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  Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

Vautard, R., Christidis, N., Ciavarella, A., Alvarez‑Castro, C., Bellprat, O., Christiansen, B., et al. (2019). Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe. Climate Dynamics, 52, 1187-1210. doi:10.1007/s00382-018-4183-6.

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 Creators:
Vautard, Robert, Author
Christidis, Nikolaos, Author
Ciavarella, Andrew, Author
Alvarez‑Castro, Carmen, Author
Bellprat, Omar, Author
Christiansen, Bo, Author
Colfescu, Ioana, Author
Cowan, Tim, Author
Doblas‑Reyes, Francisco, Author
Eden, Jonathan, Author
Hauser, Mathias, Author
Hegerl, Gabriele, Author
Hempelmann, Nils, Author
Klehmet, Katharina, Author
Lott, Fraser, Author
Nangini, Cathy, Author
Orth, René1, Author           
Radanovics, Sabine, Author
Seneviratne, Sonia I., Author
van Oldenborgh, Geert Jan, Author
Stott, Peter, AuthorTett, Simon, AuthorWilcox, Laura, AuthorYiou, Pascal, Author more..
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960–2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land–atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.

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 Dates: 2018-03-212019-04-192019
 Publication Status: Issued
 Pages: -
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 Identifiers: Other: BEX682
DOI: 10.1007/s00382-018-4183-6
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Title: Climate Dynamics
  Other : Clim. Dyn.
Source Genre: Journal
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Publ. Info: Heidelberg : Springer-International
Pages: - Volume / Issue: 52 Sequence Number: - Start / End Page: 1187 - 1210 Identifier: ISSN: 0930-7575
CoNE: https://pure.mpg.de/cone/journals/resource/954925568800