Jonathan Koh

Jonathan Koh

PhD in Statistics

Publications

Articles (peer-reviewed)

  • Koh, J., Steinfeld, D., Martius, O. (2025+). Using spatial extreme-value theory with machine learning to model and understand spatially compounding extremes. Proceedings of the Royal Society A. Preprint.

  • Allen, S., Koh, J., Segers, J., Ziegel, J. (2025+). Tail calibration of probabilistic forecasts. Journal of the American Statistical Association. DOI.

  • Koh, J. (2025). Dragons or snakes: The impact of Chinese astrology on marriages and births. Significance, 22(4):14-18. DOI. Author’s original version here.

  • Koh, J., Opitz, T. (2025). Extreme-value modelling of migratory bird arrival dates: Insights from citizen-science data. Journal of the Royal Statistical Society: Series A (with Discussion). DOI. Info, slides, and our reply.

  • Koh, J., Koch, E., Davison, A. C. (2025). Space-time extremes of severe US thunderstorm environments. Journal of the American Statistical Association, 120(550), 591–604. DOI.

  • Poschlod, B., Koh, J. (2024). Convection-permitting climate models can support observations to generate rainfall return levels. Water Resources Research, 60(4):e2023WR035159. DOI.

  • Koh, J. (2023). Gradient boosting with extreme-value theory for wildfire prediction. Extremes, 26(2):273–299. DOI.

  • Koh, J., Pimont, F., Dupuy, J.-L., Opitz, T. (2023). Spatiotemporal wildfire modelling through point processes with moderate and extreme marks. The Annals of Applied Statistics, 17(1):560-582. DOI. Correction here. Video here

  • Barton, Y., Rivoire, P., Koh, J., Ali, S. M., Kopp, J., Martius, O. (2022). On the temporal clustering of European extreme precipitation events and its relationship to persistent and transient large-scale atmospheric drivers. Weather and Climate Extremes, 38:e100518. DOI.

  • Koch, E., Koh, J., Davison, A. C., Lepore, C., Tippett, M. K. (2021). Trends in the extremes of environments associated with severe US thunderstorms. Journal of Climate, 34(4):1259–1272. DOI.

Discussions and whitepapers (peer-reviewed)

  • Koh, J., Opitz, T. (2025). Authors’ reply to the Discussion of ‘Extreme-value modelling of migratory bird arrival dates: Insights from citizen-science data’. Journal of the Royal Statistical Society: Series A. DOI.

  • Koh, J. (2025). Discussion of “Inference for extreme spatial temperature events in a changing climate with application to Ireland” by Healy et al. Journal of the Royal Statistical Society: Series C (Applied Statistics), 74(2):315–316. DOI.

  • Beucler, T., Koch, E., Kotlarski, S., Leutwyler, D., Michel, A., Koh, J. (2024). Next-Generation Earth System Models: Towards Reliable Hybrid Models for Weather and Climate Applications. Chapter of the Swiss Academy of Engineering Sciences whitepaper. Postprint

  • Davison, A. C., Koch, E., Koh, J. (2019). Comment: Models are approximations! Statistical Science, 34(4):584–590. DOI.

Articles (in revision)

  • Koh, J. (2025+). Statistics of extremes for natural hazards: wildfires. Book chapter in preparation, for Chapman and Hall/CRC Handbook on Statistics of Extremes.

  • Barton, Y., Aregger, M., Koh, J., Martius, O. (2023+). Serial clustering of convective storms and link to sub-hourly rainfall extremes in Switzerland - a large-scale process perspective.

PhD Thesis

  • Koh, J. (2022). Spatiotemporal modelling of extreme wildfires and severe thunderstorm environments. Public access.