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Effect of climate change on building cooling loads in Tokyo in the summers of the 2030s using dynamically downscaled GCM data

机译:使用动态缩减的GCM数据,在2030年代夏季,气候变化对东京建筑制冷负荷的影响

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In this study, we dynamically downscaled the Model for Interdisciplinary Research on Climate version 4 (MIROC4h) in August for the present (2001-2010) and the near future (2026-2035). We selected weather data that represent the average weather conditions during 10-year periods among the results of down scaled MIROC4h. Correcting the selected weather data with observations to reduce bias of both regional climate model (RCM) and global climate model (GCM), we constructed a prototype of the near future design weather data of the 2030s. We conducted building energy simulations using the prototype of design weather data to assess the impact of climate change on energy consumption of a two-story detached house in Tokyo. Under these conditions, total sensible heat load in August increased 26%, and the latent heat load increased 10%. (C) 2015 Published by Elsevier B.V.
机译:在本研究中,我们针对当前(2001-2010年)和不远的将来(2026年至2035年)在八月动态缩小了气候研究跨学科研究模型(MIROC4h)的规模​​。我们从缩小的MIROC4h结果中选择了代表10年平均天气状况的天气数据。我们用观测值校正了选定的天气数据,以减少区域气候模型(RCM)和全球气候模型(GCM)的偏差,我们构建了2030年代近期设计天气数据的原型。我们使用设计天气数据的原型进行了建筑能耗模拟,以评估气候变化对东京两层独立式住宅能耗的影响。在这些条件下,八月份的总显热负荷增加了26%,潜热负荷增加了10%。 (C)2015由Elsevier B.V.发布

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