PhD Cohort SEESAW 

Societal and Environmental impacts of complex ExtremeS in a chAnging World 

seesaw

The SEESAW PhD cohort aims to understand the non-linear relation between complex hydroclimatic hazards, their socioeconomic and environmental impacts, as well as the climate change effect on such impactful events. For this purpose, we will use long-term hydrometeorological observations and process-based statistics, unprecedented newspaper dataset and large language models, AI-powered remote sensing and counterfactual climate model simulations. The activities of the cohort will help to identify vulnerability hotspots at national scale to support targeted adaptation measures.


SEESAW concept

  • Considering complex extremes: collation, development and cross-validation of long-term multi-source monitoring products
  • Linking hazards and impacts: understanding complex landscape and socio-economical feedback
  • Disentangling climate change effect: novel counterfactual simulations of complex extremes

Subprojects 

Objective: Identify river catchments characterized by long-lasting droughts, unexpected floods, and hence prone to extreme transitions by combining Germany-wide observations and novel process-based statistical approaches

transitions

 PhD researcher 

  • Maysaa Abdelmajid

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Objective: Unravel complex propagation of impacts across sectors using unique newspaper impact dataset and natural language processing
 

news

PhD researcher

  • Maralda Dorsky

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Objective: Relate long-term forest condition time series with respective groundwater levels by means of machine learning quantifying underlying climate change effects 

forest

PhD researcher

  • Denis Streitmatter

UFZ advisors

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Objective: Quantify human-induced climate change influence on high-impact drought-related compound events via novel climate and crop model simulations
 

climate_change

PhD researcher

  • Serkan Bayar

UFZ advisors

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