This article provides the first comprehensive assessment of methods for the creation of weather variables for use in building simulation. We undertake a critical analysis of the fundamental issues and limitations of each methodology and discusses new challenges, such as how to deal with uncertainty, the urban heat island, climate change and extreme events. Proposals for the next generation of weather files for building simulation are made based on this analysis. A seven-point list of requirements for weather files is introduced and the state-of-the-art compared to this via a mapping exercise. It is found that there are various issues with all current and suggested approaches, but the two areas most requiring attention are the production of weather files for the urban landscape and files specifically designed to test buildings against the criteria of morbidity, mortality and building services system failure. Practical applications: Robust weather files are key to the design of sustainable, healthy and comfortable buildings. This article provides the first comprehensive assessment of their technical requirements to ensure buildings perform well in both current and future climates.

Buildings generate nearly 30% of global carbon emissions, primarily due to the need to heat or cool them to meet acceptable indoor temperatures. In the last 20 years, the empirically derived adaptive model of thermal comfort has emerged as a powerful alternative to fixed set point driven design. However, current adaptive standards offer a simple linear relationship between the outdoor temperature and the indoor comfort temperature, assumed to sufficiently explain the effect of all other variables, e.g. relative humidity (RH) and air velocity. The lack of a signal for RH, is particularly surprising given its well-known impact on comfort. Attempts in the literature to either explain the lack of such a signal or demonstrate its existence, remain scattered, unsubstantiated and localised. In this paper we demonstrate, for the first time, that a humidity signal exists in adaptive thermal comfort using global data to form two separate lines of evidence: a meta-analysis of summary data from 63 field studies and detailed field data from 39 naturally ventilated buildings over 8 climate types. We implicate method selection in previous work as the likely cause of failure to detect this signal, by demonstrating that our chosen method has a 56% lower error rate. We derive a new designer-friendly RH-inclusive adaptive model that significantly extends the range of Highlights • The influence of relative humidity on adaptive thermal comfort explained. • A new adaptive thermal comfort model which considers the effect of relative humidity introduced. • The current model is shown to overestimate overheating by 30% over 13 global locations.

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More frequent hot summers in the UK under climate change could lead to increased discomfort in dwellings, but there is little published field data on internal summer temperatures. Temperatures were measured in four dwellings around south Manchester and five dwellings in London during the August 2003 heat wave. Resultant statistics and various comfort metrics indicated a high level of discomfort in most dwellings, particularly in London. Daily internal temperatures were shown to correlate strongly with a time-decaying function of daily outside temperatures. Day and night temperatures were shown to relate to the type of structure. It is concluded that if heat waves become more common, this would lead to increased discomfort, with implications for health, mortality and housing design. Practical application: The results presented in this paper show what actually happens to a sample of dwelling temperatures during a severe UK heat wave, and the consequences for comfort. Little has been published on this previously. The correlations between time-averaged outside temperatures, and internal temperatures, provide a method for predicting dwelling temperatures in the future in a warming climate, without the need for detailed simulation and including real occupancy effects such as window opening, which are difficult to simulate reliably. Since there were many excess deaths during the August 2003 heat wave, health is an important concern. Work by others on this issue has shown that mortality rate is correlated with a three-day moving average of outside temperature above a threshold. This moving average correlates closely with the type of time-averaged outside temperature used in the paper. It seems quite possible that a 3-day moving average is a good predictor of excess mortality because it is also a good predictor of internal building temperatures, due to the mediation of thermal mass. This provides an alternative, or additional, explanation to that which explains the mortality as the cumulative result of high external temperatures acting on the human body over a few days, without considering the effects of buildings.

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