Training School on Dynamical Modelling of Compound Events
The goal of this training school organized by the COST Action DAMOCLES is to train the next generation of compound event researchers in the modelling of compound events. Compound weather and climate events refer to the combination of multiple climate drivers that contributes to societal or environmental risk. They can pose serious threats to natural systems and human societies. Modelling of compound events requires knowledge on many different drivers and approaches. The school will be a mixture of lectures and project work. The lectures will cover a range of topics including: Introduction to Modelling; Regional Climate Modelling; Event Attribution and several lectures on Impact Modelling. Each participant will spend time working on a group project applying what has been learnt. And there will be plenty of time to explore the beautiful city of Budapest.
When: 18.7.-29.7.2022
Where: Eötvös Loránd University (ELTE), Budapest (Hungary)
For whom: PhD students and early postdocs (maximum 1 year after completion of PhD) or research scientists who are less than 5 years post Masters level degree who are affiliated to institutions within countries that participate in DAMOCLES (see list)
How to apply: Send motivation letter (1 page), CV, preference for student project (1st, 2nd, 3rd choice, see below) and at least one reference (e.g. PhD advisor) as one pdf file to fiachra.oloughlin@ucd.ie.
Criteria for selection: Selection of successful applicants will be merit based on the quality of the CV and motivation letter, but diversity will also be considered in selecting the successful applicants.
Visas and COVID-19: Applicants will be required to ensure they have both visas to enter Hungary, and be able to satisfy Hungary’s COVID-19 entry requirements. We will inform the applicants as soon as possible after selection if they have been successful; we apologise for the short time window between the applications closing and the training school.
Application deadline: 15 November 2021
Financial support: The number of participants is limited to 20. All costs will be covered by DAMOCLES.
Accommodation: 2-bedrooms will be reserved locally
Organizing committee: Fiachra O’Loughlin, Freya Garry, Jakob Zscheischler, Bart van den Hurk, Rita Pongracz
Topics
- Concept of compound events
- Introduction to Modelling
- Regional Climate Modelling
- Impact Modelling for Hydrology, Fire, Vegetation, etc
- Impact forecasting of compound events
- Dynamic downscaling and Bias Correction
Lecturers
Dr Ana Bastos (Max Planck Institute for Biogeochemistry, Germany)
Dr Emaunele Bevacqua (UFZ, Germany)
Dr Rita Cardoso (University of Lisbon, Portugal)
Prof. Daniela Domeisen (ETH Zurich, Switzerland)
Dr Freya Garry (Met Office, UK)
Prof. Bart van den Hurk (Deltares, The Netherlands)
Prof. Douglas Maraun (University of Graz, Austria)
Dr Fiachra O'Loughlin (University College Dublin, Ireland)
Dr Christopher White (University of Strathclyde, UK)
Dr Jakob Zscheischler (UFZ, Germany)
Student Projects
Participants of the Traning School are requested to choose from one of the following 4 student projects. During the school there will be ample time for the four groups to work on their projects
Student project 1
Project title: A downward counterfactual analysis of compound weather risk
Supervision: Alessio Ciullo (ETH Zurich) & Bart van den Hurk (Deltares)
Compound extreme weather events often lead to unexpected and unforeseen high impacts. This happens because these events often differ significantly from what registered in the past, which is used as a guidance for preparedness and adaptation. However, past occurrences are only one realization of what could have occurred. Exploring multiple potential realizations of past events (labelled as so-called “Downward counterfactuals”) helps revealing alternative pasts to better prepare for the future. By building on a recently introduced framework (Ciullo et al., 2021), students in this project will conduct a downward counterfactual risk analysis to study the impact of temporal and spatial compounding of tropical cyclones. In particular, the students team will construct downward counterfactuals, analyze their potential impacts, and explore possible consequences of climate change or socio-economic development on the risks that are induced by these impacts. The work will involve statistical modelling using physical insights of cause-effect chains, and quantifying risks using empirical impact models.
Student project 2
Project title: Climate change alterations of riverine compound floods in (pre-)alpine catchments
Supervision: Benjamin Poschlod (Berchtesgaden National Park) & Fiachra O’Loughlin (UCD)
River flooding in Europe is mostly triggered by one of three main drivers: (Extreme) precipitation, soil moisture excess, and snowmelt. However, their relative importance differs greatly across Europe (Berghuijs et al., 2019). In pre-alpine areas, all three processes can generate floods, and their compound occurrence may cause larger flood events than individually. Climate change is expected to alter the frequency, seasonality and intensity of these drivers (increased extreme precipitation; earlier snowmelt and less snow; changing seasonality of precipitation and soil moisture). Therefore, in this training school project, we will investigate the according future alterations of riverine compound flood events.
Student project 3
Project title: Impact of preconditioned compound events on vegetation productivity
Supervision: Freya Garry (Met Office) & Ana Bastos (Max Planck Institute for Biogeochemistry)
Vegetation sensitivity to weather conditions varies from season to season and between vegetation types. Extreme climatic conditions or particular combinations of non-extreme climate anomalies during winter or spring impact productivity in the subsequent seasons through impacts on water-availability (e.g., soil-moisture memory) or on vegetation development in the early growing-season stages (e.g., frost damage). In this project, we will evaluate how extremes in vegetation productivity in summer depend on preconditioning effects from winter and spring anomalies in temperature, rainfall and radiation, using long-term datasets of vegetation productivity and outputs from Earth System Models. We will further evaluate how these effects vary between vegetation types and how they are projected to change under different future climate change scenarios.
Student project 4
Project title: The influence of modes of climate variability and their interplay on compound events
Supervision: Emanuele Bevacqua (UFZ) & Daniela Domeisen (ETH Zurich)
Climate modes of variability, such as the Atlantic Multi-decadal Oscillation (AMO) and El Niño-Southern Oscillation (ENSO), can favour extreme weather events such as precipitation and temperature extremes around the world. Although understanding the influences of modes of variability on compound events would be important to improve preparedness to climate-related impacts, little is known about these influences. Here, using large ensemble climate model simulations and reanalysis data, we will contribute to closing this research gap by focussing on a selected compound event types. We will identify hotspot regions where modes of variability influence compound event occurrences and inspect whether particular combinations of the modes of variability (e.g., superposition of extreme states of both ENSO and AMO indices), which may be favoured by dependencies between the modes, can enhance regional compound event occurrences and amplitudes.