We quantified, for the first time at global scale, the uncertainties in present-day ESL estimates, which have by default been ignored in broad-scale sea-level rise impact assessments to date. A recently developed database of historical tide gauge observations (GESLA2,
http://www.gesla.org/(si apre in una nuova finestra)) was used to explore uncertainties in extreme sea level estimates owing to the subjective selection of certain extreme value models. Given the global nature of the database this part of the analysis was also carried out at the global scale. In total we used 20 different extreme value models comprising different sampling techniques to identify extremes and a range of parametric distributions to quantify inter-model uncertainties. The latter can be compared to inter-model uncertainties in future mean sea level projections published by the Intergovernmental Panel on Climate Change (IPCC) in its Fifth Assessment report (AR5). Based on the results, recommendations were provided which model to use and how to analyze extreme sea levels for broad-scale coastal impact and adaptation analyses, namely the Generalized Pareto distribution (GPD) along with high sea level events that exceed the 99% percentile threshold.
We showed that ESL uncertainties exceed those from global MSLR projections and, assuming that we meet the Paris agreement goals, the projected MSLR itself by the end of the century, in particular in high risk regions such as Europe, the U.S. and Southeast Asia. For Europe, as an example, we also compared the uncertainties in present-day ESL estimates to projections of future changes in the storm surge climate under various greenhouse gas emission scenarios. The former were an order of magnitude larger than the projected future changes.
Also for the European coastline, the results from the global tide gauge analysis were used and integrated with an analysis of storm surge water levels that were derived with hydrodynamic numerical models for the entire coast, every few kilometers (not just at the tide gauge locations). As a result, we obtained maps of robust and spatially coherent return water level estimates for the entire coast. Adjustments have been made to the DIVA model source code in order to allow the inclusion of this three-parametric distribution in addition to the simplistic two-parametric Gumbel distribution that was applied in previous assessments. The new model setup will next be used to explore how the improved representation of storm surges affects estimates of present-day and future flood risk and associated adaptation costs.
Another shortcoming in all broad-scale coastal impact models is the omission of what we refer to as “compound flooding”. The latter occurs when freshwater from rivers or rainfall run-off cannot drain as it would usually do because of elevated sea levels due to a storm surge. So far, it has been widely assumed that extreme rainfall (and resulting river discharge) and storm surges are independent processes that only coincide by chance. Recent research has shown, however, that significant correlation exists between the two at many coastline stretches. Including these high impact events into flood risk management and disaster mitigation is essential and has been identified as a priority within the World Climate Research Program’s Grand Challenge on Extremes. Given the innovative nature of the topic and missing guidelines how to incorporate compound events into broad-scale impact models we developed a commentary paper to benchmark current knowledge.
The topics addressed in the project and results obtained have been, and will continue to be, promoted and disseminated in multiple ways. As of now 6 journal papers have been published or are under review, 9 abstracts and presentations have been contributed to national and international conferences and workshop, 4 conferences and conference sessions have been and will be organized, several media articles have been published (
http://www.nature.com/articles/sdata2016107/metrics(si apre in una nuova finestra)) and a website has been created where results will be published in the future (after acceptance of journal papers;
https://thomaswahl.org/crisis/(si apre in una nuova finestra)).
