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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.5281/zenodo...
Dataset . 2024
License: CC BY
Data sources: Sygma
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Indoor climate projections at 90 workplaces in the Upper Rhine Valley modelled by artificial neural networks

Authors: Sulzer, Markus; Christen, Andreas;

Indoor climate projections at 90 workplaces in the Upper Rhine Valley modelled by artificial neural networks

Abstract

The uploaded files contain the modelled indoor temperature (Ti) and physiologically equivalent temperature (PETi) data at 90 different workplaces in the Upper Rhine Valley, presented in the article "Climate projections of human thermal comfort for indoor workplaces" by Sulzer and Christen (2024), https://doi.org/10.1007/s10584-024-03685-7. The different csv files contain metadata to the different workplaces, the training data recorded in 2021 and 2022, the modelled data for the historical time period 1970-1999 using ERA5-Land data as input data, and for the future time period 2070-2099 using 22 different climate projections as input data. In the file Workplaces_training_2021-2022.csv you can find the measured data at the workplaces used for training of the models and in Workplaces_metadata.csv you can find some metadata about each workplace.

Related Organizations
Keywords

thermal comfort, indoor climate projections

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