Temperature Humidity Index GDDP-NEX-CMIP6 ML projections

doi:10.26050/WDCC/THI

Georgiades, Pantelis

ExperimentDOI
temperature humidity index
Summary
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.
Project
SIGNAL (effectS of clImate chanGe oN dAiry cattle)
Contact
Dr. Pantelis Georgiades (
 p.georgiades@nullcyi.ac.cy
 0000-0001-6497-3221)
Spatial Coverage
Longitude 0 to 360 Latitude -60 to 90
Temporal Coverage
2020-01-01 to 2100-12-31
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Size
11.76 TiB (12930999538547 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2034-07-21
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Cite as
Georgiades, Pantelis (2024). Temperature Humidity Index GDDP-NEX-CMIP6 ML projections. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/THI

BibTeX RIS
Funding
European Commission - Horizon Europe
Grant/Award No: 101081276 - PREVENT: Improved predictability of extremes over the Med from Seas. to Dec.
Description
Summary:
Findable: 6 of 7 level;
Accessible: 2 of 3 level;
Interoperable: 3 of 4 level;
Reusable: 5 of 10 level
Method
F-UJI online v3.1.0 automated
Method Description
Checks performed by WDCC. Metrics documentation: https://doi.org/10.5281/zenodo.6461229 Metric Version: metrics_v0.5
Result Date
2024-08-07
Result Date
2024-08-07
Description
1. Number of data sets is correct and > 0: passed;
2. Size of every data set is > 0: passed;
3. The data sets and corresponding metadata are accessible: passed;
4. The data sizes are controlled and correct: passed;
5. The spatial-temporal coverage description (metadata) is consistent to the data, time steps are correct and the time coordinate is continuous: passed;
6. The format is correct: passed;
7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
Method Url
https://www.wdc-climate.de/docs/WDCC_User_Guide_Data_v1.pdf
Result Date
2024-08-07
Contact typePersonORCIDOrganization
Contact
Dr. Pantelis Georgiades
0000-0001-6497-3221
The Cyprus Institute
Author
Dr. Pantelis Georgiades
0000-0001-6497-3221
The Cyprus Institute
Investigator
Dr. Pantelis Georgiades
0000-0001-6497-3221
The Cyprus Institute
Funder
-
-
European Commission - Horizon Europe

Is compiled by

[1] DOI Chen, Tianqi; Guestrin, Carlos. (2016). XGBoost. doi:10.1145/2939672.2939785

Is derived from

[1] DOI Hersbach, Hans; Bell, Bill; Berrisford, Paul; Hirahara, Shoji; Horányi, András; Muñoz‐Sabater, Joaquín; Nicolas, Julien; Peubey, Carole; Radu, Raluca; Schepers, Dinand; Simmons, Adrian; Soci, Cornel; Abdalla, Saleh; Abellan, Xavier; Balsamo, Gianpaolo; Bechtold, Peter; Biavati, Gionata; Bidlot, Jean; Bonavita, Massimo; Chiara, Giovanna; Dahlgren, Per; Dee, Dick; Diamantakis, Michail; Dragani, Rossana; Flemming, Johannes; Forbes, Richard; Fuentes, Manuel; Geer, Alan; Haimberger, Leo; Healy, Sean; Hogan, Robin J.; Hólm, Elías; Janisková, Marta; Keeley, Sarah; Laloyaux, Patrick; Lopez, Philippe; Lupu, Cristina; Radnoti, Gabor; Rosnay, Patricia; Rozum, Iryna; Vamborg, Freja; Villaume, Sebastien; Thépaut, Jean‐Noël. (2020). The ERA5 global reanalysis. doi:10.1002/qj.3803

Attached Dataset Groups ( 2 )

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Parent project(s)

effectS of clImate chanGe oN dAiry cattle

[Entry acronym: THI] [Entry id: 5280922]