Comparison of multi-year and reference year building simulations

Copyright © 2010 by SAGE PublicationsBuildings are generally modelled for compliance using reference weather years. In the UK these are the test reference year (TRY) used for energy analysis and the design summer year (DSY) used for assessing overheating in the summer. These reference years currently exist for 14 locations around the UK and consist of either a composite year compiled of the most average months from 23 years worth of observed weather data (TRY) or a single contiguous year representing a hot but non-extreme summer (DSY). In this paper, we compare simulations run using the reference years and the results obtained from simulations using the base data sets from which these reference years were chosen. We compare the posterior statistic to the reference year for several buildings examining energy use, internal temperatures, overheating and thermal comfort. We find that while the reference years allow rapid thermal modelling of building designs they are not always representative of the average energy use (TRY) exposed by modelling with many weather years. Also they do not always give an accurate indication of the internal conditions within a building and as such can give a misleading representation of the risk of overheating (DSY). Practical applications: An understanding of the limitations of the current reference years is required to allow creation of updated reference years for building simulation of future buildings. By comparing the reference years to the base data sets of historical data from which they were compiled an understanding of the benefit of multiple simulations in determining risk can be obtained

Overheating in retrofitted flats: occupant practices, learning and interventions

© 2016 Informa UK Limited, trading as Taylor & Francis Group The overheating risk in flats (apartments) retrofitted to energy-efficient standards has been identified by previous studies as one that is particularly high. With climate change and rising mean temperatures this is a growing concern. There is a need to understand the kinds of practices, learning and interventions adopted by the occupants of individual homes to try to reduce overheating, as this area is poorly understood and under-researched. This case study focuses on the impact of different home-use practices in relation to the severity of overheating in 18 flats in one tower block in northern England. Internal temperatures monitored in comparable flats show that the percentage of time spent above the expected category II threshold of thermal comfort according to BS EN 15251 can differ by over 70%. Extensive monitoring, covering a full year, including two summer periods, has identified emergent changes in heatwave practices linked with increased home-use skills and understanding among the research participants. Close analysis of design intentions versus reality has identified key physical barriers and social learning opportunities for appropriate adaptation in relation to heatwaves. Recommendations for designers and policy-makers are highlighted in relation to these factors

On the creation of future probabilistic design weather years from UKCP09

Copyright © 2011 by SAGE PublicationsWeather data are used extensively by building scientists and engineers to study the performance of their designs, help compare design alternatives and ensure compliance with building regulations. Given a changing climate, there is a need to provide data for future years so that practising engineers can investigate the impact of climate change on particular designs and examine any risk the commissioning client might be exposed to. In addition, such files are of use to building scientists in developing generic solutions to problems such as elevated internal temperatures and poor thermal comfort. With the publication of the UK Climate Projections (UKCP09) such data can be created for future years up to 2080 and for various probabilistic projections of climate change by the use of a weather generator. Here, we discuss a method for the creation of future probabilistic reference years for use within thermal models. In addition, a comparison is made with the current set of future weather years based on the UKCIP02 projections. When used within a dynamic thermal simulation of a building, the internal environments created by the current set of future weather files lie within the range of the internal environments created by the probabilistic reference years generated by the weather generator. Hence, the main advantages of the weather generator are seen to lie in its potentially greater spatial resolution, its ability to inform risk analysis and that such files, unlike ones based on observed data, carry no copyright. Practical applications: The methodology presented in this article will allow academics and buildings engineers to create realistic hourly future weather files using the future climate data of UKCP09 weather generator. This will allow the creation of consistent future weather years for use in areas such as building thermal simulation

The impact of the variability and periodicity of rainfall on surface water supply systems in Scotland

This paper analyses the impact of the variability and periodicity of rainfall on the reliability of water supply systems in Scotland. A conceptual rainfall-runoff model was used to simulate catchment runoff, and the reliability of 29 notional and six actual reservoirs was calculated using a simple storage model. The relationship between water supply reliability and the variability of rainfall was then investigated using different measures of variability. A strong correlation was found between reservoir reliability and measures representing the distribution of rainfall between the winter and summer seasons, as well as the cumulative sum (CUSUM) of annual precipitation, quantifying the variability of rainfall between years. In contrast, mainly the intra-annual CUSUM range and the variance of monthly precipitation influenced the reliability of river-intake schemes. The presence of periodic patterns in rainfall anomalies was found to be more prevalent in West Scotland, where reservoir reliability is on average lower than in the East. In addition, a sensitivity analysis revealed the small influence of evapotranspiration on reservoir reliability in comparison to rainfall variability. This study reveals the measures of variability most affecting the reliability of surface water supplies in Scotland, and could therefore help with their management in the context of future climate change

Regional trends in soil acidification and exchangeable metal concentrations in relation to acid deposition rates

The deposition of high levels of reactive nitrogen (N) and sulphur (S), or the legacy of that deposition, remain among the world's most important environmental problems. Although regional impacts of acid deposition in aquatic ecosystems have been well documented, quantitative evidence of wide-scale impacts on terrestrial ecosystems is not common. In this study we analysed surface and subsoil chemistry of 68 acid grassland sites across the UK along a gradient of acid deposition, and statistically related the concentrations of exchangeable soil metals (1 M KCl extraction) to a range of potential drivers. The deposition of N, S or acid deposition was the primary correlate for 8 of 13 exchangeable metals measured in the topsoil and 5 of 14 exchangeable metals in the subsoil. In particular, exchangeable aluminium and lead both show increased levels above a soil pH threshold of about 4.5, strongly related to the deposition flux of acid compound

Can a climate model reproduce extreme regional precipitation events over England and Wales?

The ability of the HiGEM climate model to represent high-impact, regional, precipitation events is investigated in two ways. The first focusses on a case study of extreme regional accumulation of precipitation during the passage of a summer extra-tropical cyclone across southern England on 20 July 2007 that resulted in a national flooding emergency. The climate model is compared with a global Numerical Weather Prediction (NWP) model and higher resolution, nested limited area models. While the climate model does not simulate the timing and location of the cyclone and associated precipitation as accurately as the NWP simulations, the total accumulated precipitation in all models is similar to the rain gauge estimate across England and Wales. The regional accumulation over the event is insensitive to horizontal resolution for grid spacings ranging from 90km to 4km. Secondly, the free-running climate model reproduces the statistical distribution of daily precipitation accumulations observed in the England-Wales precipitation record. The model distribution diverges increasingly from the record for longer accumulation periods with a consistent under-representation of more intense multi-day accumulations. This may indicate a lack of low-frequency variability associated with weather regime persistence. Despite this, the overall seasonal and annual precipitation totals from the model are still comparable to those from ERA-Interim

Comparison between the bivariate Weibull probability approach and linear regression for assessment of the long-term wind energy resource using MCP

A detailed investigation of a measure-correlate-predict (MCP) approach based on the bivariate Weibull (BW) probability distribution of wind speeds at pairs of correlated sites has been conducted. Since wind speeds are typically assumed to follow Weibull distributions, this approach has a stronger theoretical basis than widely used regression MCP techniques. Building on previous work that applied the technique to artificially generated wind data, we have used long-term (11 year) wind observations at 22 pairs of correlated UK sites. Additionally, 22 artificial wind data sets were generated from ideal BW distributions modelled on the observed data at the 22 site pairs. Comparison of the fitting efficiency revealed that significantly longer data periods were required to accurately extract the BW distribution parameters from the observed data, compared to artificial wind data, due to seasonal variations. The overall performance of the BW approach was compared to standard regression MCP techniques for the prediction of the 10 year wind resource using both observed and artificially generated wind data at the 22 site pairs for multiple short-term measurement periods of 1-12 months. Prediction errors were quantified by comparing the predicted and observed values of mean wind speed, mean wind power density, Weibull shape factor and standard deviation of wind speeds at each site. Using the artificial wind data, the BW approach outperformed the regression approaches for all measurement periods. When applied to the real wind speed observations however, the performance of the BW approach was comparable to the regression approaches when using a full 12 month measurement period and generally worse than the regression approaches for shorter data periods. This suggests that real wind observations at correlated sites may differ from ideal BW distributions and hence regression approaches, which require less fitting parameters, may be more appropriate, particularly when using short measurement periods

Looking at the weather The work of the Meteorological Office

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