EGU22-11672, updated on 16 Jan 2024
EGU General Assembly 2022
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Hourly sea-level change with long-term trends for impact attribution: the HLT Dataset

Matthias Mengel1, Simon Treu1, Sanne Muis2, Sönke Dangendorf3, Thomas Wahl4, Stefanie Heinicke1, and Katja Frieler1
Matthias Mengel et al.
  • 1Potsdam Institute for Climate Impact Research, Potsdam, Germany
  • 2Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Netherlands
  • 3Tulane University, New Orleans, US
  • 4University of Central Florida, Orlando, US

Rising seas are a threat for human and natural systems along coastlines. The relation between global warming and sea-level rise is established, but impacts due to historical sea-level rise are not well quantified on a global scale. To foster the attribution of observed coastal impacts to sea-level rise, we here present HLT, a sea-level forcing dataset encompassing factual and counterfactual sea-level evolution along global coastlines from 1979 to 2015. HLT combines observation-based long-term changes with reanalysis-based hourly water level variation. Comparison to tide gauge records shows improved performance of HLT, mainly due to the inclusion of density-driven sea-level change. We produce a counterfactual by removing the trend in relative sea level since 1900. The detrending preserves the timing of historical extreme sea-level events. Hence, the data can be used in event-based impact attribution to sea-level rise with tuples of impact simulations driven with the factual and counterfactual dataset. The dataset is made available openly through the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).

How to cite: Mengel, M., Treu, S., Muis, S., Dangendorf, S., Wahl, T., Heinicke, S., and Frieler, K.: Hourly sea-level change with long-term trends for impact attribution: the HLT Dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11672,, 2022.