Teaching Material

The material on this page will be completed and updated as we receive it.
For your personal preparation, please get familiar with the abstracts and associated reading of all keynotes. Consider installing the software used during the workshops and get familiar with it.
Note: All material on this webpage is for your personal use and must not be redistributed!

Keynotes: Presentations, Abstracts and Readings

Keynote 1: The other climate crisis

Presentation: KN_01_Stevens.pdf (PDF, 37MB)
Abstract: KN_01_Stevens.pdf (PDF, 152KB)

Key References:

Shaw, T. A., & Stevens, B. (2025). The other climate crisis. Nature, 639(8056), 877–887. (PDF, 2.3 MB)
Stevens, B. (2026). Climate modelling (Vol. 51, 2026, pp. in press. Annual Reviews. (preprint for download). (PDF, 2.9 MB)

Keynote 2: The Space-Time Structure of Climate Variability - What Proxies Can and Cannot Tell Us

Abstract: KN_02_Laepple.pdf (PDF, 135KB)

Key References:

Laepple, T., et al. (2023). Regional but not global temperature variability underestimated by climate models at supradecadal timescales. Nature Geoscience, 16(11), 958–966. (PDF, 3.9 MB)
Hébert, R., Herzschuh, U., & Laepple, T. (2022). Millennial-scale climate variability over land overprinted by ocean temperature fluctuations. Nature Geoscience, 15(11), 899–905. (PDF, 13.7 MB)
McPartland, M. Y., et al (2025). The colors of proxy noise. Climate of the Past, 21(11), 1917–1931. (PDF, 2.6 MB)

Keynote 3: Weather and climate variations of the last centuries: New approaches and new insights

Presentation: KN_03_Broennimann.pdf (PDF, 13.2 MB)
Abstract: KN_03_Brönnimann.pdf (PDF, 131KB)

Key References:

Valler et al (2024) ModE-RA - a global monthly paleo-reanalysis of the modern era (1421-2008). Scientific Data, 11, 36 (PDF, 12.7 MB)
Stucki et al (2026) Evaluation of nine gridded daily weather reconstructions for the European heatwave summer of 1807. Clim. Past, 22, 517–540 (PDF, 11.7 MB)
Brönnimann et al (2025) Past hydroclimate extremes in Europe driven by Atlantic Jet stream and recurrent weather patterns. Nat. Geosci., 18, 246-253 (PDF, 10.0 MB)

Keynote 4: Observed and modelled decadal variability

Presentation: KN_04_Simpson.pdf (PDF, 16.5 MB)
Abstract: KN_04_Simpson.pdf (PDF, 124KB)

Key References:

Zhang et al (2019) A Review of the Role of the Atlantic Meridional Overturning Circulation in Atlantic Multidecadal Variability and Associated Climate Impacts, Review of Geophysics (PDF, 11.1 MB)
Di Lorenzo et al (2023) Modes and Mechanisms of Pacific Decadal-Scale Variability (PDF, 5.3 MB)
Simpson et al (2018) Modeled and Observed Multidecadal Variability in the North Atlantic Jet Stream and Its Connection to Sea Surface Temperatures, J. Clim., 31, 8313–8338 (PDF, 5.9 MB)
Clement et al (2026) A Signal-to-Noise Problem in Model Simulations of Decadal Climate Modes, J. Clim., 39, 2853–2869 (PDF, 6.8 MB)

Keynote 5: Climate variability in space and time in the atmospheric boundary layer of urban environments

Presentation: KN_05_Fenner.pdf (PDF, 9.8 MB)
Abstract: KN_05_Fenner.pdf (PDF, 128KB)

Key References:

Fenner, D., et al 2024: urbisphere-Berlin campaign: Investigating multi-scale urban impacts on the atmospheric boundary layer. Bull. Am. Meteorol. Soc. 105 (10): E1929-E1961. (PDF, 8.9 MB)
Masson, V., et al 2020: Urban Climates and Climate Change. Annu. Rev. Environ. Resour. 45 (1): 411-444. (PDF, 9.7 MB)
Kittner, J., et al 2025: Analysis of nocturnal urban heat advection using crowd weather stations. Q. J. R. Meteorol. Soc. 151 (773): e5065. (PDF, 17.5 MB)

Keynote 6: Rossby waves and their influence on climate variability and extremes

Presentation: KN_06_Romppainen (PDF, 21.3 MB)
Abstract: KN_06_Romppainen (PDF, 155KB)

Key References:

Rossby, C.-G. and collaborators 1939 ‘Relation between variations in the intensity of the zonal circulation of the atmosphere and the displacements of the semi-permanent centers of action,’ J. Marine Res., 2, pp. 38–55. (PDF, 5.3 MB)
Hoskins, B. J., and T. Ambrizzi, 1993: Rossby Wave Propagation on a Realistic Longitudinally Varying Flow. J. Atmos. Sci., 50, 1661–1671. (PDF, 1.0 MB)
Wirth, V. et al 2018: Rossby Wave Packets on the Midlatitude Waveguide - A Review. Mon. Wea. Rev., 146, 1965–2001. (PDF, 4.6 MB)
White, R. H. et al 2022: From Atmospheric Waves to Heatwaves: A Waveguide Perspective for Understanding and Predicting Concurrent, Persistent, and Extreme Extratropical Weather. Bull. Amer. Meteor. Soc., 103, E923–E935. (PDF, 2.7 MB)

Keynote 7: Climate variability and extremes in a warming climate: Driving processes and coupling between land, ocean and atmosphere

Abstract: KN_07_Seneviratne.pdf (PDF, 133KB)

Key References:

Seneviratne, S.I.et al 2021: Chapter 11: Weather and Climate Extreme Events in a Changing Climate. In: IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. (PDF, 16.3 MB)
Schumacher, D.L. et al 2022: Drivers and Mechanisms of the 2021 Pacific Northwest Heatwave. Earth's Future, 10, e2022EF002967. (PDF, 4.6 MB)

Keynote 8: Stratosphere – troposphere dynamical coupling and impacts on our weather

Presentation: KN_08_Domeisen.pdf (PDF, 19.0 MB)
Abstract: KN_8_Domeisen.pdf (PDF, 177KB)

Key References:

Baldwin, M. P., & Dunkerton, T. J. (2001). Stratospheric harbingers of anomalous weather regimes. Science, 294(5542), 581-584. (PDF, 623KB)
Domeisen, D. I., & Butler, A. H. (2020). Stratospheric drivers of extreme events at the Earth’s surface. Communications Earth & Environment, 1(1), 59. (PDF, 1.7 MB)
Domeisen et al, (2020). The Role of the Stratosphere in Subseasonal to Seasonal Prediction: 2. Predictability Arising From Stratosphere-Troposphere Coupling. JGR Atmospheres. (PDF, 16.1 MB)

Keynote 9: Uncertainty in the climate system and the generation of climate information

Presentation: KN_09_Dolas-Reyes.pdf (PDF, 4.3 MB)
Abstract: KN_09_Doblas-Reyes.pdf (PDF, 130KB)

Key References:

Slingo, J. & Palmer, T. (2011). Uncertainty in weather and climate prediction. Philosophical Transactions of the Royal Society A, 369, 4751–4767. (PDF, 1.5 MB)
Hawkins, E. & Sutton, R. (2009). The potential to narrow uncertainty in regional climate predictions. Bulletin of the American Meteorological Society, 90(8), 1095–1107. (PDF, 13.7 MB)
Kumar, A. and Murtugudde, R. (2013). Predictability, uncertainty and decision making: a unified perspective to build a bridge from weather to climate. Current Opinion in Environmental Sustainability, 5, 327–333. (PDF, 536KB)
Doblas-Reyes, F.J. et al. (2021). The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1363–1512. (PDF, 17.9 MB)

Keynote 10: Climate Variability: Ocean Memory and Ocean Circulation

Presentation: KN_10_Marotzke.pdf (PDF, 10.2 MB)
Abstract: KN_10_Marotzke.pdf (PDF, 157KB)

Key Reference:

Wunsch, C., 1992: Decade-to-century changes in the ocean circulation. Oceanography 5, 99-106. (PDF, 1.6 MB)
Marotzke, J., and P. M. Forster, 2015: Forcing, feedback and internal variability in global temperature trends. Nature, 517, 565-570. (PDF, 1.1 MB)
Roberts et al 2014: Is the 2004–2012 reduction of the Atlantic meridional overturning circulation significant? Geophysical Research Letters, 41, 3204-3210. (PDF, 762KB)

Keynote 11: Weather and climate predictions with AI

Presentation: KN_11_Fuhrer.pdf (PDF, 11.8 MB)
Abstract: KN_11_Fuhrer.pdf (PDF, 153KB)

Key References:

Watt-Meyer, O. et al. (2025). ACE2: accurately learning subseasonal to decadal atmospheric variability and forced responses. npj Climate and Atmospheric Science, 8, 205. (PDF, 4.1 MB)
Lam, R. et al. (2023). Learning skillful medium-range global weather forecasting. Science, 382, 1416–1421. (PDF, 1003KB)
Kochkov, D. et al. (2024). Neural general circulation models for weather and climate. Nature, 632, 1060–1066. (PDF, 18.2 MB)

Posters: Abstracts

Workshops: Presentations, Abstracts and Software Installation

Whenever possible please bring your own laptop or notebook for the workshops an pre-install special software (please see in workshop details which software is needed for which workshop), if it is needed and read the corresponding readings and key references.

Workshop 1: Time series analysis with spectral methods

Abstract: WS_01_Pöppelmeier-Raible.pdf (PDF, 157KB)

Key References:

Ghil, M., et al., (2002b), “Advanced spectral methods for climatic time series.” Review of Geophysics., 674 40 (1), 1-41. (PDF, 587KB)
Grinsted A, Jevrejeva S, Moore J (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Proc Geophys 11:561–566 (PDF, 204KB)
Jevrejeva S, Moore JC, Grinsted A (2003) Influence of the Arctic Oscillation and El Nino-Southern Oscillation (ENSO) on ice conditions in the Baltic Sea: The wavelet approach. J Geophys Res 108. doi:10.1029/2003JD003417 (PDF, 881KB)
Torrence C, Compo GP (1998) A practical guide to wavelet analysis. B Am Meteorol Soc 79:61–78. (PDF, 1.0 MB)

Requirements:

Own laptop or notebook.
No special software installations required.

Workshop 2: Data-Model Integration - Climate Variability and Change, and Challenges for Data-Model Integration: From Regional Climate Models to Swiss Climate Scenarios

Presentation: WS_02_Rajczak-Kotlarski.pdf (PDF, 3.7 MB)
Abstract: WS_02_Kotlarski-Rajczak.pdf (PDF, 200KB)

Key References:

MeteoSwiss & ETH Zurich (2025): Climate CH2025 – Switzerland's Future Climate. Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, 24 pp. (PDF, 12.2 MB)
MeteoSwiss & ETH Zurich (2025): Climate CH2025 – Scientific Report. Federal Office of Meteorology and Climatology MeteoSwiss, Zurich. (PDF, 1.0 MB)
Rajczak et al 2016: Robust climate scenarios for sites with sparse observations: a two-step bias correction approach. Int. J. Climatol., 36, 1226–1243, doi:10.1002/joc.4417. (PDF, 4.0 MB)
Maraun, D., et al., 2017: Towards process-informed bias correction of climate change simulations. Nature Climate Change, 7, 764–773, doi:10.1038/nclimate3418. (PDF, 1.1 MB)

Requirements:

Own Laptop or notebook.
Software installation: Participants are required to have R installed on their laptops prior to the workshop. Alternative software capable of reading and analyzing .nc and .csv files (e.g. Python) is also acceptable, though no example scripts or technical support will be provided for alternatives. Data files and example R scripts will be distributed to participants at the beginning of the workshop.

Workshop 3: Urban Climate Data – from low-cost networks to multi-city repositories

Abstract: WS_03_Gubler-Burger-Brönnimann.pdf (PDF, 130KB)

Key References:

Gubler, M., Christen, A., Remund, J. & Brönnimann, S. (2021) Evaluation and application of a low-cost measurement network to study intra-urban temperature differences during summer 2018 in Bern, Switzerland. Urban Climate, 37, 100817. (PDF, 6.7 MB)
Burger, M., Gubler, M. & Brönnimann, S. (2024) High-resolution dataset of nocturnal air temperatures in Bern, Switzerland (2007–2022). Geoscience Data Journal, 11, 623–637. (PDF, 19.2 MB)
Amini, S., Huerta, A., Franke, J. et al. (2026) Comprehensive compilation and quality assessment of street-level urban air temperature measurements across European networks. Scientific Data, 13, 658. (PDF, 6.1 MB)

Requirements:

Own Laptop or notebook.
No special software installations required.

Workshop 4: Extreme event attribution

Abstract: WS_4_Fischer.pdf (PDF, 106KB)

Key References:

General overview about attribution of extreme weather and climate-related events (PDF, 1.6 MB)
Step-by-step guide for event attribution as developed by the World Attribution group (PDF, 3.6 MB)
Examples of attribution studies (PDF, 6.1 MB)
Examples of alternative attribution approaches (PDF, 1.9 MB)

Requirements:

Own Laptop or notebook.