were monitored weekly in 2010-2011 and biweekly in 2012-2013. Data from a brief study of three streams at the Buck Creek Pine Barrens in Clay County, NC, also was completed, as well as one grab sample at Porters Creek, Mountain View Intermediate School. Water samples were analyzed for chemistry at the Coweeta Analytical Lab. Specific conductivity and temperature data were collected using a YSI 30 handheld conductivity meter. Turbidity data were collected using a Hach 2100P turbidimeter.
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 13
<p>These data were collected from FIDIA machine tool controller during milling operation.</p> <p> </p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 11
<p>These data were collected from FIDIA machine tool controller during milling operation.</p> <p> </p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 09
<p>These data were collected from FIDIA machine tool controller during milling operation.</p> <p> </p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2019 Week 43
<p>These data were collected from FIDIA machine tool controller during milling operation.</p> <p> </p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2019 Week 52
<p>These data were collected from FIDIA machine tool controller during milling operation.</p> <p> </p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2019 Week 38
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
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
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.