About Me
I am a climate scientist at the International Institute for Applied Systems Analysis in Laxenburg, Austria. I completed a postdoctoral fellowship at Princeton University’s Center for Policy Research on Energy and the Environment (C-PREE), advised by Prof Michael Oppenheimer. I obtained my DPhil in the field of Attribution Science and Climate Econometrics from the University of Oxford, and obtained a MS in Sustainability Management from Columbia University.
My research approach is strongly interdisciplinary and collaborative, integrating numerical models and data science methods from probabilistic event attribution and econometrics to answer research questions related to estimating the impacts of climate change on vulnerable populations and environments. The main questions that underlie my ongoing research activities include:
1) Whether and to what extent does anthropogenic climate change impact the frequency and intensity of extreme weather events and resulting human vulnerabilities?
2) What are the human responses and health-related sensitivities to climate change?
3) What disaster risk reduction mechanisms prepare populations before natural hazards turn into disasters?
In my spare time, I can be found hiking in the woods with my 1-year old, learning Yiddish (or trying to?) and embracing ‘ready, steady, cook’ sessions, creating new recipes from leftovers.
Latest Research
Annals of Applied Statistics: The Short-Term Dynamics of Conflict-Driven Displacement: Bayesian Modeling of Disaggregated Data from Somalia
Together with Gregor Zens, I investigate methodological challenges when modeling imperfect data collected in conflict zones. Employing a Bayesian panel regression, we aim to understand why and under what conditions higher temperatures and meteorological drought lead to conflict-related migration. The results suggest a rapid and non-linear migration response post-conflict, with significant heterogeneity in effects dependent on the nature of conflict events. Our model outperforms standard benchmarks in a forecasting exercise, underscoring its potential for informing decision-makers in crisis scenarios.
Link to accepted paper: Zens, G. and Thalheimer, L. (in press): The Short-Term Dynamics of Conflict-Driven Displacement: Bayesian Modeling of Disaggregated Data from Somalia. The Annals of Applied Statistics
Earth’s Future (preprint): Advancing human displacement modelling: A case study of the 2022 summer floods in Pakistan
The devastating 2022 summer flood in Pakistan displaced about 7 million people in the Sindh province alone. Up to one third of the country’s area, mostly the country’s south, was flooded. Effective response to intensifying and compounding climate change hazards requires impact assessments to include socio-economic components, as well as uncertainties arising from the dynamic interactions between impacts. Such quantitative evidence largely remains limited and fragmented, due to methodological challenges and data limitations. Using the open-source impact assessment platform CLIMADA, we study to what extent flood-related hazards can be used to quantify displacement outcomes in a data-limited region. Using flood depths, exposed population, and impact functions, we link flood vulnerability to displaced people. This allows us to estimate internal displacement resulting from the flood event, and to further assess how displacement varies across different areas. We find that a flood depth threshold of 0.67m (CI 0.35 - 1.10) provides a best fit to all data from Sindh province. We find a negative correlation between displacement and the degree of urbanisation. By testing the performance of our model in explaining differing displacement estimates reported across Pakistan, we show the limitations of existing impact assessment frameworks. We emphasise the importance of estimating potential displacement alongside other impacts to better characterise, communicate, and ultimately respond to the impacts of floods.
Link to preprint: Kam, P. M., Cache, T., Biess, B., Lohrey, S., di Vincenzo, S., McCaughey, J. W., … & Thalheimer, L. (2024). Advancing human displacement modelling: A case study of the 2022 summer floods in Pakistan. Authorea Preprints.