{"id":4541,"date":"2024-07-01T16:50:38","date_gmt":"2024-07-01T11:20:38","guid":{"rendered":"https:\/\/newsdata.io\/blog\/?p=4541"},"modified":"2024-07-04T15:34:55","modified_gmt":"2024-07-04T10:04:55","slug":"heat-wave-news-datasets","status":"publish","type":"post","link":"https:\/\/newsdata.io\/blog\/heat-wave-news-datasets\/","title":{"rendered":"Heat Wave News Datasets: A Mega Compilation"},"content":{"rendered":"[vc_row type=&#8221;in_container&#8221; full_screen_row_position=&#8221;middle&#8221; column_margin=&#8221;default&#8221; column_direction=&#8221;default&#8221; column_direction_tablet=&#8221;default&#8221; column_direction_phone=&#8221;default&#8221; scene_position=&#8221;center&#8221; text_color=&#8221;dark&#8221; text_align=&#8221;left&#8221; row_border_radius=&#8221;none&#8221; row_border_radius_applies=&#8221;bg&#8221; overflow=&#8221;visible&#8221; overlay_strength=&#8221;0.3&#8243; gradient_direction=&#8221;left_to_right&#8221; shape_divider_position=&#8221;bottom&#8221; bg_image_animation=&#8221;none&#8221;][vc_column column_padding=&#8221;no-extra-padding&#8221; column_padding_tablet=&#8221;inherit&#8221; column_padding_phone=&#8221;inherit&#8221; column_padding_position=&#8221;all&#8221; column_element_direction_desktop=&#8221;default&#8221; column_element_spacing=&#8221;default&#8221; desktop_text_alignment=&#8221;default&#8221; tablet_text_alignment=&#8221;default&#8221; phone_text_alignment=&#8221;default&#8221; background_color_opacity=&#8221;1&#8243; background_hover_color_opacity=&#8221;1&#8243; column_backdrop_filter=&#8221;none&#8221; column_shadow=&#8221;none&#8221; column_border_radius=&#8221;none&#8221; column_link_target=&#8221;_self&#8221; column_position=&#8221;default&#8221; gradient_direction=&#8221;left_to_right&#8221; overlay_strength=&#8221;0.3&#8243; width=&#8221;1\/4&#8243; tablet_width_inherit=&#8221;default&#8221; animation_type=&#8221;default&#8221; bg_image_animation=&#8221;none&#8221; border_type=&#8221;simple&#8221; column_border_width=&#8221;none&#8221; column_border_style=&#8221;solid&#8221; column_padding_type=&#8221;default&#8221; gradient_type=&#8221;default&#8221; offset=&#8221;vc_hidden-sm vc_hidden-xs&#8221;][\/vc_column][vc_column column_padding=&#8221;no-extra-padding&#8221; column_padding_tablet=&#8221;inherit&#8221; column_padding_phone=&#8221;inherit&#8221; column_padding_position=&#8221;all&#8221; column_element_direction_desktop=&#8221;default&#8221; column_element_spacing=&#8221;default&#8221; desktop_text_alignment=&#8221;default&#8221; tablet_text_alignment=&#8221;default&#8221; phone_text_alignment=&#8221;default&#8221; background_color_opacity=&#8221;1&#8243; background_hover_color_opacity=&#8221;1&#8243; column_backdrop_filter=&#8221;none&#8221; column_shadow=&#8221;none&#8221; column_border_radius=&#8221;none&#8221; column_link_target=&#8221;_self&#8221; column_position=&#8221;default&#8221; el_class=&#8221;text_block_wrapper&#8221; gradient_direction=&#8221;left_to_right&#8221; overlay_strength=&#8221;0.3&#8243; width=&#8221;3\/4&#8243; tablet_width_inherit=&#8221;default&#8221; animation_type=&#8221;default&#8221; bg_image_animation=&#8221;none&#8221; border_type=&#8221;simple&#8221; column_border_width=&#8221;none&#8221; column_border_style=&#8221;solid&#8221; column_padding_type=&#8221;default&#8221; gradient_type=&#8221;default&#8221; offset=&#8221;vc_col-lg-9 vc_col-md-12&#8243;][image_with_animation image_url=&#8221;4543&#8243; image_size=&#8221;full&#8221; animation_type=&#8221;entrance&#8221; animation=&#8221;None&#8221; animation_movement_type=&#8221;transform_y&#8221; hover_animation=&#8221;none&#8221; alignment=&#8221;&#8221; border_radius=&#8221;10px&#8221; box_shadow=&#8221;small_depth&#8221; image_loading=&#8221;default&#8221; max_width=&#8221;100%&#8221; max_width_mobile=&#8221;default&#8221;][vc_column_text]Welcome back to the <b>\u2018Dataset of the Week\u2019<\/b> blog series, where we bring you a mega compilation of free, available datasets on trending topics. The topic we chose for this week is <b>\u2018Heat Wave\u2019<\/b>.<\/p>\n<p>You can also read previous blogs in the <a href=\"https:\/\/newsdata.io\/blog\/mega-compilation-news-dataset\/\">\u2018Dataset of the Week\u2019<\/a> series on the following blogs:<\/p>\n<ul>\n<li><a href=\"https:\/\/newsdata.io\/blog\/russia-ukraine-war-news-datasets\/\">Russia-Ukraine War News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/israel-hamas-war-datasets\/\">Israel-Hamas News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/global-inflation-datasets\/\">Global Inflation Dataset<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/us-elections-news-datasets\/\">US Elections News Dataset<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/india-election-2024-news-datasets\/\">India Elections 2024 News Dataset<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/fifa-worldcup-2023-datasets-a-mega-compilation\/\">FIFA World Cup News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/infrastructure-development-news-dataset\/\">Infrastructure Development News Dataset<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/carbon-footprint-news-datasets\/\">Carbon Footprints News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/indian-stock-market-news-dataset\/\">Indian Stock Market News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/space-race-news-datasets\/\">Space Race News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/climate-crisis-news-datasets-a-mega-compilation\/\">Climate Crisis News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/oil-trading-news-datasets\/\">Oil Trading News Datasets<\/a><\/li>\n<li><a href=\"https:\/\/newsdata.io\/blog\/ai-progress-news-datasets\/\">AI Progress News Datasets<\/a><\/li>\n<\/ul>\n[\/vc_column_text][vc_column_text]\n<h2><b>Heat Wave<\/b><\/h2>\n[\/vc_column_text][vc_column_text]Heat waves refer to a period of abnormally hot weather that affects the economy as a whole. Such conditions not only disrupt mundane activities but also impact agricultural and industrial processes as well as cause damage to the infrastructure. In the past few years, there have been growing instances of heat waves around the world, but 2024 saw the peak of heat waves.[\/vc_column_text][vc_column_text]\n<h2><b>Dataset Customization<\/b><\/h2>\n[\/vc_column_text][vc_column_text]Despite ample websites and data portals providing you with datasets related to this, you can\u2019t always get a dataset that meets all the required criteria. For scenarios like this, there are providers like <b>Newsdata.io<\/b> and <b>Datarade<\/b>, who are leading providers of customized datasets.[\/vc_column_text][vc_column_text]You can request customized datasets on Heat Wave on Newsdata.io by following the given steps:<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li>\n<h3>Search for Data<\/h3>\n<\/li>\n<\/ul>\n<p>You can now look for a number of articles on the topic of your choice and fetch data using the search bar, as shown below.<\/p>\n\n<!-- iframe plugin v.5.0 wordpress.org\/plugins\/iframe\/ -->\n<iframe loading=\"lazy\" src=\"https:\/\/newsdata.io\/single\/search\" height=\"150\" width=\"100%\" scrolling=\"yes\" class=\"iframe-class\" frameborder=\"0\"><\/iframe>\n\n<ul>\n<li>\n<h3>Request News Data<\/h3>\n<\/li>\n<\/ul>\n<p>You can request data by choosing the\u00a0 <a href=\"https:\/\/newsdata.io\/historical-news-download#request-form\">\u2018<b>Request News Data<\/b>\u2019<\/a> option. This will then redirect you to a request form, as shown below.<\/p>\n<p><b><img loading=\"lazy\" decoding=\"async\" class=\"https:\/\/newsdata.io\/historical-news-download#request-form alignnone wp-image-3471 size-full\" src=\"https:\/\/i0.wp.com\/newsdata.io\/blog\/wp-content\/uploads\/2024\/03\/Screenshot-2024-03-22-104425-1.png?resize=771%2C811&#038;ssl=1\" alt=\"Historical Data Request Form\" width=\"771\" height=\"811\" srcset=\"https:\/\/i0.wp.com\/newsdata.io\/blog\/wp-content\/uploads\/2024\/03\/Screenshot-2024-03-22-104425-1.png?w=771&amp;ssl=1 771w, https:\/\/i0.wp.com\/newsdata.io\/blog\/wp-content\/uploads\/2024\/03\/Screenshot-2024-03-22-104425-1.png?resize=285%2C300&amp;ssl=1 285w, https:\/\/i0.wp.com\/newsdata.io\/blog\/wp-content\/uploads\/2024\/03\/Screenshot-2024-03-22-104425-1.png?resize=768%2C808&amp;ssl=1 768w\" sizes=\"(max-width: 771px) 100vw, 771px\" data-recalc-dims=\"1\" \/>NOTE: <\/b>You can choose the <a href=\"https:\/\/newsdata.io\/historical-news-download#request-form\"><b>\u2018Download Sample\u2019<\/b><\/a> option if you want an overview of how the data will be segregated into datasets.[\/vc_column_text][vc_column_text]\n<h2><b>List of available datasets<\/b><\/h2>\n[\/vc_column_text][vc_column_text]<strong>1. Number of heat wave days in India: 2010-2022<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Erick Burgue\u00f1o Salas<br \/>\n<strong>Publish Date:<\/strong> Jun 28, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1006838\/india-number-of-heat-waves\/\">https:\/\/www.statista.com\/statistics\/1006838\/india-number-of-heat-waves\/<\/a><br \/>\n<strong>Description:<\/strong> About 172 heat wave days were recorded across India in 2022, a significant increase compared to the previous year. In recent years, these events have been more intense in the country&#8217;s northern regions, coinciding with droughts, water shortages, and an already inadequate infrastructure.<\/p>\n<p><strong>2. Heat Waves: Year-wise Number of Deaths in India due to Heat Waves, as recorded by NDMA<\/strong><br \/>\n<strong>Source:<\/strong> Dataful<br \/>\n<strong>Author:<\/strong> National Disaster Management Authority<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/dataful.in\/datasets\/451\/\">https:\/\/dataful.in\/datasets\/451\/<\/a><br \/>\n<strong>Description:<\/strong> The dataset contains year-wise compiled data on the number of deaths that have happened in India due to heat waves, as recorded by the National Disaster Management Authority (NDMA).<\/p>\n<p><strong>3. A dataset of heatwaves in Xinjiang province during 1961\u20132019<\/strong><br \/>\n<strong>Source:<\/strong> Science Data Bank<br \/>\n<strong>Publish Date:<\/strong> October 21, 2021<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.scidb.cn\/en\/detail?dataSetId=37a77850dd8b49c19ac653aefb53e4be#detail_start\">https:\/\/www.scidb.cn\/en\/detail?dataSetId=37a77850dd8b49c19ac653aefb53e4be#detail_start<\/a><br \/>\n<strong>Description:<\/strong> The quality of the dataset was assessed based on the existing literature. The results indicate that the dataset has high credibility and can provide data support for heatwave research and risk assessment in Xinjiang.<\/p>\n<p><strong>4. Heat waves and cold spells in Europe derived from climate projections<\/strong><br \/>\n<strong>Source:<\/strong> Climate.copernicus.eu<br \/>\n<strong>Author:<\/strong> European Commission<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/cds.climate.copernicus.eu\/cdsapp#!\/dataset\/sis-heat-and-cold-spells?tab=overview\">https:\/\/cds.climate.copernicus.eu\/cdsapp#!\/dataset\/sis-heat-and-cold-spells?tab=overview<\/a><br \/>\n<strong>Description:<\/strong> The dataset contains the number of hot and cold spell days using different European-wide and national\/regional definitions developed within the C3S European Health Service.<\/p>\n<p><strong>5. Projected number of extreme heatwaves (2068\u20132100; RCP 8.5; number in 33 years), Jul. 2015<\/strong><br \/>\n<strong>Source:<\/strong> EEA.Europa.EU<br \/>\n<strong>Author:<\/strong> EEA Geospatial Data Catalog<br \/>\n<strong>Publish Date:<\/strong> June 23, 2015<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/sdi.eea.europa.eu\/catalogue\/srv\/api\/records\/a18bcf0e-14bc-43fc-adaf-8fd4f72efbd0\">https:\/\/sdi.eea.europa.eu\/catalogue\/srv\/api\/records\/a18bcf0e-14bc-43fc-adaf-8fd4f72efbd0<\/a><br \/>\n<strong>Description:<\/strong> The gridded dataset presents the median of the projected number of extreme heatwaves in the future (2068\u20132100) in Europe, following the Representative Concentration Pathways (RCP) 8.5 scenario. The dataset is one of the multimodel ensembles used to project the future occurrence and severity of heat waves under different RCPs, which were adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5).<\/p>\n<p><strong>6. Southern Europe and Western Asia Marine Heat Waves (SEWA-MHWs): a dataset based on macro events<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Authors:<\/strong> Giulia Bonino, Simona Masina, Giuliano Galimberti, Mateo Moretti<br \/>\n<strong>Publish Date:<\/strong> October 6, 2022<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/zenodo.org\/records\/7540325\">https:\/\/zenodo.org\/records\/7540325<\/a><br \/>\n<strong>Description:<\/strong> This repository contains the SEWA-MHWs dataset, which consists of daily fields of marine heatwaves (MHWs) macroevents, daily fields of MHWs characteristics, and daily fields of relevant atmospheric variables over Southern Europe and Western Asia. It also contains the codes to detect MHW macro events and their characteristics.<\/p>\n<p><strong>7. Southern Europe and Western Asia Marine Heat Waves (SEWA-MHWs): a dataset based on macro events<\/strong><br \/>\n<strong>Source:<\/strong> DataCite Commons<br \/>\n<strong>Authors:<\/strong> Giulia Bonino, Simona Masina, Giuliano Galimberti &amp; Matteo Moretti<br \/>\n<strong>Publish Date:<\/strong> 2022<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/commons.datacite.org\/doi.org\/10.5281\/zenodo.7540325\">https:\/\/commons.datacite.org\/doi.org\/10.5281\/zenodo.7540325<\/a><br \/>\n<strong>Description:<\/strong> This repository contains the SEWA-MHWs dataset, which consists of daily fields of marine heatwaves (MHWs) macroevents, daily fields of MHWs characteristics, and daily fields of relevant atmospheric variables over Southern Europe and Western Asia. It also contains the codes to detect MHW macro events and their characteristics.<\/p>\n<p><strong>8. Heat Wave Index in U.S. 1895\u20132020<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Bruna Alves<br \/>\n<strong>Publish Date:<\/strong> Feb 16, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1293872\/us-heat-wave-index\/\">https:\/\/www.statista.com\/statistics\/1293872\/us-heat-wave-index\/<\/a><br \/>\n<strong>Description:<\/strong> Based on the United States historical record, extended periods of very high temperatures were more frequent in the 1930s. In the United States, approximately 64 percent of the people lived in counties that experienced multiday heat waves in 2021.<\/p>\n<p><strong>9. A daily dataset of global marine heatwaves from 1982 to 2020<\/strong><br \/>\n<strong>Source:<\/strong> Science Data Bank<br \/>\n<strong>Author:<\/strong> Zhang Xiaojuan, Zheng Fei<br \/>\n<strong>Publish Date:<\/strong> June 15, 2021<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.scidb.cn\/en\/detail?dataSetId=43cbc3b870e545a2a16967782103b557\">https:\/\/www.scidb.cn\/en\/detail?dataSetId=43cbc3b870e545a2a16967782103b557<\/a><br \/>\n<strong>Description:<\/strong> A marine heatwave (MHW) is a prolonged high-temperature extreme event in the ocean that can cause devastating impacts on marine life and then have a serious impact on the climate system and the social economy.<\/p>\n<p><strong>10. Hottest summers in South Korea, 1973\u20132023, by heat wave days<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> L. Yoon<br \/>\n<strong>Publish Date:<\/strong> Apr 10, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/887291\/south-korea-hottest-summers-by-heat-wave-period\/\">https:\/\/www.statista.com\/statistics\/887291\/south-korea-hottest-summers-by-heat-wave-period\/<\/a><br \/>\n<strong>Description:<\/strong> In 2018, South Korea recorded its hottest summer since 1973, with 31 heat-wave days. Heatwaves with maximum temperatures above 33 degrees Celsius usually occur after the rainy season in the summer. In recent years, not only the frequency of heatwaves has increased, but also their intensity.[\/vc_column_text][vc_column_text]<strong>11. Simulations of urban heat island effect in Paris Region during various types of heatwaves and in different adaptation scenarios<\/strong><br \/>\n<strong>Source:<\/strong> Data Subak<br \/>\n<strong>Publish Date:<\/strong> November 1, 2022<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/data.subak.org\/dataset\/simulations-of-urban-heat-island-effect-in-paris-region-during-various-types-of-heatwaves-and-i\">https:\/\/data.subak.org\/dataset\/simulations-of-urban-heat-island-effect-in-paris-region-during-various-types-of-heatwaves-and-i<\/a><br \/>\n<strong>Description:<\/strong> These data present air temperature in the shade, 2 m above ground in the Paris Region (projection: RGF93\/Lambert 93, EPSG: 2154) at different times of the day, for various heat wave conditions, and in different prospective scenarios for the built-up evolution and adaptation action implementations.<\/p>\n<p><strong>12. Simulations of urban heat island effect in Paris Region during various types of heatwaves and in different adaptation scenarios<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Author:<\/strong> Lemonsu Aude, Virgui Vincent<br \/>\n<strong>Publish Date:<\/strong> March 28, 2019<br \/>\n<strong>Link:<\/strong> https:\/\/zenodo.org\/records\/2613879<br \/>\n<strong>Description:<\/strong> These data present air temperature in the shade, 2 m above ground in the Paris Region (projection: RGF93\/Lambert 93, EPSG: 2154) at different times of the day, for various heat wave conditions, and in different prospective scenarios for the built-up evolution and adaptation action implementations.<\/p>\n<p><strong>13. Historical Heatwaves in Australia<\/strong><br \/>\n<strong>Source:<\/strong> TERN Geospatial Catalogue<br \/>\n<strong>Author:<\/strong> Terrestrial Ecosystem Research Network<br \/>\n<strong>Publish Date:<\/strong> August 20, 2020<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/geonetwork.tern.org.au\/geonetwork\/srv\/api\/records\/be6dad2c-584c-4d5e-b557-8530526241b5\">https:\/\/geonetwork.tern.org.au\/geonetwork\/srv\/api\/records\/be6dad2c-584c-4d5e-b557-8530526241b5<\/a><br \/>\n<strong>Description:<\/strong> This dataset provides a time series of heatwave characteristics such as peak temperature, number of events, frequency, and duration from 1950 to 2016 in Australia. The analyses were based on daily minimum and maximum temperatures obtained from the Australian Water Availability Project (AWAP).<\/p>\n<p><strong>14. Gap-filling Satellite Land Surface Temperature Over Heatwave Periods with Machine Learning<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Author:<\/strong> Buo, Isaac, Sagris, Valentina, Jaagus, Jaak<br \/>\n<strong>Publish Date:<\/strong> March 10, 2021<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/zenodo.org\/records\/4593208\">https:\/\/zenodo.org\/records\/4593208<\/a><br \/>\n<strong>Description:<\/strong> This study validates machine learning as a suitable tool for filling gaps in satellite LST. In addition, we acknowledge that while time is an important factor in predicting LST, additional information on vegetation can improve the predictions of a model.<\/p>\n<p><strong>15. Number of heat wave episodes in France in 2005\u20132018<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Statista Research Department<br \/>\n<strong>Publish Date:<\/strong> Nov 13, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1040616\/number-of-episodes-of-heat-wave-france\/\">https:\/\/www.statista.com\/statistics\/1040616\/number-of-episodes-of-heat-wave-france\/<\/a><br \/>\n<strong>Description:<\/strong> This bar chart shows the number of heat wave episodes in France from 2004 to 2018. It displays that 2016 and 2017 were the years with the highest number of heat wave episodes since 2004. There have been four heat wave episodes during these two years.<\/p>\n<p><strong>16. Number of deaths due to heat waves across India in 2008\u20132021<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Erick Burgue\u00f1o Salas<br \/>\n<strong>Publish Date:<\/strong> Nov 20, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1006983\/india-deaths-due-to-heat-waves\/\">https:\/\/www.statista.com\/statistics\/1006983\/india-deaths-due-to-heat-waves\/<\/a><br \/>\n<strong>Description:<\/strong> In 2021, no deaths were caused due to heat waves in India. This was a significant decrease from the previous year&#8217;s number of 27. The highest number of deaths was recorded in 2015, when over two thousand people died due to heat waves across the nation.<\/p>\n<p><strong>17. Climate change worry, personal experience of extreme rainfall and heatwaves, and attribution to climate change<\/strong><br \/>\n<strong>Source:<\/strong> DataCite Commons<br \/>\n<strong>Authors:<\/strong> Lucy Richardson, Tahereh Alinejadtabrizi, Genevieve Evans, Jane Nguyen, Jess Mountain, Francine Machin, Jagadish Thakare, and Peter D. Howe<br \/>\n<strong>Publish Date:<\/strong> 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/commons.datacite.org\/doi.org\/10.26180\/24257308.v1\">https:\/\/commons.datacite.org\/doi.org\/10.26180\/24257308.v1<\/a><br \/>\n<strong>Description:<\/strong> This dataset was used in a study to test the relationships between personal experiences of climate change and worry, using both objective exposure and subjective experience data relating to extreme heatwaves and rainfall in Australia.<\/p>\n<p><strong>18. Heatwave characterization derived from observations and climate projections to assess thermal behavior of regions in Europe<\/strong><br \/>\n<strong>Source:<\/strong> NIAID Data Ecosystem<br \/>\n<strong>Author:<\/strong> Joshua Lizundia-Loiola, Nieves Pena Cerezo<br \/>\n<strong>Publish Date:<\/strong> June 12, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/data.niaid.nih.gov\/resources?id=ZENODO_8031517\">https:\/\/data.niaid.nih.gov\/resources?id=ZENODO_8031517<\/a><br \/>\n<strong>Description:<\/strong> This dataset provides the frequency and severity of heatwaves under past, current, and future climate conditions, which allows for the estimation of the thermal behavior of regions in Europe during episodes of extreme heat.<\/p>\n<p><strong>19. Dataset for &#8220;An Analytical Heat Wave Definition Based on the Impact on Buildings and Occupants&#8221;<\/strong><br \/>\n<strong>Source:<\/strong> University of Bath<br \/>\n<strong>Authors:<\/strong> Alfonso Ramallo-Gonz\u00e1lez, Sukumar Natarajan, David Coley, Matt Eames, and Daniel Fosas<br \/>\n<strong>Publish Date:<\/strong> March 2020<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/researchdata.bath.ac.uk\/775\/\">https:\/\/researchdata.bath.ac.uk\/775\/<\/a><br \/>\n<strong>Description:<\/strong> Several data sets are included in this deposit to aid the use of the method in the paper and the data we have produced. This includes some data on the real homes used in the paper as well as the EnergyPlus input data files (IDF) used in the simulation.<\/p>\n<p><strong>20. Exposure to heat waves in U.S. 2016\u20132021<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Bruna Alves<br \/>\n<strong>Publish Date:<\/strong> Feb 16, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1264726\/exposure-to-heat-waves-us\/\">https:\/\/www.statista.com\/statistics\/1264726\/exposure-to-heat-waves-us\/<\/a><br \/>\n<strong>Description:<\/strong> In the United States, approximately 64 percent of the people lived in counties that experienced multiday heat waves in 2021. A heatwave is designated as two or more consecutive days when the daily minimum temperature in a particular area is higher than the 85th percentile of historical July and August temperatures.[\/vc_column_text][vc_column_text]<strong>21. Data supporting: Heatwaves, elevated temperatures, and a pesticide cause interactive effects on multi-trophic levels of a freshwater ecosystem<\/strong><br \/>\n<strong>Source:<\/strong> B2Find<br \/>\n<strong>Author:<\/strong> Data Archiving and Networked Services (DANS)<br \/>\n<strong>Publish Date:<\/strong> 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/b2find.dkrz.de\/dataset\/a06a7ac8-619a-53f5-921e-c841899c9229\">https:\/\/b2find.dkrz.de\/dataset\/a06a7ac8-619a-53f5-921e-c841899c9229<\/a><br \/>\n<strong>Description:<\/strong> The data derives from an indoor (micro-) cosm experiment in which the transportable temperature and heatwave control device (TENTACLE) was used to investigate the effects of two different temperature scenarios (i.e., elevated temperature and reoccurring heatwaves) in combination with the fungicide carbendazim.<\/p>\n<p><strong>22. Temporal dynamics of heatwaves are key drivers of sediment mixing by bioturbators<\/strong><br \/>\n<strong>Source:<\/strong> Dataverse Nioz<br \/>\n<strong>Author:<\/strong> Zhou, Zhengquan<br \/>\n<strong>Publish Date:<\/strong> 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/dataverse.nioz.nl\/dataset.xhtml?persistentId=doi:10.25850\/nioz\/7b.b.7d\">https:\/\/dataverse.nioz.nl\/dataset.xhtml?persistentId=doi:10.25850\/nioz\/7b.b.7d<\/a><br \/>\n<strong>Description:<\/strong> Present findings reveal that the impact of heatwaves on sediment bioturbation will strongly depend on the temporal dynamics of future heatwaves; bioturbation will be enhanced unless the heatwave duration exceeds species resistance and increases mortality. (2023-02-21).<\/p>\n<p><strong>23. Sectoral water use responses to droughts and heatwaves<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Author:<\/strong> Cardenas B., Gabriel A., Biekens, Marc F.P., Van Vliet, Michelle T.H.<br \/>\n<strong>Publish Date:<\/strong> July 6, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/zenodo.org\/records\/8122382\">https:\/\/zenodo.org\/records\/8122382<\/a><br \/>\n<strong>Description:<\/strong> These datasets enable the assessment of sectoral water use responses during droughts, heatwaves, and compound events at global, regional, and local scales. File names contain the spatial scale of the analysis, water dimension, water sector, and analysis period.<\/p>\n<p><strong>24. Experimental heatwaves compromise sperm function and cause transgenerational damage in a model insect<\/strong><br \/>\n<strong>Source:<\/strong> B2Find<br \/>\n<strong>Author:<\/strong> Sales, Kris; Vasudeva, Ramakrishnan; Dickinson, Matthew E.; Godwin, Joanne L.; Lumley, Alyson J.; Michalkzyk, Lukasz; Hebberecht, Laura; Thomas, Paul; Franco, Aldina; Gage, Matthew J.G.<br \/>\n<strong>Publish Date:<\/strong> 2018<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/b2find.dkrz.de\/dataset\/923127a3-9aec-57f4-b046-9857a0306210\">https:\/\/b2find.dkrz.de\/dataset\/923127a3-9aec-57f4-b046-9857a0306210<\/a><br \/>\n<strong>Description: <\/strong>Climate change is affecting biodiversity, but proximate drivers remain poorly understood. Here, we examine how experimental heatwaves impact reproduction in an insect system.<\/p>\n<p><strong>25. Experimental study on the impacts of heatwaves with different duration and frequency on the common starfish Asterias rubens<\/strong><br \/>\n<strong>Source:<\/strong> B2Find<br \/>\n<strong>Author:<\/strong> Wolf, Fabian ; Seebass, Katja<br \/>\n<strong>Publish Date:<\/strong> 2022<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/b2find.dkrz.de\/dataset\/c39be9bd-1da1-5148-aa76-0276d7b7154d\">https:\/\/b2find.dkrz.de\/dataset\/c39be9bd-1da1-5148-aa76-0276d7b7154d<\/a><br \/>\n<strong>Description:<\/strong> These measurements were taken at the start of the experiment, right before the heatwaves started, before the present-day heatwave started to decline, before the extended heatwave started to decline, and at the end of the experiment.<\/p>\n<p><strong>26. The Dynamical Linkage of Atmospheric Blocking to Drought, Heatwaves and Urban Heat Island in Southeastern US: A Multi-Scale Case Study<\/strong><br \/>\n<strong>Source:<\/strong> American View<br \/>\n<strong>Publish Date:<\/strong> September 16, 2021<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/ckan.americaview.org\/dataset\/the-dynamical-linkage-of-atmospheric-blocking-to-drought-heatwave-and-urban-heat-island\">https:\/\/ckan.americaview.org\/dataset\/the-dynamical-linkage-of-atmospheric-blocking-to-drought-heatwave-and-urban-heat-island<\/a><br \/>\n<strong>Description:<\/strong> The present work provides a unique case study in which blocking, drought, heatwave, and urban heat island all occur concurrently and interplay across a spectrum of spatial scales. We conclude that atmospheric blocking is capable of reinforcing droughts, initiating heat waves, and probably amplifying the urban heat island intensity during the concurrent period.<\/p>\n<p><strong>27. Canopy-forming macroalgae can adapt to marine heatwaves<\/strong><br \/>\n<strong>Source:<\/strong> B2Find<br \/>\n<strong>Author:<\/strong> Fabbrizzi, E<br \/>\n<strong>Publish Date:<\/strong> 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/b2find.dkrz.de\/dataset\/03f21c16-8ada-588c-b4d0-c2e0085a333c\">https:\/\/b2find.dkrz.de\/dataset\/03f21c16-8ada-588c-b4d0-c2e0085a333c<\/a><br \/>\n<strong>Description:<\/strong> This data set is the result of a laboratory experiment carried out as a part of research activities supported by the European Community within the EASME-EMFF (Sustainable Blue Economy) Project AFRIMED (http:\/\/afrimed-project.eu\/, grant agreement N. 789059). To test the effect of MHWs on recruits of G. barbata, a two-fixed factorial design with asymmetrical controls was used.<\/p>\n<p><strong>28. Heatwave characterization derived from reanalysis and climate projections to assess thermal behavior of 7 European city-hubs<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Authors:<\/strong> Lizundia-Loiola, Joshua, Pena Cerezo, and Nieves<br \/>\n<strong>Publish Date:<\/strong> June 13, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/zenodo.org\/records\/8031482\">https:\/\/zenodo.org\/records\/8031482<\/a><br \/>\n<strong>Description:<\/strong> This dataset includes the processing results used to create the interactive climate service Thermal Assessment Tool. It provides the frequency and severity of heatwaves under past, current, and future climate conditions, which allows for the estimation of the thermal behavior of regions and cities in Europe during episodes of extreme heat.<\/p>\n<p><strong>29. Global multi-model projections of urban daily temperatures<\/strong><br \/>\n<strong>Source:<\/strong> Illinois Data Bank<br \/>\n<strong>Author:<\/strong> Lei Zhao<br \/>\n<strong>Publish Date:<\/strong> 2021<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/databank.illinois.edu\/datasets\/IDB-6081052\">https:\/\/databank.illinois.edu\/datasets\/IDB-6081052<\/a><br \/>\n<strong>Description:<\/strong> This dataset contains the emulated global multi-model urban daily temperature projections under the RCP 8.5 scenario. The dataset is derived from the study &#8220;Large model structural uncertainty in global projections of urban heat waves&#8221; (XXXX).<\/p>\n<p><strong>30. Mating under climate change: impact of simulated heatwaves on the reproduction of model pollinators<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Author:<\/strong> Martinet, Baptiste<br \/>\n<strong>Publish Date:<\/strong> December 7, 2020<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/zenodo.org\/records\/4310163\">https:\/\/zenodo.org\/records\/4310163<\/a><br \/>\n<strong>Description:<\/strong> Climate change is related increased frequency and intensity of extreme events such as heatwaves. It is well established that such events may worsen the current worldwide biodiversity decline. In many organisms, heat stress is associated with direct physiological perturbations and could lead to a decrease in fitness.[\/vc_column_text][vc_column_text]<strong>31. Annual frequency of heat waves in U.S. 1961\u20132019, by decade<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Bruna Alves<br \/>\n<strong>Publish Date:<\/strong> Feb 16, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1293780\/us-heat-wave-frequency\/\">https:\/\/www.statista.com\/statistics\/1293780\/us-heat-wave-frequency\/<\/a><br \/>\n<strong>Description:<\/strong> Extreme weather events, such as heat waves, are likely to become more frequent and more intense within the next few years. In the United States, the frequency has increased steadily, from an average of two heat waves per year during the 1960s to about six per year during the 2010s.<\/p>\n<p><strong>32. Parameters of antimicrofouler defence after different heat wave regimes in eelgrass Zostera marina<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Author:<\/strong> Guan, Chi<br \/>\n<strong>Publish Date:<\/strong> 2020<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/b2find.dkrz.de\/dataset\/ac4c01d0-bcc7-5cb5-b277-188d3d2e802c\">https:\/\/b2find.dkrz.de\/dataset\/ac4c01d0-bcc7-5cb5-b277-188d3d2e802c<\/a><br \/>\n<strong>Description:<\/strong> Density of bacteria on Zostera marina, activity strength of Zostera marina surface extract against bacterial settlers, and rosmarinic acid concentration in Zostera marina leaf surface extracts, measured in May, July, and August after three different heatwave regimes simulated in outdoor mesocosms in Kiel, Germany.<\/p>\n<p><strong>33. Examining the joint effects of heatwaves, air pollution, and green space on the risk of preterm birth in California<\/strong><br \/>\n<strong>Source:<\/strong> OmnicsDI<br \/>\n<strong>Author:<\/strong> Sun Y<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.omicsdi.org\/dataset\/biostudies-literature\/S-EPMC8516119\">https:\/\/www.omicsdi.org\/dataset\/biostudies-literature\/S-EPMC8516119<\/a><br \/>\n<strong>Description:<\/strong> In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to understand the etiological mechanisms better and design targeted interventions for certain women during pregnancy.<\/p>\n<p><strong>34. Population exposure to heat waves in Africa 2050, by country<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Saifaddin Galal<br \/>\n<strong>Publish Date:<\/strong> Jan 31, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/1310855\/population-exposure-to-heat-waves-in-africa-by-country\/\">https:\/\/www.statista.com\/statistics\/1310855\/population-exposure-to-heat-waves-in-africa-by-country\/<\/a><br \/>\n<strong>Description:<\/strong> Considering a moderate emissions scenario, most of Africa&#8217;s countries will likely have their entire population exposed to heat waves by 2050. According to the source estimates, exposure to heat waves will be lower in South Africa (45 percent) and Morocco (15 percent).<\/p>\n<p><strong>35. Local-scale climatic refugia offer sanctuary for a habitat-forming species during a marine heatwave<\/strong><br \/>\n<strong>Source:<\/strong> Data Subak<br \/>\n<strong>Publish Date:<\/strong> November 1, 2022<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/data.subak.org\/dataset\/local-scale-climatic-refugia-offer-sanctuary-for-a-habitat-forming-species-during-a-marine-heat\">https:\/\/data.subak.org\/dataset\/local-scale-climatic-refugia-offer-sanctuary-for-a-habitat-forming-species-during-a-marine-heat<\/a><br \/>\n<strong>Description:<\/strong> Gradual climate change and discrete extreme climatic events have driven shifts in the structure of populations and the distribution of species in many marine ecosystems. The most profound impacts of recent warming trends have been generally observed at species&#8217; warm edges and on large, conspicuous species.<\/p>\n<p><strong>36. Typical &amp; Extreme Meteorological Years and Heatwaves for Dynamic Building Simulations in Belgium based on MAR model Simulations<\/strong><br \/>\n<strong>Source:<\/strong> Zenodo<br \/>\n<strong>Author:<\/strong> Doutreloup, S\u00e9bastien, Fettweis, Xavier<br \/>\n<strong>Publish Date:<\/strong> November 9, 2021<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/zenodo.org\/records\/5606983\">https:\/\/zenodo.org\/records\/5606983<\/a><br \/>\n<strong>Description:<\/strong> These files were produced from simulations of the MAR model forced by the ERA5 reanalyses over the period 1980\u20132020 but also by 3 ESMs from the CMIP6 database, namely BCC-CSM2-MR, MPI-ESM.1.2, and MIROC6 over the period 1980\u20132100. The available data for version 1.0 concerns 12 cities in Belgium, but this may be increased in future versions of this dataset.<\/p>\n<p><strong>37. Heatwave-mediated decreases in phytoplankton quality negatively affect zooplankton productivity<\/strong><br \/>\n<strong>Source:<\/strong> Borealis Data<br \/>\n<strong>Author:<\/strong> Kim, Jihyun; Dimitriou, Alexandra; Forster, Ian; Tseng, Michelle<br \/>\n<strong>Publish Date:<\/strong> 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/borealisdata.ca\/dataset.xhtml?persistentId=doi:10.5683\/SP3\/8DTNYX\">https:\/\/borealisdata.ca\/dataset.xhtml?persistentId=doi:10.5683\/SP3\/8DTNYX<\/a><br \/>\n<strong>Description:<\/strong> Abstract Climate change is expected to increase the frequency of extreme temperature events. The effect of heatwaves on phytoplankton is of particular concern because they are a key source of C, N, P, and essential fatty acids for aquatic ecosystems.<\/p>\n<p><strong>38. European summer heatwave catalogue<\/strong><br \/>\n<strong>Source:<\/strong> WDC Climate<br \/>\n<strong>Author:<\/strong> Beobide Arsuaga, Goratz<br \/>\n<strong>Publish Date:<\/strong> July 11, 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.wdc-climate.de\/ui\/entry?acronym=DKRZ_LTA_1075_ds00028\">https:\/\/www.wdc-climate.de\/ui\/entry?acronym=DKRZ_LTA_1075_ds00028<\/a><br \/>\n<strong>Description:<\/strong> The file contains the data to create the European summer heatwave catalogue using ERA5 (1982\u20132022) high boreal summer (July and August) daily maximum temperatures (T2max) linearly interpolated to the MPI-ESM-HR grid.<\/p>\n<p><strong>39. 4-Dimensional Weekly Temperature and Marine Heatwaves Categories from ESA\/CAREHeat project<\/strong><br \/>\n<strong>Source:<\/strong> Catalogue PIGMA<br \/>\n<strong>Publish Date:<\/strong> March 8, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.pigma.org\/geonetwork\/BORDEAUX_METROPOLE_DIR_INFO_GEO\/api\/records\/87a33c31-5930-4379-8cfa-0b29ceee9756\">https:\/\/www.pigma.org\/geonetwork\/BORDEAUX_METROPOLE_DIR_INFO_GEO\/api\/records\/87a33c31-5930-4379-8cfa-0b29ceee9756<\/a><br \/>\n<strong>Description:<\/strong> These datasets contain 4D (x, y, z, t) weekly temperature and marine heatwaves (MHW) categories estimated from the surface up to 300-m depth, at a 0.25\u00b0x0.25\u00b0 horizontal grid resolution and for 4 areas of interest.<\/p>\n<p><strong>40. UQAM-Heatwave ERA5 Archive and Temperatures (U-HEAT) Catalog<\/strong><br \/>\n<strong>Source:<\/strong> Borealis Data<br \/>\n<strong>Authors:<\/strong> Comeau, Elise; DiLuca, Alejandro; Roberge, Fran\u00e7ois<br \/>\n<strong>Publish Date:<\/strong> 2023<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/borealisdata.ca\/dataset.xhtml?persistentId=doi:10.5683\/SP3\/Z4Y0LK\">https:\/\/borealisdata.ca\/dataset.xhtml?persistentId=doi:10.5683\/SP3\/Z4Y0LK<\/a><br \/>\n<strong>Description:<\/strong> The UQAM Heatwave ERA5 Archive and Temperatures (U-HEAT) catalog is a global temperature and heatwave dataset for the period between 1940 and 2022.[\/vc_column_text][vc_column_text]<strong>41. Heat Waves: Deaths due to Heat Waves, as recorded by WMO<\/strong><br \/>\n<strong>Source:<\/strong> Dataful<br \/>\n<strong>Author:<\/strong> World Meteorological Organizations<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/dataful.in\/datasets\/15705\/\">https:\/\/dataful.in\/datasets\/15705\/<\/a><br \/>\n<strong>Description:<\/strong> World Meteorological Organization. Heat Waves: Deaths due to Heat Waves, as recorded by WMO [Data set].<\/p>\n<p><strong>42. Economic losses due to major heat waves and cold spells worldwide up to 2016<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Statista Research Department<br \/>\n<strong>Publish Date:<\/strong> Nov 17, 2016<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/267727\/economic-loss-caused-by-worldwide-major-heat-waves-and-cold-waves\/\">https:\/\/www.statista.com\/statistics\/267727\/economic-loss-caused-by-worldwide-major-heat-waves-and-cold-waves\/<\/a><br \/>\n<strong>Description:<\/strong> The statistic shows the economic damage due to the world&#8217;s major heat waves and cold waves from 1900 to 2016. The economic loss in China due to the heat wave in January 2008 amounted to approximately 21.1 billion U.S. dollars.<\/p>\n<p><strong>43. Meteor showers or heat waves?<\/strong><br \/>\n<strong>Source:<\/strong> ICPSR<br \/>\n<strong>Authors:<\/strong> Engle, Robert F., Ito, Takato, and Lin, Wen-Ling<br \/>\n<strong>Publish Date:<\/strong> Jan 3, 1996<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.icpsr.umich.edu\/web\/ICPSR\/studies\/1010\">https:\/\/www.icpsr.umich.edu\/web\/ICPSR\/studies\/1010<\/a><br \/>\n<strong>Description:<\/strong> These data and\/or computer programs are part of ICPSR&#8217;s publication-related archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.<\/p>\n<p><strong>44. Long-term sea surface temperature measurements from the Leigh Marine Laboratory, northern New Zealand<\/strong><br \/>\n<strong>Source:<\/strong> Government of New Zealand<br \/>\n<strong>Authors:<\/strong> Nick Shears, Jo Evans, and John Atkins<br \/>\n<strong>Publish Date:<\/strong> February 1, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/portal.zero.govt.nz\/77d6ef04507c10508fcfc67a7c24be32\/dataset\/oai-figshare-com-article-24773262\">https:\/\/portal.zero.govt.nz\/77d6ef04507c10508fcfc67a7c24be32\/dataset\/oai-figshare-com-article-24773262<\/a><br \/>\n<strong>Description:<\/strong> In review. Long-term warming and record-breaking marine heatwaves in the Hauraki Gulf, northern New Zealand. The New Zealand Journal of Marine and Freshwater Research.<\/p>\n<p><strong>45. Monthly average daily temperatures in the United Kingdom, 2015-2023<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Erick Burgue\u00f1o Salas,<br \/>\n<strong>Publish Date:<\/strong> Feb 5, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/322658\/monthly-average-daily-temperatures-in-the-united-kingdom-uk\/\">https:\/\/www.statista.com\/statistics\/322658\/monthly-average-daily-temperatures-in-the-united-kingdom-uk\/<\/a><br \/>\n<strong>Description:<\/strong> While daily average temperatures in the United Kingdom usually peak in July or August, the highest average temperature recorded in 2023 was in June, at 16.8 degrees Celsius. Since 2015, the highest average daily temperature in the UK was registered in July 2018, at 18.7 degrees Celsius.<\/p>\n<p><strong>46. Three-dimensional analysis reveals diverse heat waves types in Europe<\/strong><br \/>\n<strong>Source:<\/strong> B2Find<br \/>\n<strong>Author:<\/strong> Data Archiving and Networked Services (DANS)<br \/>\n<strong>Publish Date:<\/strong> 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/b2find.dkrz.de\/dataset\/40d8d6c0-5e48-559f-be9a-8220691fe2c1\">https:\/\/b2find.dkrz.de\/dataset\/40d8d6c0-5e48-559f-be9a-8220691fe2c1<\/a><br \/>\n<strong>Description:<\/strong> Figure source files in plain text format (.txt) for the article &#8216;Lhotka, O., &amp; Kysel, J. (2024): Three-dimensional analysis reveals diverse heat waves types in Europe. Communications Earth &amp; Environment.&#8217;<\/p>\n<p><strong>47. Figure source files for article &#8216;Three-dimensional analysis reveals diverse heat waves types in Europe&#8217;<\/strong><br \/>\n<strong>Source:<\/strong> Mendeley Data<br \/>\n<strong>Author:<\/strong> Ondrej Lhotka, Jan Kysely<br \/>\n<strong>Publish Date:<\/strong> May 21, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/data.mendeley.com\/datasets\/fkfywnjcr8\/1\">https:\/\/data.mendeley.com\/datasets\/fkfywnjcr8\/1<\/a><br \/>\n<strong>Description:<\/strong> Figure source files in plain text format (.txt) for the article &#8216;Lhotka, O., &amp; Kysel, J. (2024): Three-dimensional analysis reveals diverse heat wave types in Europe. Communications Earth &amp; Environment.&#8217;<\/p>\n<p><strong>48. Average winter temperature in Germany, 1960\u20132024<\/strong><br \/>\n<strong>Source:<\/strong> Statista<br \/>\n<strong>Author:<\/strong> Statista Research Department<br \/>\n<strong>Publish Date:<\/strong> May 15, 2024<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.statista.com\/statistics\/982807\/average-winter-temperature-germany\/\">https:\/\/www.statista.com\/statistics\/982807\/average-winter-temperature-germany\/<\/a><br \/>\n<strong>Description:<\/strong> In 2023\/2024, the average winter temperature in Germany was 4.1 degrees Celsius. That winter was part of a growing list of warmer winters in the country. Figures had increased noticeably compared to the 1960s.<\/p>\n<p><strong>49. Extreme-Weather Temperature Prediction<\/strong><br \/>\n<strong>Source:<\/strong> Kaggle<br \/>\n<strong>Author:<\/strong> GAURAV DUTTA<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.kaggle.com\/datasets\/gauravduttakiit\/extreme-weather-temperature-prediction\">https:\/\/www.kaggle.com\/datasets\/gauravduttakiit\/extreme-weather-temperature-prediction<\/a><br \/>\n<strong>Description:<\/strong> Reliable forecasting of air temperature at 2 m above the land surface plays a significant role when preparing for potential weather-related disasters, such as heat waves (i.e., maximum daytime air temperature) and cold spells (i.e., minimum nighttime air temperature).<\/p>\n<p><strong>50. Extreme-Weather Temperature Data set<\/strong><br \/>\n<strong>Source:<\/strong> Kaggle<br \/>\n<strong>Author:<\/strong> AKHEELMD_4<br \/>\n<strong>Link:<\/strong> <a href=\"https:\/\/www.kaggle.com\/datasets\/akheelmd4\/extreme-weather-temperature-data-set\">https:\/\/www.kaggle.com\/datasets\/akheelmd4\/extreme-weather-temperature-data-set<\/a><br \/>\n<strong>Description:<\/strong> Reliable forecasting of air temperature at 2 m above the land surface plays a significant role when preparing for potential weather-related disasters, such as heat waves (i.e., maximum daytime air temperature) and cold spells (i.e., minimum nighttime air temperature).[\/vc_column_text][vc_column_text]\n<h2><b>Conclusion<\/b><\/h2>\n[\/vc_column_text][vc_column_text]With this, we come to an end to this week\u2019s \u2018Dataset of the Week\u2019 blog. Make sure to check out our previously published blogs in \u2018Dataset of the Week\u2019 on <a href=\"http:\/\/newsdata.io\">Newsdata.io<\/a>. I hope to see you again next week for yet another blog on trending topics.<\/p>\n<p>Happy Minning![\/vc_column_text][image_with_animation image_url=&#8221;3027&#8243; image_size=&#8221;full&#8221; animation_type=&#8221;entrance&#8221; animation=&#8221;None&#8221; animation_movement_type=&#8221;transform_y&#8221; hover_animation=&#8221;none&#8221; alignment=&#8221;&#8221; border_radius=&#8221;10px&#8221; box_shadow=&#8221;small_depth&#8221; image_loading=&#8221;default&#8221; max_width=&#8221;100%&#8221; max_width_mobile=&#8221;default&#8221; img_link=&#8221;https:\/\/bit.ly\/41MjLOC&#8221;][\/vc_column][\/vc_row]\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>The article focuses on the increasing heat wave in the past few decades. 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