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3 results for “heat metrics”
Supplementary material for the article "High-resolution projections of ambient heat for major European cities using different heat metrics"
<p>This dataset contains the data displayed in the figures or the article "High-resolution projections of ambient heat for major European cities using different heat metrics".</p> <p>The different files contain:</p> <ul> <li>Data_Fig1_DeltaTXx_EURO-CORDEX_1981-2010_to_3K-European-warming_RCP85.nc:<br> Change of yearly maximum temperature in Europe between 1981-2010 and 3 °C European warming relative to 1981-2010.</li> <li>Data_Fig2_timeseries-GSAT-ESAT_EURO-CORDEX_CMIP5_CMIP6_1971-2100_RCP85_SSP585.xlsx:<br> Time series of global mean surface air temperature (GSAT) for CMIP5 and CMIP6 models, and for European mean surface air temperature (ESAT) for EURO-CORDEX, CMIP5, and CMIP6 models for the period 1971-2100.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_E-OBS_1981-2010.xlsx:<br> Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for E-OBS for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_ERA5-Land_1981-2010.xlsx:<br> Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for ERA5-Land for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_EURO-CORDEX_1981-2010.xlsx:<br> Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for the EURO-CORDEX models for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_weather-stations_1981-2010.xlsx:<br> Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for GSOD and ECA&D stations for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig4_TX-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx:<br> Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models.</li> <li>Data_Fig5_Contribution-of-explanatory-variables-to-total-explained-variance.xlsx:<br> Contribution of different explanatory variables (climate and location factors) to the total explained variance of spatial patterns of heat metrics.</li> <li>Data_Fig6_TN-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx:<br> Nighttime heat metrics for the investigated cities: HWMId-TN at 3 °C European warming relative to 1981-2010, TN exceedances above 20 °C at 3 °C European warming relative to 1981-2010, and TNx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models.</li> <li>Data_Fig7_TX-ambient-heat_CMIP5_3K-European-warming.xlsx:<br> Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP5 models.</li> <li>Data_Fig7_TX-ambient-heat_CMIP6_3K-European-warming.xlsx:<br> Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP6 models.</li> <li>Data_Fig8_GCM-RCM-matrix_ambient-heat_3K-European-warming.xlsx:<br> GCM-RCM matrices for the three heat metrics.</li> </ul>
Prioritizing equity in urban heat reduction: Beyond cooling as a metric
<p>Archived simulations for five heat wave events happened over Houston from 2017 - 2019 with different urban overheating mitigation strategies. </p>
A global high-resolution and bias-corrected dataset of CMIP6 projected heat stress metrics
<p><strong>Motivation</strong></p> <p>Increasing heat stress due to climate change poses significant risks to human health and can lead to widespread social and economic consequences. Evaluating these impacts requires reliable datasets of heat stress projections. </p> <p><strong>Data Record</strong></p> <p><strong>CMIP6</strong></p> <p>We present a global dataset projecting future dry-bulb, wet-bulb, and wet-bulb globe temperatures under 1-4°C global warming scenarios (at 0.5°C intervals) relative to the preindustrial era, using outputs from 16 CMIP6 global climate models (GCMs) (Table 1). All variables were retrieved from the historical and SSP585 scenarios which were selected to maximize the warming signal.</p> <p>Wet-bulb and wet-bulb globe temperature are calculated using the Davies-Jones[1] and Liljegren[2] approach respectively.</p> <p>The dataset was bias-corrected against ERA5 reanalysis by incorporating the GCM-simulated climate change signal onto the ERA5 baseline (1950-1976) at a 3-hourly frequency. It therefore includes a 27-year sample for each GCM under each warming target.</p> <p>The data is provided at a fine spatial resolution of 0.25° x 0.25° and a temporal resolution of 3 hours, and is stored in a self-describing NetCDF format. Filenames follow the pattern "VAR_bias_corrected_3hr_GCM_XC_yyyy.nc", where:</p> <ul> <li> <p>"VAR" represents the variable (Ta, Tw, WBGT for dry-bulb, wet-bulb, and wet-bulb globe temperature, respectively),</p> </li> <li> <p>"GCM" denotes the CMIP6 GCM name,</p> </li> <li> <p>"X" indicates the warming target compared to the preindustrial period,</p> </li> <li> <p>"yyyy" represents the year index (0001-0027) of the 27-year sample</p> </li> </ul> <p><strong>Table 1 </strong>CMIP6 GCMs used for generating the dataset for Ta, Tw and WBGT.</p> <div> <table> <tbody> <tr> <td> <p>GCM</p> </td> <td> <p>Realization</p> </td> <td> <p>GCM grid spacing</p> </td> <td> <p>Ta</p> </td> <td> <p>Tw</p> </td> <td> <p>WBGT</p> </td> </tr> <tr> <td> <p>ACCESS-CM2</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.25ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>BCC-CSM2-MR</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.1ox1.125o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CanESM5</p> </td> <td> <p>r1i1p2f1</p> </td> <td> <p>2.8ox2.8o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CMCC-CM2-SR5</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.94ox1.25o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CMCC-ESM2</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.94ox1.25o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CNRM-CM6-1</p> </td> <td> <p>r1i1p1f2</p> </td> <td> <p>1.4ox1.4o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> </td> </tr> <tr> <td> <p>EC-Earth3</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.7ox0.7o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>GFDL-ESM4</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.0ox1.25o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>HadGEM3-GC31-LL</p> </td> <td> <p>r1i1p1f3</p> </td> <td> <p>1.25ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>HadGEM3-GC31-MM</p> </td> <td> <p>r1i1p1f3</p> </td> <td> <p>0.55ox0.83o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>KACE-1-0-G</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.25ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>KIOST-ESM</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.9ox1.9o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MIROC-ES2L</p> </td> <td> <p>r1i1p1f2</p> </td> <td> <p>2.8ox2.8o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MIROC6</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.4ox1.4o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MPI-ESM1-2-HR</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.93ox0.93o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MPI-ESM1-2-LR</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.85ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> </tbody> </table> </div> <p><strong>ERA5</strong></p> <p>We also provide hourly Tw and WBGT derived from ERA5 reanalysis during 1950-2023 to enable analyses of heat stress changes from historical period to a warmer climate.</p> <p><strong> </strong></p> <p><strong>Data Access</strong></p> <p>An inventory of the dataset is available in this repository. The complete dataset, approximately 57 TB in size, is freely accessible via Purdue Fortress' long-term archive through Globus. The bias-corrected CMIP6 dataset is available at <a href="https://transfer.rcac.purdue.edu/file-manager?origin_id=6538f53a-1ea7-4c13-a0cf-10478190b901&origin_path=%2F">Globus Link1</a>, and the ERA5 dataset is available at <a href="https://transfer.rcac.purdue.edu/file-manager?destination_id=63242aea-d3e0-4aa4-9372-0e19dd0c6539&destination_path=%2F">Globus Link2</a>. After clicking the link, users may be prompted to log in with a Purdue institutional Globus account. You can switch to your institutional account, or log in via a personal Globus ID, Gmail, GitHub handle, or ORCID ID. Alternatively, the dataset can be accessed by searching for the universally unique identifier (UUID)—"6538f53a-1ea7-4c13-a0cf-10478190b901" for CMIP6, and “63242aea-d3e0-4aa4-9372-0e19dd0c6539” for ERA5 dataset—in Globus.</p> <p><strong>Dataset Validation</strong></p> <p>We validate the bias-correction method and show that it significantly enhances the GCMs' accuracy in reproducing both the annual average and the full range of quantiles for all metrics within an ERA5 reference climate state. This dataset is expected to support future research on projected changes in mean and extreme heat stress and the assessment of related health and socio-economic impacts.</p> <p>For a detailed introduction to the dataset and its validation, please refer to our data descriptor currently under review at Scientific Data. We will update this information upon publication.</p> <p><strong><br><br><br></strong></p>
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