Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1667-2024
https://doi.org/10.5194/gmd-17-1667-2024
Development and technical paper
 | 
26 Feb 2024
Development and technical paper |  | 26 Feb 2024

High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning

Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen

Related authors

Sectoral attribution of greenhouse gas and pollutant emissions using multi-species eddy covariance on a tall tower in Zurich, Switzerland
Rainer Hilland, Josh Hashemi, Stavros Stagakis, Dominik Brunner, Lionel Constantin, Natascha Kljun, Betty Molinier, Samuel Hammer, Lukas Emmenegger, and Andreas Christen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1088,https://doi.org/10.5194/egusphere-2025-1088, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
A relaxed eddy accumulation flask sampling system for 14C-based partitioning of fossil and non-fossil CO2 fluxes
Ann-Kristin Kunz, Lars Borchardt, Andreas Christen, Julian Della Coletta, Markus Eritt, Xochilt Gutiérrez, Josh Hashemi, Rainer Hilland, Armin Jordan, Richard Kneißl, Virgile Legendre, Ingeborg Levin, Susanne Preunkert, Pascal Rubli, Stavros Stagakis, and Samuel Hammer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3175,https://doi.org/10.5194/egusphere-2024-3175, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Modular approach to near-time data management for multi-city atmospheric environmental observation campaigns
Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, and Nektarios Chrysoulakis
Geosci. Instrum. Method. Data Syst., 13, 393–424, https://doi.org/10.5194/gi-13-393-2024,https://doi.org/10.5194/gi-13-393-2024, 2024
Short summary
Harmonized gap-filled datasets from 20 urban flux tower sites
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022,https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
The motion of trees in the wind: a data synthesis
Toby D. Jackson, Sarab Sethi, Ebba Dellwik, Nikolas Angelou, Amanda Bunce, Tim van Emmerik, Marine Duperat, Jean-Claude Ruel, Axel Wellpott, Skip Van Bloem, Alexis Achim, Brian Kane, Dominick M. Ciruzzi, Steven P. Loheide II, Ken James, Daniel Burcham, John Moore, Dirk Schindler, Sven Kolbe, Kilian Wiegmann, Mark Rudnicki, Victor J. Lieffers, John Selker, Andrew V. Gougherty, Tim Newson, Andrew Koeser, Jason Miesbauer, Roger Samelson, Jim Wagner, Anthony R. Ambrose, Andreas Detter, Steffen Rust, David Coomes, and Barry Gardiner
Biogeosciences, 18, 4059–4072, https://doi.org/10.5194/bg-18-4059-2021,https://doi.org/10.5194/bg-18-4059-2021, 2021
Short summary

Related subject area

Atmospheric sciences
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025,https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025,https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
NeuralMie (v1.0): an aerosol optics emulator
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025,https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025,https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025,https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary

Cited articles

Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M.: Optuna: A Next-Generation Hyperparameter Optimization Framework, in: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2623–2631, https://doi.org/10.1145/3292500.3330701, 2019. 
Albertson, J. D. and Parlange, M. B.: Natural integration of scalar fluxes from complex terrain, Adv. Water Resour., 23, 239–252, https://doi.org/10.1016/S0309-1708(99)00011-1, 1999a. 
Albertson, J. D. and Parlange, M. B.: Surface length scales and shear stress: Implications for land-atmosphere interaction over complex terrain, Water Resour. Res., 35, 2121–2132, https://doi.org/10.1029/1999WR900094, 1999b. 
Ao, X., Grimmond, C. S. B., Ward, H. C., Gabey, A. M., Tan, J., Yang, X.-Q., Liu, D., Zhi, X., Liu, H., and Zhang, N.: Evaluation of the Surface Urban Energy and Water Balance Scheme (SUEWS) at a Dense Urban Site in Shanghai: Sensitivity to Anthropogenic Heat and Irrigation, J. Hydrometeorol., 19, 1983–2005, https://doi.org/10.1175/JHM-D-18-0057.1, 2018. 
Bergstra, J., Bardenet, R., Bengio, Y., and Kégl, B.: Algorithms for Hyper-Parameter Optimization, in: Proceedings of the 24th International Conference on Neural Information Processing Systems, 2546–2554, ISBN 9781618395993, 2011. 
Download
Short summary
We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Share