Data-based analysis of climate decisions

Our research group works to better understand the complex, dynamic, and multi-dimensional mechanisms through which climatic conditions affect human well-being and through which climate-related decisions are made, both individually and on a societal level. We analyse these systems through a variety of data-analytic methods, ranging from statistics, econometrics and machine learning to numerical modelling techniques. Using both historic data and projected data about the climate, socio-economic conditions, and development pathways, we are able to provide insight into the motivators of past climate-related phenomena as well as predict future climate-related decisions and societal developments.  

Previously, we have studied how temperature shocks affect economic productivity and electricity consumption, how extreme weather events can cause ripple effects in the global trade and food supply networks, and the factors motivating solar panel usage. 

For more details, see below.

Available position

Our research group brings together expertise from physical and socio-economic disciplines in a quantitative context to analyse the impacts of climate on socio-economic systems.

We are looking for an M.Sc. student with a strong quantitative background to work on the following thesis topic:

Attribution of historical rainfall impacts on the economy to climate change

Building on the success of our recent research which has identified numerous economic sensitivities to climate (see below), you will use in-house climate data from models and observations to assess the extent to which historical climate change has impacted the economy.

A strong quantitative background in mathematics, physics, economics or computer science is necessary; experience in statistics and/or geo-spatial data as well as programming skills (Python, R, or similar) are desirable. Close supervision from experienced researchers working in closely related fields will assist in delivering a successful thesis as well as with your personal and technical development, possibly extending into a PhD position. Contact leonie.wenz@pik-potsdam.de or maxkotz@pik-potsdam.de for further information or to apply. 

Research foci

Using social media and newspaper data to study climate-related behaviour

Understanding the effects of the changing climate on human behaviour is essential for developing informed and effective adaptation and mitigation strategies. In our research, we employ methods from machine learning and econometrics to analyse the unprompted beliefs and feelings that millions of users express on social media platforms such as Twitter in order to understand behavioural changes in relation to environmental influences.

A key factor that influences social concern about climate change is the coverage in journalistic publications such as print and online newspapers. Complementing our social media analysis, we examine the coverage of climate issues in the context of weather extremes.

One focus of our work is the analysis of conflicts and aggression in digital spaces. For example, we used Twitter data to investigate the relationship between climate variables and digital interpersonal conflicts in the United States and Europe in two separate studies. Our results for the United States show that temperatures above or below of 12°C to 21°C are linked to a marked rise in hate speech (Stechemesser et al, 2022). Hate speech increases across U.S. climate zones, income groups and belief systems for temperatures too hot or too cold. Similarly, we find that the amount of racist and xenophobic content posted to the social media platform Twitter is nonlinearly influenced by temperature in six different European countries spanning multiple climate zones (Stechemesser et al, 2021). For each country, fewest racist tweets and likes are found for daily average temperatures between 5 °C and 11 °C, even if hotter temperatures are frequently experienced. Overall our results indicate limits to adaptation to extreme temperatures, and shed light on a yet underestimated societal impact of climate change: conflict in the digital sphere with implications for both societal cohesion and mental health.

• A. Stechemesser, A. Levermann, L. Wenz. Temperature impacts on hate speech online: evidence from four billion geolocated tweets from the USA. The Lancet Planetary Health (2022). https://dio.org/10.1016/S2542-5196(22)00173-5.
• A. Stechemesser, L. Wenz, M. Kotz, A. Levermann. Strong increase of racist tweets outside of climate comfort zone in Europe. Environmental Research Letters (2021). https://iopscience.iop.org/article/10.1088/1748-9326/ac28b3
• A. Stechemesser, L. Wenz, A. Levermann. Corona crisis fuels racially profiled hate in social media networks. The Lancet - EClinicalMedicine (2020). https://doi.org/10.1016/j.eclinm.2020.100372

Artificial intelligence & geospatial analysis for sustainable decisions

In this area, our group focuses on the use of artificial intelligence methodologies and use of geospatial data to develop insight into climate-related decisions on a societal level. So far, our work has used tree-based algorithms to better understand the factors that determine the probability of solar panel installation, as well as temporal patterns of recovery from hurricanes. By means of satellite imagery and population data, we have quantified the number of people worldwide without access to infrastructure via roads (Sustainable Development Goal 9.1) and assessed the trade-off between closing these access gaps and achieving ambitious climate change mitigation targets (SDG-13). We are also applying machine learning methodologies to better understand the predictors of global seasonal temperature variability. Towards these ends, we work extensively with large, geospatial datasets and time series data.

• K. Barton-Henry & L. Wenz. Nighttime light data reveal lack of full recovery after hurricanes in Southern US. Environmental Research Letters 16 (2022). https://doi.org/10.1088/1748-9326/ac998d
• K. Barton-Henry, L. Wenz, A. Levermann. Decay radius of climate decision for solar panels in the city of Fresno, USA. Nature Scientific Reports 11, 8571 (2021). https://doi.org/10.1038/s41598-021-87714-w
• L. Wenz, U. Weddige, M. Jakob, J.C. Steckel. Road to glory or highway to hell? Global road access and climate change mitigation. Environmental Research Letters 15 (2020). https://dx.doi.org/10.1088/1748-9326/ab858d

The economic costs of climate change

Assessments of the economic costs of climate change are a vital tool for guiding climate policy and achieving mitigation, but such assessments lack a comprehensive empirical basis. By employing state-of-the-art statistical methods (e.g. from econometrics, pattern recognition, detection/attribution) to historical data, we aim to uncover new links between climate and society with which we can assess the future costs of climate change. 

Furthermore, in collaboration with the Mercator Research Institute on Global Commons and Climate Change we are continuing to develop DOSE, an open-access Data-base of Sub-national Economic output. With this strong empirical foundation, we will continue to identify and quantify detailed climate impacts and to translate these into policy relevant insights. See below for a list of our related work:

See below for a list of our related work:

• M. Kotz, L. Wenz, A. Levermann, The effect of rainfall changes on economic production. Nature (2022). https://doi.org/10.1038/s41586-021-04283-8.
• M. Kotz, L. Wenz, A. Levermann, Footprint of greenhouse forcing in daily temperature variability
  Proceedings of the National Academy of Sciences 118 (2021). https://doi.org/10.1073/pnas.2103294118
• M. Kotz, L. Wenz, A. Stechemesser, M. Kalkuhl, A. Levermann. Day-to-day temperature variability reduces economic growth. Nature Climate Change (2021). https://doi.org/10.1038/s41558-020-00985-5/
• M. Kalkuhl & L. Wenz. The impact of climate conditions on economic production. Evidence from a global panel of regions. Journal of Environmental Economics and Management 102360 (2020). https://doi.org/10.1016/j.jeem.2020.102360
• F. Ueckerdt, K. Frieler, S. Lange, L. Wenz, G. Luderer, A. Levermann. The economically optimal warming limit of the planet. Earth System Dynamics 10 (2019). https://doi.org/10.5194/esd-10-741-2019
• L. Wenz, A. Levermann, M. Auffhammer. North-South polarization of European electricity consumption under future warming. Proceedings of the National Academy of Sciences 114 (2017). DOI: 10.1073/pnas.1704339114.
• Leonie Wenz, Matthias Kalkuhl, & Maximilian Kotz. (2021). DOSE - The MCC-PIK Database Of Subnational Economic output (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4681306

The international trade network & climate change

International supply chains interconnect suppliers and consumers throughout the world economy. We use Multi Regional Input Output (MRIO) tables, large data sets capturing interdependencies in the global trade network, to explore these interconnections and their role in propagating climate damages. We develop algorithmic methods to advance MRIO techniques on spatial (Wenz et al., 2015) and prospective dimensions (Beaufils & Wenz, 2021). We work in close cooperation with the working group Numerical analysis of global economic impacts to investigate how the structure of the international trade network shapes our resilience toward extreme weather events (Wenz & Levermann 2016, Bren D'Amour et al., 2016).

• M. Jakob, S. Afionis, [...], L. Wenz, S.N. Willner How trade policy can support the climate agenda Science (2022) DOI: 10.1126/science.abo4207
• L. Wenz & S.N. Willner Climate impacts and global supply chains: an overview [Book chapter] Handbook on Trade Policy and Climate Change [edited by M. Jakob] (2022).
• T. Beaufils & L. Wenz, A scenario-based method for projecting multi-regional input-output tables
  Economic Systems Research (2021). https://doi.org/10.1080/09535314.2021.1952404
• C. Otto, S. N. Willner, L. Wenz , K. Frieler, A. Levermann. Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate. Journal of Economic Dynamics and Control 83 (2017). DOI: 10.1016/j.jedc.2017.08.001.
• L. Wenz & A. Levermann. Enhanced economic connectivity to foster heat stress-related losses. Science Advances 2 (2016). DOI: 10.1126/sciadv.1501026.
• C. Bren d'Amour, L. Wenz, M. Kalkuhl, J.C. Steckel, F. Creutzig. Teleconnected food supply shocks. Environmental Research Letters 11 (2016). DOI: 10.1088/1748-9326/11/3/035007.
• L. Wenz, S.N. Wilner, A. Radebach, R. Bierkandt, J.C. Steckel, A. Levermann, Regional and sectoral disaggregation of multi-regional input-output tables - a flexible algorithm, Economic Systems Research 27 (2015), DOI: 10.1080/09535314.2014.987731

Corona-virus related work

The working group also investigates the question of whether the COVID-19 pandemic and possible political, individual and economic responses to it will render us more or less vulnerable to future weather extremes and how we can steer that development in a favourable way such that our societies’ resilience to extreme events – of any kind – is enhanced.