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196 results for “heatwave”
Supporting data for “Climate Intervention through Stratospheric Aerosol Injection may partially mitigate marine heatwaves"
Although climate intervention aims to lower the global average temperature, the potential impact of Stratospheric Aerosol Injection on marine heatwaves (MHW) has not been thoroughly examined. This spatial dataset provides global and regional MHW metrics—such as frequency, maximum intensity, and duration—from the Community Earth System Model, version 2 (CESM2), using the baseline scenario SSP2-4.5, referred to as a no climate intervention scenario, and the ARISE-SAI ensemble. The ARISE-SAI model uses the SSP2-4.5 scenario, introducing stratospheric aerosol injection at approximately 21 km in 2035, aiming to keep global mean surface air temperature near 1.5°C for ARISE-SAI-1.5 and near 1.0°C for ARISE-SAI-1.0 above pre-industrial levels. The dataset includes global MHW properties for the historical period (1990-2009), the current period under SSP2-4.5 emission scenario (2015-2034), and future scenarios under SSP2-4.5, ARISE-SAI-1.5, and ARISE-SAI-1.5 for 2050-2059 and 2060-2069.
Cascade Project at North Temperate Lakes LTER: Aquatic heatwave effects on chlorophyll 2008-2019
Temperature and chlorophyll data were collated from multiple datasets to identify the effects of aquatic heatwaves on phytoplankton in three north temperate lakes, Peter Lake, Paul Lake, and Tuesday Lake between 2008 and 2019. Heatwaves were identified using a water temperature model constructed from temperature data from Sparkling Lake and Woodruff Airport between 1989 and 2022. Heatwave characteristics, water color, nutrients, grazing, and lake stability data are included to relate chlorophyll response to heatwaves to other conditions associated with a set of whole-lake experiments. The food web of Peter Lake was manipulated with largemouth bass additions between 2008 and 2011. Nutrient additions were made to Peter Lake and Tuesday Lake between 2013 and 2015, and again in Peter Lake in 2019. Paul Lake was always maintained as an unmanipulated reference lake. Full descriptions of the experiments can be found in Szydlowski et al., "Aquatic heatwaves increase surface chlorophyll concentrations in experimental and reference lakes."
Data in support of 'ENSO influences subsurface marine heatwave occurrence in the Kuroshio Extension'
<p>Data in support of 'Chandler M, Sprintall J, Zilberman NV. (2025). ENSO influences subsurface marine heatwave occurrence in the Kuroshio Extension. <em>Journal of Geophysical Research: Oceans</em>. <a href="https://doi.org/10.1029/2025JC022899" target="_blank" rel="noopener">https://doi.org/10.1029/2025JC022899</a>'</p> <p> </p> <p>There are 2 netCDF files:</p> <ol> <li>p40tem1211_2312.nc</li> <li>synthetic_T_10day_px40_kuroshio_chandler2024.nc</li> </ol> <p><strong>p40tem1211_2312.nc </strong>contains the temperature sections from <a href="https://www-hrx.ucsd.edu/px40.html">HR-XBT transect PX40</a> objectively mapped onto a 10-m depth grid and a 0.1° longitudinal grid. <em>[LONGITUDE; LATITUDE; DEPTH; TIME; TEM]</em></p> <p><strong>synthetic_T_10day_px40_kuroshio_chandler2024.nc</strong> contains the synthetic temperature anomaly time series between the surface and 800-m deep at the western end of transect PX40 over the period from January-1993 to April-2023, as well as the temperature annual cycle needed for reconstructing the full synthetic temperature time series. <em>[time; depth; longitude; latitude; T_prime; T_ann]</em></p> <p> </p> <p>There is 1 MATLAB file:</p> <ol> <li>px40_synthetic_T.m</li> </ol> <p><strong>px40_synthetic_T.m</strong> is the MATLAB script used to produce the synthetic temperature anomaly time series saved in synthetic_T_10day_px40_kuroshio_chandler2024.nc.</p> <p> </p> <p>There is 1 Julia file:</p> <ol> <li>px40_synthetic_T_julia.jl</li> </ol> <p><strong>px40_synthetic_T_julia.jl</strong> is a Julia implementation of the MATLAB script px40_synthetic_T.m.</p> <p> </p> <p>There is 1 R file:</p> <ol> <li>px40_synthetic_T_R.R</li> </ol> <p><strong>px40_synthetic_T_R.R</strong> is an R implementation of the MATLAB script px40_synthetic_T.m.</p> <p> </p> <p><code>Version history:</code><br><code>v1.0.0 First uploaded (25-November-2024)</code><br><code>v1.0.1 Julia script uploaded (18-January-2025)</code><br><code>v1.0.2 R script uploaded (28-January-2025)</code><br><code>v1.1.0 Updated description of synthetic_T_10day_px40_kuroshio_chandler2024.nc to include reference to accepted publication (21-August-2025)</code></p>
Observed and WRF-simulated near-surface meteorological parameters on selected James Ross Island glaciers during heatwaves in summer 2022/23
<p>The files contain time series of near-surface meteorological conditions observed on Triangular Glacier and Davies Dome on James Ross Island, Antarctica and simulated time series for these glaciers based on the Weather Research and Forecasting (WRF) model output. Observations of 2-m air temperature, 2-m wind speed, net radiation and glacier surface height are available from 01 November 2022 to 16 January 2023 (net radiation is available only on Triangular Glacier). Simulated values of 2-m air temperature, 2-m wind speed, net radiation, sensible and latent heat fluxes are available from 08 November 2022 to 16 January 2023.</p>
Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis
<p>The attached two datasets are the optimized inputs used to analyze predictability limits in the paper Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis. Specifically, the datasets correspond to the inputs used to produce the blue (global) and green (regional) loss curves in Figure S2. They are NetCDF files of dimensions batch (1), time (2), latitude (181), longitude (360), pressure levels (13), and may be run as Graphcast model inputs to initiate a forecast at 00 UTC 20 June 2021. Both datasets have been systematically perturbed to reduce the Graphcast model's loss function, which minimizes forecast eror as described in the manuscript. The global input seeks to reduce the loss over the entire globe, while the regional input seeks only to minimize error within the Pacific Northwest (42N to 60N and 130W to 110W). The optimized inputs result in a reduction of the loss by approximately 85% (global) and 93% (regional) when compared to a control Graphcast forecast without perturbations.</p>
Marine heatwaves statistics for the tropical western and central Pacific Ocean
<p>Processed marine heatwave metrics are provided for the tropical western and central Pacific Ocean region (120°E-140°W, 40°S-15°N). The metrics are computed from daily sea surface temperature (SST) data, from both observations and models. The observed marine heatwave data are calculated from NOAA 0.25° daily Optimum Interpolation Sea Surface Temperature (OISST) over the period 1982-2019. The modelled marine heatwave data are from analysis of 18 model simulations as part of the Coupled Model Intercomparison Project, Phase 6 (CMIP6) over the period 1982-2100, where two future scenarios have been analysed. Marine heatwaves are computed with respect to the 1995-2014 climatology. The marine heatwave data are provided on a grid point basis across the domain. Marine heatwave timeseries metrics are also provided for three case study regions: Fiji, Samoa, and Palau.</p>
Dataset for "Heatwave reveals potential for enhanced aerosol formation in Siberian boreal forest"
<p>This dataset supplements the manuscript "Heatwave reveals potential for enhanced aerosol formation in Siberian boreal forest", Environmental Research Letters, 2023. </p>
Identifying South African Marine Protected Areas at risk from marine heatwaves and cold spells
<p>This data reflects information on marine heatwaves (MHWs) and marine cold spells (MCSs) that occurred along the South African coast from January 1982 to April 2022, with special focus on Marine Protected Areas. Thermal metrics for MHW and MCS events were obtained using the HeatwaveR package (Schlegel and Smit, 2018) and the associated Marine Heatwave Tracker (Schlegel, 2020). </p> <p> </p> <p>THis data stems from Courtailac et al (in review) Indentifying South AFrican Marine Protected Areas at risk of marine heatwaves and cold-spells </p>
Modeled temperature and Marine heatwaves intensity in the coastal Northern Humboldt Current System
<p>This dataset includes the tridimensional modeled temperature and associated research data that support the results of the article "<strong><em>Comprehensive characterization of Marine Heatwaves in a coastal Northern Humboldt Current System regional model over recent decades</em></strong>".</p> <p>Specifically, it consists of three files (NetCDF format):<br> i) Northern_MHWs.nc, this file contains the daily modeled temperature (from 2000 to 2019) within the northern domain of analysis (3-8°S) within the 250 km nearshore band for each vertical layer ranging from 0 to 250m depth. In addition, daily snapshots of MHW intensity are also included by depth.<br> ii) Central_MHWs.mat, similar to the previous file, but for the central domain of analysis, from 8 to 13°S.<br> iii) Southern_MHWs.mat, similar to the previous file, but for the southern domain of analysis, from 13 to 18°S.</p>
Modelled urban climate island during the record-breaking 2022 heatwave in London
<p>This record is created as a data supplement for the manuscript "Estimated mortality attributable to the urban heat island during the record-breaking 2022 heatwave in London".</p> <p>These data were produced using the Weather Research Forecasting model with BEP-BEM. The model setup is described in Brousse et al (2023) <a href="doi.org/10.1175/JAMC-D-22-0142.1">10.1175/JAMC-D-22-0142.1</a>. These data cover the period 2022-07-10 to 2022-07-25, during which temperatures exceding<strong> </strong>40 °C were recorded in London for the first time.</p> <p>The data comprise two NetCDF files. One is labelled "Urb" one "Nourb". In the "Nourb" file, the urban tile is removed from the model and the land surface replaced by the nearest natural tile. This can be used to estimate the influence of the urban tile on the local climate.</p> <p>Variables included in the file are T2 (temperature at 2 m elevation in Kelvin), V10 and U10 (winds at 10 m elevation in metres per second), PSFC (surface level pressure in Pascal), RAINNC (rain in mm), TH2 (potential temperature at 2m elevation in Kelvin), and Q2 (specific humidity at 2 m elevation, which is dimensionless). All variables are provided at hourly timestep.</p> <p>Queries about this dataset can be directed to o.brousse@ucl.ac.uk</p>
Data supporting: Combined stress of an insecticide and heatwaves or elevated temperature induce community and food web effects in a Mediterranean freshwater ecosystem
<p>Data used to obtain the results of the research paper entitled: "Combined stress of an insecticide and heatwaves or elevated temperature induce community and food web effects in a Mediterranean freshwater ecosystem", published in the journal "Water Research". The data derives from an outdoor (meso-) cosm experiment in Spain (Imdea Water, Alcala de Henares) in which the transportable temperature and heatwave control device (TENTACLE) was used to investigate the multiple stressors effects of two different climate change scenarios related to temperature (i.e., elevated temperature and reoccurring heatwaves) in combination with the neonicotinoid insecticide imidacloprid.</p>
Heatwave indexes 1980-2018
<p>Heatwaves were defined as minimum temperature exceeding the 99th percentile of minimum temperature for the reference period (1986-2005) for four or more days.</p> <p>From this definition, four heatwave indicators are derived:</p> <p>Number of heatwave instances</p> <p>Total number of days of heatwave</p> <p>Heatwave degree-days over threshold, being the sum of the differences between the daily temperatures and the 99th percentile threshold</p> <p>Mean length of heatwaves</p> <p>Heatwave mean degrees over threshold, being the heatwave degree-days divided by the total number of days.</p> <p> </p> <p>These definitions were applied to ECMWF ERA5 temperature data at 0.5˚ grid resolution for the years 1980-2018. Each indicator is provided in a separate file.</p> <p> </p>
Marine heatwaves and cold spells events based on ESA-CCI SSTs (experimental product)
<p>This repository contains an extension of the catalogues of marine heatwaves (MHWs) and cold spells (MCSs) prepared by the National Research Council - Institute of Marine Sciences (CNR-ISMAR, Italy) within the ESA-funded CAREHeat project. The catalogues are based on the ESA-CCI sea surface temperature (SST) dataset (available from https://doi.org/10.24381/cds.cf608234) for the period 1982-2022, on a regular 1°x1° longitude-latitude grid.</p> <p>Events are identified for each pixel following the methodology of Hobday et al. (2016) after preprocessing. Event categories are provided as daily maps and metrics are given by event. Results are <strong>experimental</strong> since the post-processing procedure effectively removes interannual variability from the SST record, so please use having consulted the documentation and not for operational purposes. </p> <p><br>Please cite the reference paper "Serva, F., et al.: Detection of Satellite Sea Surface Temperature Extremes: Low Frequency Variability and Climate Change, JGR:Oceans, 10.1029/2025JC022886, 2025" when using the dataset in your work.</p>
Processed data for the manuscript, entitled "Substantial increase in heavy precipitation events preceded by moist heatwaves over China during 1961–2019"
<p>This is the dataset on annual frequency of heatwaves, heavy precipitation, and heatwave-heavy precipitation events during 1961-2019 at 1776 stations across China. This dataset is the processed results based on daily observations that are provided by the National Meteorological Science Data Center (<a href="http://data.cma.cn/en">http://data.cma.cn/en</a>). In this processed dataset, the "HW_HI" column is the annual frequency of heat-index-based heatwaves; "HW_TW" column is the annual frequency of wet-bulb temperature based heatwaves; "HP" is the annual frequency of heavy precipitation with taking the 95<sup>th</sup> percentile of non-zero precipitation at the threshold. "HWHP_HI"/"HWHP_TW" column indicate annual frequency of heavy precipitation preceded by HW_HI/HW_TW. All the results shown in the manuscript entitled "<strong>Substantial increase in heavy precipitation events preceded by moist heatwaves over China during 1961</strong>–<strong>2019</strong>", are obtained based on this processed dataset.</p>
Data used in the paper: Heatwaves, droughts, and fires: Exploring compound and cascading dry T hazards at the pan-European scale
<p>These datasets were used to analyze European compound and cascading dry hazards. The scripts are publicly available on GitHub: https://github.com/sjsutanto/Dryhazards.git.</p> <p>File Daily_SM_drought_WB_Converted.nc is for soil moisture drought, fwi_1990_2016_binary_95th_lowThreshold.nc is for wildfires, and datacube_2mtpp_19902016_HW.nc is for heatwaves.</p> <p> </p>
Validation of MODIS11A2 LST and glacier surface heatwave during 2001-2020 over Tibetan Plateau
<p>1,Validation of MODIS11A2 LST in 2019 using AWS temperature on the glacier</p> <p>2,Validation of MODIS11A2 LST during 2001-2020 using CMA station temperature over the Tibetan Plateau</p> <p>3,Glacier surface heatwave during 2001-2020 over the Tibetan Plateau glacier </p>
Marine heatwave datasheet for Northern Indian Ocean
<p>The datasheet gives a detailed information on the marine heatwave intensity from 1981 to 2020 at the three coral reef regions (Andaman and Nicobar, Gulf of Mannar and Lakshadweep archipelago) in the Northern Indian Ocean. This dataset was used to study various regional ecosystem changes from the variability in MHW over the period of time.</p>
Heatwaves characterization derived from observations and climate projections to assess thermal behavior of 7 European city-hubs: Milano, Athens, Logroño, Cork, Gdynia, Lillestrøm and Amsterdam (1981-2100)
<p>This dataset includes the processing results used to create the interactive climate service <a href="https://thermal-assessment.urban.tecnalia.dev/">Thermal Assessment Tool</a>. It provides frequency and severity of heatwaves under past, current and future climate conditions which allows to estimate the thermal behavior of regions and cities in Europe during episodes of extreme heat.</p> <p>A heatwave is typically defined as a “prolonged” period of “extremely high” temperature for a particular region or location. In REACHOUT, “prolonged” is defined by a period of two or more days and “extremely high” is determined per region when daily maximal temperature exceeds its threshold (95th percentile) and the daily minimum temperature exceeds its threshold (90th percentile). The percentiles were obtained considering the values of maximum and minimum temperatures of the region during the summer season of the baseline period of 1981 to 2010.</p> <p>To provide homogeneous data for the whole EU, the input variables used to generate this dataset come from the public, independent and authoritative <a href="https://climate.copernicus.eu/">Copernicus Climate Change Service</a> (C3S). For the observations the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-gridded-observations-europe?tab=overview">e-OBS</a> dataset is used and for the future projections the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/projections-cordex-domains-single-levels?tab=overview">EURO-CORDEX</a> dataset. The intermediate (<strong>RCP4.5</strong>) and very high (<strong>RCP8.5</strong>) emissions scenarios were considered. All the data was downloaded from the <a href="https://cds.climate.copernicus.eu/">Copernicus Climate Data Store</a> (CDS).</p> <p>The database is organized in three datasets:</p> <p>Regional_eobs_thresholds_Reachout.csv: contains the thresholds that were used to detect the heatwaves for each region. They were calculated considering the values of maximum and minimum temperatures during the summer season of the baseline period (1981-2010). The columns are:</p> <ul> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID or GISCO_ID.</li> <li><strong>tmax</strong>: daily maximum temperature threshold.</li> <li><strong>tmin</strong>: daily minimum temperature threshold.</li> </ul> <p>Historical_eobs_heatwaves_Reachout.csv: heatwaves of the historical period (1981-2021) for each region. The columns are:</p> <ul> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID or GISCO_ID.</li> <li><strong>start</strong>: first date of the heatwave.</li> <li><strong>tmax</strong>: maximum temperature reached during the heatwave.</li> <li><strong>intensity</strong>: the sum of the degrees of the maximum and minimum temperatures over their corresponding thresholds.</li> <li><strong>duration</strong>: duration of the heatwave.</li> </ul> <p>Future_and_baseline_eobs_heatwaves_Reachout.csv: ensemble future projections of heatwaves. The columns are:</p> <ul> <li><strong>hazard_level</strong>: it can be a warning, an alert or an alarm.</li> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID or GISCO_ID.</li> <li><strong>experiment</strong>: emission scenario. It can be baseline, rcp-4-5 or rcp-8-5.</li> <li><strong>period</strong>: it can be 1981-2010 for the baseline or 2011-2040, 2021-2050, 2031-2060, 2041-2070, 2051-2080, 2061-2090 or 2071-2100 for the future.</li> <li><strong>decade_frequency</strong>: decade mean frequency. In the case of the future this is the ensemble of the models.</li> <li><strong>decade_frequency_best</strong>: only applicable to the future. It determines the best projection among the models.</li> <li><strong>decade_frequency_worst</strong>: only applicable to the future. It determines the worst projection among the models.</li> <li><strong>year_days</strong>: average annual days.</li> <li><strong>year_tmax_intensity</strong>: the average annual degrees of the maximum temperature over its corresponding threshold.</li> <li><strong>year_tmin_intensity</strong>: the average annual degrees of the minimum temperature over its corresponding threshold.</li> </ul>
Heatwaves characterization derived from reanalysis and climate projections to assess thermal behavior of regions in Europe (1981-2100)
<p>This dataset provides frequency and severity of heatwaves under past, current and future climate conditions which allows to estimate the thermal behavior of regions in Europe during episodes of extreme heat.</p> <p>A heatwave is typically defined as a “prolonged” period of “extremely high” temperature for a particular region or location. In REACHOUT, “prolonged” is defined by a period of two or more days and “extremely high” is determined per region when daily maximal temperature exceeds its threshold (95th percentile) and the daily minimum temperature exceeds its threshold (90th percentile). The percentiles were obtained considering the values of maximum and minimum temperatures of the region during the summer season of the baseline period of 1981 to 2010.</p> <p>To provide homogeneous data for the whole EU, the input variables used to generate this dataset come from the public, independent and authoritative <a href="https://climate.copernicus.eu/">Copernicus Climate Change Service</a> (C3S). For the reanalysis the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview">ERA5-Land</a> dataset is used and for the future projections the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/projections-cordex-domains-single-levels?tab=overview">EURO-CORDEX</a> dataset. The intermediate (<strong>RCP4.5</strong>) and very high (<strong>RCP8.5</strong>) emissions scenarios were considered. All the data was downloaded from the <a href="https://cds.climate.copernicus.eu/">Copernicus Climate Data Store</a> (CDS).</p> <p>The database is organized in three datasets:</p> <p>Regional_era5land_thresholds_Europe.csv: contains the thresholds that were used to detect the heatwaves for each region. They were calculated considering the values of maximum and minimum temperatures during the summer season of the baseline period (1981-2010). The columns are:</p> <ul> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID.</li> <li><strong>tmax</strong>: daily maximum temperature threshold.</li> <li><strong>tmin</strong>: daily minimum temperature threshold.</li> </ul> <p>Historical_era5land_heatwaves_Europe.csv: heatwaves of the historical period (1981-2021) for each region. The columns are:</p> <ul> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID.</li> <li><strong>start</strong>: first date of the heatwave.</li> <li><strong>tmax</strong>: maximum temperature reached during the heatwave.</li> <li><strong>intensity</strong>: the sum of the degrees of the maximum and minimum temperatures over their corresponding thresholds.</li> <li><strong>duration</strong>: duration of the heatwave.</li> </ul> <p>Future_and_baseline_era5land_heatwaves_Europe.csv: ensemble future projections of heatwaves. The columns are:</p> <ul> <li><strong>hazard_level</strong>: it can be a warning, an alert or an alarm.</li> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID.</li> <li><strong>experiment</strong>: emission scenario. It can be baseline, rcp-4-5 or rcp-8-5.</li> <li><strong>period</strong>: it can be 1981-2010 for the baseline or 2011-2040, 2021-2050, 2031-2060, 2041-2070, 2051-2080, 2061-2090 or 2071-2100 for the future.</li> <li><strong>decade_frequency</strong>: decade mean frequency. In the case of the future this is the ensemble of the models.</li> <li><strong>decade_frequency_best</strong>: only applicable to the future. It determines the best projection among the models.</li> <li><strong>decade_frequency_worst</strong>: only applicable to the future. It determines the worst projection among the models.</li> <li><strong>year_days</strong>: average annual days.</li> <li><strong>year_tmax_intensity</strong>: the average annual degrees of the maximum temperature over its corresponding threshold.</li> <li><strong>year_tmin_intensity</strong>: the average annual degrees of the minimum temperature over its corresponding threshold.</li> </ul> <p> </p>
Heatwaves characterization derived from observations and climate projections to assess thermal behavior of regions in Europe (1981-2100)
<p>This dataset provides frequency and severity of heatwaves under past, current and future climate conditions which allows to estimate the thermal behavior of regions in Europe during episodes of extreme heat.</p> <p>A heatwave is typically defined as a “prolonged” period of “extremely high” temperature for a particular region or location. In REACHOUT, “prolonged” is defined by a period of two or more days and “extremely high” is determined per region when daily maximal temperature exceeds its threshold (95th percentile) and the daily minimum temperature exceeds its threshold (90th percentile). The percentiles were obtained considering the values of maximum and minimum temperatures of the region during the summer season of the baseline period of 1981 to 2010.</p> <p>To provide homogeneous data for the whole EU, the input variables used to generate this dataset come from the public, independent and authoritative <a href="https://climate.copernicus.eu/">Copernicus Climate Change Service</a> (C3S). For the observations the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-gridded-observations-europe?tab=overview">e-OBS</a> dataset is used and for the future projections the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/projections-cordex-domains-single-levels?tab=overview">EURO-CORDEX</a> dataset. The intermediate (<strong>RCP4.5</strong>) and very high (<strong>RCP8.5</strong>) emissions scenarios were considered. All the data was downloaded from the <a href="https://cds.climate.copernicus.eu/">Copernicus Climate Data Store</a> (CDS).</p> <p>The database is organized in three datasets:</p> <p>Regional_eobs_thresholds_Europe.csv: contains the thresholds that were used to detect the heatwaves for each region. They were calculated considering the values of maximum and minimum temperatures during the summer season of the baseline period (1981-2010). The columns are:</p> <ul> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID.</li> <li><strong>tmax</strong>: daily maximum temperature threshold.</li> <li><strong>tmin</strong>: daily minimum temperature threshold.</li> </ul> <p>Historical_eobs_heatwaves_Europe.csv: heatwaves of the historical period (1981-2021) for each region. The columns are:</p> <ul> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID.</li> <li><strong>start</strong>: first date of the heatwave.</li> <li><strong>tmax</strong>: maximum temperature reached during the heatwave.</li> <li><strong>intensity</strong>: the sum of the degrees of the maximum and minimum temperatures over their corresponding thresholds.</li> <li><strong>duration</strong>: duration of the heatwave.</li> </ul> <p>Future_and_baseline_eobs_heatwaves_Europe.csv: ensemble future projections of heatwaves. The columns are:</p> <ul> <li><strong>hazard_level</strong>: it can be a warning, an alert or an alarm.</li> <li><strong>region</strong>: unique identifier of the corresponding EUROSTAT NUTS_ID.</li> <li><strong>experiment</strong>: emission scenario. It can be baseline, rcp-4-5 or rcp-8-5.</li> <li><strong>period</strong>: it can be 1981-2010 for the baseline or 2011-2040, 2021-2050, 2031-2060, 2041-2070, 2051-2080, 2061-2090 or 2071-2100 for the future.</li> <li><strong>decade_frequency</strong>: decade mean frequency. In the case of the future this is the ensemble of the models.</li> <li><strong>decade_frequency_best</strong>: only applicable to the future. It determines the best projection among the models.</li> <li><strong>decade_frequency_worst</strong>: only applicable to the future. It determines the worst projection among the models.</li> <li><strong>year_days</strong>: average annual days.</li> <li><strong>year_tmax_intensity</strong>: the average annual degrees of the maximum temperature over its corresponding threshold.</li> <li><strong>year_tmin_intensity</strong>: the average annual degrees of the minimum temperature over its corresponding threshold.</li> </ul> <p> </p>
ScienceDex guides
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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.