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Planetary wave-breaking can lead to large-scale atmospheric circulation anomalies and favour high-impact weather occurrences. For example, the simultaneous occurrence of anti-cyclonic wave-breaking to the south of the North Atlantic jet and cyclonic wave-breaking to the north, here termed double wave-breaking, has been linked to heightened frequencies of explosive cyclones in the Atlantic basin and destructive windstorms over Western and Continental Europe. The present study analyses the long-term temporal variability of wintertime cyclonic and anti-cyclonic wave-breaking, and the resulting double wave-breaking, in the North Atlantic. We use reanalysis data, proxy reconstructions of the North Atlantic Oscillation (NAO) and a 1000-year coupled global climate model equilibrium simulation under constant pre-industrial forcing. The wave-breaking wavelet spectra highlight a significant ultra-centennial variability in double wave-breaking frequency, which is largely mirrored in the variability of the NAO. However, we note that the NAO wavelet spectra in the different datasets display significant discrepancies. The low-frequency wave-breaking variability is reflected in long-term anomalies of the large-scale atmospheric circulation in the Euro-Atlantic sector. The 100-year periods with the most and least double wave-breaking occurrences display significant and opposite anomalies in both upper and lower-level wind, as well as in the frequency of extreme temperature events and in the magnitude of wind destructiveness over Europe. The latter broadly resembles the wind destructiveness anomalies associated with individual double wave-breaking instances in reanalysis data. The existence of low-frequency variability in an atmospheric pattern related to high-impact weather events has important implications for the study and interpretation of climate change projections and of possible future NAO changes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The analysis of recurrences of trajectories in dynamical systems allows the identification of rare states of the systems. 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 (20CR) dataset. We use the recurrence analysis method developed by Faranda and Vaienti (2013) 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.ReferenceFaranda D, Vaienti S (2013) A recurrence-based technique for detecting genuine extremes in instrumental temperature records. Geophys. Res. Lett. 40(21):5782--5786 [ABSTRACT FROM AUTHOR]

Background: A higher incidence of inflammatory bowel disease (IBD) in industrialized areas has been previously reported, but the effect of emigrating to western industrialized countries for a period of time and returning to the country of origin is unknown. Aim of the study was to evaluate the effect of emigrating to another country and returning to the place of origin on the risk of IBD., Methods: A prospective case-control study was performed. Inclusion criteria were all patients >18 years diagnosed with Crohn's disease (CD) or ulcerative colitis (UC) in the last 10 years. Healthy, unrelated controls, matched by sex, age and smoking habits, with no family history of IBD were included. All patients and controls were interviewed and emigration was defined as living for at least one year in another country., Results: 242 consecutive patients with IBD (105 CD and 137 UC) and 242 controls were included. Patients who had previously emigrated developed more frequently IBD than controls (OR 1.93, 95%CI 1.19-3.15, p<0.01). Patients who emigrated to European countries developed more frequently IBD than controls (OR 1.91, 95%CI 1.07-3.47, p=0.02), but not those who had emigrated to Latin America (OR 1.48, 95%CI 0.67-3.27, p=0.32). Emigration plays a significant role in the development of UC (OR 2.24, 95%CI:1.29-3.88, p<0.01), but not in CD (OR 1.56, 95%IC:0.83-2.92, p=0.15)., Conclusions: People who emigrate to westernised countries have a higher risk for developing IBD, especially UC. Environmental factors related with industrialization seem to play an important role in the pathogenesis of these diseases., (Copyright © 2011 European Crohn's and Colitis Organisation. Published by Elsevier B.V. All rights reserved.)