Evaluation of the capability of global climate models in reproducing the temporal clustering in heavy precipitation over Europe

Zhiqi Yang, Gabriele Villarini

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Evaluating the capability of global climate models (GCMs) in reproducing the historical records represents a way of building confidence in their capability for future projections. Among the different ways of evaluating them, here we focus on their capability in reproducing the temporal clustering of heavy precipitation events across Europe in light of four climate modes [the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA) pattern, and the Scandinavia pattern (SCAND)], and GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the large ensemble runs using the Community Earth System Model (CESM). We use a peak over threshold (POT) approach to identify heavy precipitation events, and Cox regression to relate the occurrence of these events to the climate modes. We find that the GCMs can capture the temporal clustering in heavy precipitation across Europe as a function of these four climate modes; moreover, our findings indicate the GCMs can better reproduce the relationship between heavy precipitation and AO/SCAND, than NAO/EA. Comparing the results based on CMIP5 models and CESM, we find that the inter-model uncertainties are larger than the intra-model ones in most of the cases, even though CESM tends to have a poorer performance for EA; this shortcoming for CESM is likely due to the pattern of the Z500 anomalies which is different from the reference data when EA is in the positive phase, affecting the transport of moisture across Europe.

Original languageEnglish (US)
Pages (from-to)131-145
Number of pages15
JournalInternational Journal of Climatology
Volume41
Issue number1
DOIs
StatePublished - Jan 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Keywords

  • climate modes
  • global climate models (GCMs)
  • heavy precipitation
  • temporal clustering

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