wdc-climate.de:5280922 eng; USA collection THI Dr. Pantelis Georgiades The Cyprus Institute www.cyi.ac.cy pointOfContact 2026-02-04T10:21:32 ISO 19115 ISO 19115-2:2009 Temperature Humidity Index GDDP-NEX-CMIP6 ML projections 2024-08-07 publication 1 THI doi:10.26050/WDCC/THI Dr. Pantelis Georgiades The Cyprus Institute www.cyi.ac.cy Email: p.georgiades@cyi.ac.cy principalInvestigator Dr. Pantelis Georgiades The Cyprus Institute www.cyi.ac.cy Email: p.georgiades@cyi.ac.cy author WDCC publisher The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data (https://doi.org/10.7917/OFSG3345) to hourly Temperature Humidity Index (THI) values. The THI is a critical metric for assessing heat stress in dairy cattle, which is a significant concern under changing climatic conditions. We utilized the Extreme Gradient Boost (XGBoost Chen et al. 2016) algorithm, chosen for its efficiency and capability to handle large datasets, to train models using historical hourly data from the ERA5 reanalysis dataset (Hersbach et al. 2020). The trained models were then applied to generate hourly THI projections from 2020 to 2100 across 12 climate models under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). The focus was exclusively on land areas, with a spatial grid resolution of 0.25 degrees, ensuring the relevance and applicability of the data for agricultural purposes. The result is a comprehensive, high-resolution dataset that provides detailed insights into the future impacts of heat stress on dairy cattle, facilitating better planning and mitigation strategies in the agricultural sector. Dr. Pantelis Georgiades The Cyprus Institute www.cyi.ac.cy pointOfContact NetCDF machine learning temperature humidity index CC-BY-4.0: Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ eng; USA 0.0 360.0 -60.0 90.0 2020-01-01 2100-12-31 info:eu-repo/grantAgreement/EC/HE/101081276/BE//PREVENT: Improved predictability of extremes over the Med from Seas. to Dec. temperature_humidity_index The Temperature Humidity Index (THI) is a simple, non-invasive metric which estimates the levels of thermal stress caused by the combined effect of temperature and humidity and has been widely used in the scientific literature as as reference for early warning systems of heat stress.; unit: 1 NetCDF 12931000 https://www.wdc-climate.de/ui/entry?acronym=THI information collection