Abstract
We analyse and quantify the recurrences of European temperature extremes using 32 historical simulations (1900–1999) of the fifth Coupled Model Intercomparison Project (CMIP5) and 8 historical simulations (1971–2005) from the EUROCORDEX experiment. We compare the former simulations to the 20th Century Reanalysis (20CRv2c) dataset to compute recurrence spectra of temperature in Europe. We find that, (1) the spectra obtained by the model ensemble mean are generally consistent with those of 20CR; (2) spectra biases have a strong regional dependence; (3) the resolution does not change the order of magnitude of spectral biases between models and reanalysis, (4) the spread in recurrence biases is larger for cold extremes. Our analysis of biases provides a new way of selecting a subset of the CMIP5 ensemble to obtain an optimal estimate of temperature recurrences for a range of time-scales.
Highlights
Climate events linked to extremes of temperature [1,2,3] have severe impacts on human health and natural ecosystems [4,5,6]
We evaluate how Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations can represent the recurrences in extremes events using the methodology of [28] to further illustrate the biases between CMIP5 models and a reference
The term bias refers to the difference between CMIP5 and 20CRv2c recurrence spectra
Summary
Climate events linked to extremes of temperature (heatwaves/cold spells) [1,2,3] have severe impacts on human health and natural ecosystems [4,5,6]. Morak et al [16] uses the Hadley Centre Global Environmental Model, version 1 (HadGEM1) with both anthropogenic and natural forcings to demonstrate that the model shows a tendency to significantly overestimated changes in warm extremes, changes in temperature extremes are generally well captured by the model. HadGEM3-A [19], models overestimated warm extremes especially in central/northern Europe while cold extremes appear well simulated. One of the most striking findings in [19] is the ability of the model to capture and reproduce the main observed North-Atlantic atmospheric weather regimes responsible for temperature and precipitation extreme events
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