Daily time series of 12 human thermal stress indices in Greece, aggregated at commune level (1998–2022)

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-02-01 Epub Date: 2024-12-28 DOI:10.1016/j.dib.2024.111264
Georgios Charvalis , Michalis Koureas , Chloe Brimicombe , Chara Bogogiannidou , Fani Kalala , Varbara Mouchtouri , Christos Hadjichristodoulou , for HIGH Horizons Study Group
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Abstract

In this paper we present a dataset that contains daily mean, maximum and minimum values of 12 heat stress indices averaged over Greek communes from January 1998 to December 2022. The heat indices contained in the dataset include Apparent Temperature (AT), Heat Index (HI), Humidity Index (Humidex), Normal Effective Temperature (NET), Wet Bulb Globe Temperature (simple version WBGT), Wet Bulb Globe Temperature (thermofeelWBGT), Wet Bulb Temperature (WBT), Wind Chill Temperature (WCT), Mean Radiant Temperature (MRT), and Universal Thermal Climate Index (UTCI) with two variations (UTCI indoor and UTCI outdoor).
To develop the dataset, we used hourly climate variables, acquired from the ERA5 and ERA5-Land datasets, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which are accessible through the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) Application Program Interface (API) client. We used freely available python scripts and resources (HiTiSEA repository, thermofeel library), to calculate 12 heat stress indices for Greece at an enhanced spatial resolution of 0.1° × 0.1°. To facilitate geospatial analysis over the Greek communes, boundary data in shapefile format were obtained from the Hellenic Statistical Authority (ELSTAT). The execution of a built-in QGIS function was implemented to geospatially aggregate the NetCDF files of 12 daily mean, maximum and minimum, indices to 326 Greek communes for 9131 days.
The high spatial and temporal resolution of the data, makes the dataset appropriate for analysis and comparison of climate change impacts, heatwave patterns, and the development of climate adaptation strategies at a regional scale in Greece. Additionally, it can be used as a basis of a system to inform and devise targeted interventions and policies aimed at mitigating the effects of extreme heat events. The attribution of heat stress indices at the commune level (also referred as municipalities or municipal units), which is the lowest level of government within the organizational structure in Greece, enhances the usefulness of the data for statistical analysis against other parameters, such as epidemiological or socio-economic data, which are often available at this level. Finally, the dataset can support educational purposes, providing a practical example of climate data analysis and geospatial statistics applications.
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希腊12个人体热应激指数的日时间序列,在公社一级汇总(1998-2022)
在本文中,我们提供了一个数据集,其中包含1998年1月至2022年12月希腊公社平均12个热应力指数的日平均值,最大值和最小值。数据集中的热指数包括视温(AT)、热指数(HI)、湿度指数(Humidex)、正常有效温度(NET)、全球湿球温度(简单版WBGT)、全球湿球温度(thermofeelWBGT)、全球湿球温度(WBT)、风寒温度(WCT)、平均辐射温度(MRT)和具有两种变化的通用热气候指数(UTCI) (UTCI室内和室外)。为了开发数据集,我们使用了从欧洲中期天气预报中心(ECMWF)制作的ERA5和ERA5- land数据集获取的每小时气候变量,这些数据集可通过哥白尼气候变化服务(C3S)气候数据存储(CDS)应用程序接口(API)客户端访问。我们使用免费的python脚本和资源(HiTiSEA存储库,thermofeel库),以0.1°× 0.1°的增强空间分辨率计算了希腊的12个热应力指数。为了便于对希腊公社进行地理空间分析,从希腊统计局(ELSTAT)获得了shapefile格式的边界数据。通过执行一个内置的QGIS功能,对326个希腊公社9131天内的12个日均值、最大值和最小值指数的NetCDF文件进行地理空间聚合。数据的高时空分辨率使该数据集适合于分析和比较希腊区域范围内的气候变化影响、热浪模式以及气候适应战略的制定。此外,它还可以作为一个系统的基础,为减轻极端高温事件的影响提供信息和制定有针对性的干预措施和政策。公社一级(也称为市镇或市政单位)是希腊组织结构中最低一级的政府,其热应激指数的归因增强了数据对其他参数的统计分析的有用性,如流行病学或社会经济数据,这些数据通常在这一级可用。最后,该数据集可以支持教育目的,提供气候数据分析和地理空间统计应用的实际示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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