01921nas a2200265   4500008004100000022001300041245007100054210006600125260001200191300001600203490000800219520115000227653002401377653000901401653001401410653002501424653004301449653002101492100001501513700001201528700001901540700001501559700001401574856006701588       2019                        eng d  a0306261900aA novel approach for selecting typical hot-year (THY) weather data0 anovel approach for selecting typical hotyear THY weather data  c03/2019  a1634 - 16480 v2423 a<p>The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.</p>10aActual weather data10adest10aHeat wave10aMultiyear simulation10aResidential indoor thermal environment10aTypical hot year1 aGuo, Siyue1 aYan, Da1 aHong, Tianzhen1 aXiao, Chan1 aCui, Ying  uhttps://linkinghub.elsevier.com/retrieve/pii/S030626191930465902060nas a2200265   4500008004100000245011700041210006900158260001200227300001200239490000800251520123400259653002401493653002401517653001501541653002501556653001801581653001701599100001401616700001201630700001901642700001501661700001401676700001401690856009001704       2017                        eng d00aComparison of typical year and multiyear building simulations using a 55-year actual weather data set from China0 aComparison of typical year and multiyear building simulations us  c06/2017  a890-9040 v1953 a<p>Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.</p>10aActual weather data10abuilding simulation10aenergy use10aMultiyear simulation10aPeak load  10aTypical year1 aCui, Ying1 aYan, Da1 aHong, Tianzhen1 aXiao, Chan1 aLuo, Xuan1 aZhang, Qi  uhttps://simulationresearch.lbl.gov/publications/comparison-typical-year-and-multiyear01971nas a2200193   4500008004100000245013400041210006900175520127100244653001201515653002001527653001701547653004101564653002201605100001401627700001201641700001901653700001601672856008901688       2017                        eng d00aTemporal and spatial characteristics of the urban heat island in Beijing and the impact on building design and energy performance0 aTemporal and spatial characteristics of the urban heat island in3 a<p>With the increased urbanization in most countries worldwide, the urban heat island (UHI) effect, referring to the phenomenon that an urban area has higher ambient temperature than the surrounding rural area, has gained much attention in recent years. Given that Beijing is developing rapidly both in urban population and economically, the UHI effect can be significant. A long-term measured weather dataset from 1961 to 2014 for ten rural stations and seven urban stations in Beijing, was analyzed in this study, to understand the detailed temporal and spatial characteristics of the UHI in Beijing. The UHI effect in Beijing is significant, with an urban-to-rural temperature difference of up to 8℃ during the winter nighttime. Furthermore, the impacts of UHIs on building design and energy performance were also investigated. The UHI in Beijing led to an approximately 11% increase in cooling load and 16% decrease in heating load in the urban area compared with the rural area, whereas the urban heating peak load decreased 9% and the cooling peak load increased 7% because of the UHI effect. This study provides insights into the UHI in Beijing and recommendations to improve building design and decision-making while considering the urban microclimate.</p>10abeijing10abuilding design10aMicroclimate10aTemporal and spatial characteristics10aurban heat island1 aCui, Ying1 aYan, Da1 aHong, Tianzhen1 aMa, Jingjin  uhttps://simulationresearch.lbl.gov/publications/temporal-and-spatial-characteristics