Combining a Multi‐Lake Model Ensemble and a Multi‐Domain CORDEX Climate Data Ensemble for Assessing Climate Change Impacts on Lake Sevan

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Muhammed Shikhani - (Author)
  • Johannes Feldbauer - , Chair of Limnology (Author)
  • Robert Ladwig - (Author)
  • Daniel Mercado‐Bettín - (Author)
  • Tadhg N. Moore - (Author)
  • Artur Gevorgyan - (Author)
  • Amalya Misakyan - (Author)
  • Chenxi Mi - , University of Lethbridge (Author)
  • Martin Schultze - (Author)
  • Bertram Boehrer - (Author)
  • Tom Shatwell - (Author)
  • Klemens Barfus - , Chair of Meteorology (Author)
  • Karsten Rinke - (Author)

Abstract

Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi-scenario, and multi GCM- RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature (Formula presented.) and substantial bottom warming (Formula presented.), longer stratification periods (+55 days) and disappearance of ice cover leading to a shift in mixing regime. Increased insufficient cooling during warmer winters points to the vulnerability of Lake Sevan to climate change. Our workflow leverages the strengths of multiple models at several levels of the model chain to provide a more robust projection and at the same time a better uncertainty estimate that accounts for the contributions of the different model levels to overall uncertainty. Although for specific variables, for example, summer bottom temperature, single lake models may perform better, the full ensemble provides a robust estimate of thermal dynamics that has a high transferability so that our workflow can be a blueprint for climate impact studies in other systems.

Details

Original languageEnglish
Article numbere2023WR036511
JournalWater resources research
Volume60
Issue number11
Publication statusPublished - Nov 2024
Peer-reviewedYes

External IDs

Scopus 85210103242

Keywords

Sustainable Development Goals