Physical and statistical analysis of climate extremes in large data sets (ClimateXL)
Physical and statistical analysis of climate extremes in large data sets (ClimateXL)
ClimateXL brings together national and international experts from climate sciences, statistics and economics to address some of the World Climate Research Program Grand Challenges on Extremes.
Weather and climate extremes (e.g., heavy precipitation events and flooding) can cause severe damages to infrastructure. The occurrence, frequency, and intensity of such extremes are determined by a complex interplay of natural and anthropogenic factors. Climate extremes, in general, are projected to increase and intensify significantly due to anthropogenic climate change until the end of this century. In the near-term, internally generated climate variability will dominate the anthropogenic greenhouse gas forced changes in climate extremes. Adaptation planning to the impacts of climate extremes is therefore challenged to take into account both near- and long-term changes and associated uncertainties.
ClimateXL will investigate uncertainties related to simulations of climate extremes in climate models and, subsequently, improve our understanding of present and future changes in climate extremes. More precisely, the objectives of the project are
- to detect robust relationships between dynamical/physical processes and climate extremes;
- to develop new evaluation methods for climate simulations with focus on extremes;
- to model multivariate extremes in adaptation decision making under uncertainty;
- to provide freely available synthesized information from large climate datasets.
The project is a collaboration between researchers at CICERO, NR and Uni Research AS with CICERO being the project manager. NR's main contribution will be in the development of new evaluation methods. The project runs for four years, from January 1, 2015 to December 31, 2018, and it is funded by the Research Council of Norway under the KLIMAFORSK program.
Research areas
Project period
January 2015 - December 2018