Training Schools

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: 10.1.-21.1.2022

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.

 


Training School on Statistical Modelling of Compound Events

 

NEWS: A blog post about the Training School can be found here

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 compound events requires knowledge on advanced statistical methods. The goal of this training school organized by the COST Action DAMOCLES is to train the next generation of compound event researchers. The school  will provide an introduction into various statistical approaches to study compound events. There will be ample time to work on scientific projects in small groups to apply what has been learned in the classes and to socialize with the other participants and lecturers.

When: 23.9.-4.10.2019

Where: Lake Como School of Advanced Studies (Italy)

For whom: PhD students and early postdocs (maximum 2 years after completion of PhD)

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 trainingschool.damocles@climate.unibe.ch.

Application deadline: 10 June 2019

Financial support: The number of participants is limited to 20. All participants will receive stipends between 900 and 1400€, which will be covered by DAMOCLES (depending on the travel distance, see  participating countries

Accomodation: 2- and 3-bedrooms have been reserved at In Riva Al Lago Como.

Organizing committee: Jakob Zscheischler, Carlo de Michele, Aglaé Jézéquel, Philippe Naveau 

 

Topics

  • Concept of compound events
  • Copula theory
  • Multivariate extreme value theory
  • Importance sampling
  • Processes behind different types of compound events (droughts and heatwaves; compound flooding)

 

Lecturers

Dr. Tamara Ben-Ari (INRA-AgroParisTech, France)

Dr. Emaunele Bevacqua (University of Reading, UK)

Prof. Fabrizio Durante (University of Salento, Italy)

Prof. Sebastian Engelke (University of Geneva, Switzerland)

Prof. Bart van den Hurk (Deltares & VU Amsterdam, Netherlands)

Prof. Douglas Maraun (University of Graz, Austria)

Prof. Carlo de Michele (Politecnico di Milano, Italy)

Dr. Philippe Naveau (LSCE, France)

Dr. Roberta Pappadà (University of Trieste, Italy) 

Prof. Gianfausto Salvadori (University of Salento, Italy)

Prof. Sonia Seneviratne (ETH Zurich, Switzerland)

Dr. Sebastian Sippel (ETH Zurich, Switzerland)

Dr. Pascal Yiou (LSCE, France)

Dr. Jakob Zscheischler (University of Bern, Switzerland)


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: Identifying drivers of extreme impacts

Supervision: Karin van der Wiel (KNMI) & Jakob Zscheischler (University of Bern)

Extreme impacts are often related to multiple compounding conditions in the weather and climate system. For instance, unfortunate combinations of temperature and precipitation can lead to crop failure or vegetation mortality. Identifying which combination of weather conditions lead to and extreme impacts is challenging and often made even more difficult do to a small sample size in observations. In this project, we will work with very long impact model runs (crop model, vegetation model) and explore approaches to identify multivariate climate conditions that are associated with extreme impacts.

The project resulted in a manuscript, which has been published in Earth System Dynamics.

 

Student project 2

Project title: Importance sampling for compound events

Supervision: Aglaé Jézéquel (LMD) & Pascal Yiou (LSCE)

The goal is to adapt an analogue-based importance sampling algorithm (developed by Pascal Yiou and Aglaé Jézéquel) to a multivariate compound event (currently it is used to simulate single variable extremes such as very extreme heatwaves and evaluate their probability of occurrence). This could for example be useful to simulate very extreme compound events, which may have a higher occurrence probability with climate change. Similar to a weather generator, simulated compound events could be used as an input for an impact model. The project will also compare the return periods obtained by importance sampling with other approaches, e.g. based on multivariate extreme value theory.

The project resulted in a manuscript, which has been published in Earth System Dynamics.

 

Student project 3

Project title: Model evaluation of bivariate relationships with copulas

Supervision: Emanuele Bevacqua (University of Reading) & Carlo de Michele (Uni di Milano)

Combinations of hot conditions and high/low relative humidity can lead to extreme heat stress for the human body or exacerbate the fire risk. To develop reliable heat stress and fire risk assessments, it is crucial to evaluate how climate models represent relative humidity and temperature, as well as their interplay, i.e. statistical dependence. In this project, we will carry out this evaluation and quantify the contribution of the model biases in temperature, relative humidity, and - especially - their dependence, to the final bias in heat stress and fire risk indices. The results will highlight the regions where a careful development of present and future heat stress and fire risk assessments is required.

The project resulted in a manuscript, which has been published in Natural Hazards and Earth System Sciences.

 

Student project 4

Benefits and limitations of statistical models for assessing compound flooding

Supervision: Elisa Ragno (TU Delft) & Bart van den Hurk (Deltares)

The goal of the project is to investigate the benefits and limitations of statistical methods to model dependencies between hydro-meteorological data. Specifically, the project will retrace the work presented in van den Hurk et al. (2015) in which the authors investigate the effect of the co-occurrence of precipitation events and storm surges on inland water level using a set of dynamical models. These models will be replaced by a statistical model calibrated at the specific site. The comparison between the results from the two approaches will provide the basis to discuss opportunities and limitations of the application of statistical methods to investigate compound events. Moreover, the project will place emphasis on the importance of compound events for flooding risk assessment.

The project resulted in a manuscript, which has been published in Hydrology and Earth System Sciences.