Globally estimated precipitation extremes
- 1Delft University of Technology, Water Management, Delft, Netherlands (g.j.gruendemann@tudelft.nl)
- 2Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, Netherlands
- 3Department of Civil and Environmental Engineering, Princeton University, Princeton, USA
- 4Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, Netherlands
- 5Division of Earth and Ocean Sciences, Duke University, Durham, NC, USA
Understanding the magnitude and frequency of extreme precipitation events is a core component of translating climate observations to planning and engineering design. This research aims to capture extreme precipitation return levels at the global scale. A benchmark of the current climate is created using the global Multi-Source Weighted-Ensemble Precipitation (MSWEP-V2, coverage 1979-2017 at 0.1 arc degree resolution) data, by using both classical and novel extreme value distributions. Traditional extreme value distributions, such as the Generalized Extreme Value (GEV) distribution use annual maxima to estimate precipitation extremes, whereas the novel Metastatistical Extreme Value (MEV) distribution also includes the ordinary precipitation events. Due to this inclusion the MEV is less sensitive to local extremes and thus provides a more reliable and smoothened spatial pattern. The global scale application of methods allows analysis of the complete spatial patterns of the extremes. The generated database of precipitation extremes for high return periods is particularly relevant in otherwise data-sparse regions to provide a benchmark for local engineers and planners.
How to cite: Gründemann, G., van der Ent, R., Beck, H., Schleiss, M., Zorzetto, E., and van de Giesen, N.: Globally estimated precipitation extremes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6996, https://doi.org/10.5194/egusphere-egu2020-6996, 2020.
