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Summer weather extremes are often associated with high‐amplitude atmospheric planetary waves (Petoukhov et al., 2013). Such conditions lead to stationary weather patterns, triggering heat waves and sometimes prolonged intense rainfall. These wave events, referred to as periods of Quasi‐Resonant Amplification (QRA), are relatively rare though and hence provide only a few data points in the meteorological record to analyse. Here, we use atmospheric models coupled to boundary conditions that have evolved slowly (i.e., climate), to supplement measurements. Specifically we assess altered probabilities of resonant episodes by employing a unique massive ensemble of atmosphere‐only climate simulations to populate statistical distributions of event occurrence. We focus on amplified waves during the two most extreme European heat waves on record, in years 2003 and 2015 (Russo et al., 2015). These years are compared with other modelled recent years (1987–2011), and critically against a modelled world without climate change. We find that there are differences in the statistical characteristics of wave event likelihood between years, suggesting a strong dependence on the known and prescribed Sea Surface Temperature (SST) patterns. The differences are larger than those projected to have occurred under climate change since the pre‐industrial period. However, this feature of small differences since pre‐industrial is based on single large ensembles, with members consisting of a range of estimates of SST adjustment from pre‐industrial to present. Such SST changes are from projections by a set of coupled atmosphere–ocean (AOGCM) climate models. When instead an ensemble for pre‐industrial estimates is subdivided into simulations according to which AOGCM the SST changes are based on, we find differences in QRA occurrence. These differences suggest that to reliably estimate changes to extremes associated with altered amplification of planetary waves, and under future raised greenhouse gas concentrations, likely requires reductions in any spread of future modelled SST patterns.

The United Nations Framework Convention on Climate Change (UNFCCC) has established the Warsaw International Mechanism (WIM) to deal with loss and damage associated with climate change impacts, including extreme events, in developing countries. It is not yet known whether events will need to be attributed to anthropogenic climate change to be considered under the WIM. Attribution is possible for some extreme events- a climate model assessment can estimate how greenhouse gas emissions have affected the likelihood of their occurrence. Dialogue between scientists and stakeholders is required to establish whether, and how, this science could play a role in the WIM.

Demonstrating the effect that climate change is having on regional weather is a subject which occupies climate scientists, government policy makers and the media. After an extreme weather event occurs, the question is often posed, ‘Was the event caused by anthropogenic climate change?’ Recently, a new branch of climate science (known as attribution) has sought to quantify how much the risk of extreme events occurring has increased or decreased due to climate change. One method of attribution uses very large ensembles of climate models computed via volunteer distributed computing. A recent advancement is the ability to run both a global climate model and a higher resolution regional climate model on a volunteer's home computer. Such a set-up allows the simulation of weather on a scale that is of most use to studies of the attribution of extreme events. This article introduces a global climate model that has been developed to simulate the climatology of all major land regions with reasonable accuracy. This then provides the boundary conditions to a regional climate model (which uses the same formulation but at higher resolution) to ensure that it can produce realistic climate and weather over any region of choice. The development process is documented and a comparison to previous coupled climate models and atmosphere-only climate models is made. The system (known as weather@home) by which the global model is coupled to a regional climate model and run on volunteers' home computers is then detailed. Finally, a validation of the whole system is performed, with a particular emphasis on how accurately the distributions of daily mean temperature and daily mean precipitation are modelled in a particular application over Europe. This builds confidence in the applicability of the weather@home system for event attribution studies.

In response to their respective opinion articles, I argue that Kevin Trenberth's proposal to reverse the burden of proof in attribution studies is misguided, but Judith Curry's counter proposal to abandon hypothesis tests as useless is worse still. Some observed weather events will have been made more likely by human influence on climate, some less likely, and it is a legitimate and very important field of scientific enquiry to work out which are which. The appropriate null hypothesis to use in such studies is that human influence has not increased the probability of occurrence of a particular weather event unless the evidence suggests otherwise. WIREs Clim Change 2011, 2:931–934. doi: 10.1002/wcc.145 For further resources related to this article, please visit the WIREs website.

Equatorial winds in the stratosphere are known to influence the frequency of stratospheric midwinter sudden warmings. Sudden warmings, in turn, influence the Earth's climate both through their direct influence on polar temperatures and through the temperature dependence of ozone depletion in the lower stratosphere. The conventional (Holton-Tan) explanation for the equatorial influence on sudden warmings is in terms of the equatorial winds in the lower stratosphere (∼20-30 km) acting as a waveguide for midlatitude planetary wave propagation. This study employs stratospheric-temperature analyses and equatorial rocketsonde wind data extending to 58 km to diagnose the relationship between the northern-hemisphere polar temperatures and equatorial zonal winds at all height levels in the stratosphere. In addition to the recognized Holton-Tan relationship linking the polar temperatures to the quasi-biennial oscillation in equatorial winds in the lower stratosphere, a strong correlation of polar temperatures with equatorial winds in the upper stratosphere is found. We suggest that this may be associated with the strength and vertical extent of the westerly phase of the semi-annual oscillation in the upper stratosphere, although the observations alone cannot provide a conclusive, causal relationship. The main diagnostic tools employed are correlation studies and composite analysis. The results underline the need for continued high quality, equatorial wind measurements at all stratospheric levels.