EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

A comparison of moderate and extreme ERA-5 daily precipitation with two observational data sets

Pauline Rivoire1, Olivia Martius1, and Philippe Naveau2
Pauline Rivoire et al.
  • 1Oeschger Centre for Climate Change Research and Institute of Geography, University of Bern, Bern, Switzerland (
  • 2Laboratoire des Sciences du Climat et de l'Environnement, CNRS-CEA-UVSQ, Gif-sur-Yvette, France

Both mean and extreme precipitation are highly relevant and a probability distribution that models the entire precipitation distribution therefore provides important information. Gamma distributions are often used to model low and moderate precipitation amounts and extreme value theory allows to model the upper tail of the distribution. We apply the Extended Generalized Pareto Distribution (EGPD). Thanks to a transition function, this method overcomes the problem of finding a threshold between upper and lower tails. The transition cumulative distribution function of the EGPD is constrained on the upper tail and lower tail to enable a GPD behavior for both small and large extremes.

EGPD is used here to characterize ERA-5 precipitation. ERA-5 is a new ECMWF climate re-analysis dataset that provides a numerical description of the recent climate by combining a numerical weather model with observations. The data set is global with a spatial resolution of 0.25° and currently covers the period from 1979 to present. ERA-5 precipitation is computed from model forecasts and therefore needs validation against observational datasets. ERA-5 daily precipitation is compared to EOBS precipitation, a gridded dataset spatially interpolated from observations over Europe, and to CMORPH precipitation, a global satellite-based dataset. Simultaneous occurrence of extreme events is assessed with a hit rate. An intensity comparison is conducted with quantiles confidence intervals and a Kullback Leibler divergence test, both derived from the EGPD.

Overall, good agreements but also strong mismatches between ERA-5 and the observational datasets can be found, depending on the feature of interest in precipitation data. This work highlights both. For example, extreme event occurrences between ERA5 and the observational datasets appear to agree. The overlap between 95% confidence intervals on quantiles depends on the season and the probability of occurrence. Over Europe, the best agreement results are generally reached in regions with high station density in EOBS. The global intensity comparison between ERA5 and CMORPH shows a good agreement for moderate quantiles, except for some mountainous regions, but presents a large signal of disagreement in the tropics for large quantiles.

How to cite: Rivoire, P., Martius, O., and Naveau, P.: A comparison of moderate and extreme ERA-5 daily precipitation with two observational data sets, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-666,, 2021.