EGU23-5278
https://doi.org/10.5194/egusphere-egu23-5278
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Emergence of extreme precipitation statistics from the properties of convective cells

Francesco Marra1,2, Eleonora Dallan3, Efrat Morin4, and Moshe Armon5
Francesco Marra et al.
  • 1Department of Geosciences, University of Padova, Italy
  • 2Institute of Atmospheric Sciences and Climate, National Research Council (CNR-ISAC), Bologna, Italy
  • 3Department of Land Environment Agriculture and Forestry, University of Padova, Italy
  • 4Institute of Earth Sciences, Hebrew University of Jerusalem, Israel
  • 5Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland

The statistics of extreme precipitation over a location of interest are crucial for designing hydraulic structures and mitigating extreme events impact. These statistics emerge from (i) the presence of different storm types, (ii) the different intensity of storms of a given type, (iii) the spatial variability of storms during their life-cycle, combined with (iv) the advection of storms across the domain. Explicit separation of these components could help us establish links between atmospheric dynamics (i.e., the occurrence and frequency of different types of storms) and thermodynamics (i.e., the properties of different storm types) on one side, and the emerging statistics of extremes. Here, we make a first step in this direction by focusing on a semi-arid region in the southeastern Mediterranean in which precipitation is almost solely related to convective processes, minimizing the effect of point (i).

We use very-high-resolution (60 m x 60 m, 1 min) weather radar observations to track convective cells during 11 storms that occurred over 2 years (>1200 cells). We mimic rain gauge observation of the tracked cells by sampling the rainfall fields at random locations and we alter advection by applying synthetic velocities to the Lagrangian fields of the cells. This allows us to isolate the impacts of (ii) storm intensity, and (iv) advection. Then, we generate sets of synthetic cells with analogous properties (peak intensity, area, velocity) and different profiles to examine the impact of (iii) spatial variability.

We find that the spatial sampling of convective cells occurred during the 11 storms explains most of the variability of extreme precipitation in the region. The extremes emerging from this sampling are well described by Weibull tails. Return levels estimated from the 11 storms using a non-asymptotic extreme value method are comparable to the ones derived from 25 years of rain gauge observations (error in the 100-year return levels <15%). We discuss the sensitivity of extreme return levels to changes in properties and velocities of the convective cells.

How to cite: Marra, F., Dallan, E., Morin, E., and Armon, M.: Emergence of extreme precipitation statistics from the properties of convective cells, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5278, https://doi.org/10.5194/egusphere-egu23-5278, 2023.