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Comparison of the Impact of Global Climate Changes and Urbanization on Summertime Future Climate in the Tokyo Metropolitan Area

机译:全球气候变化和城市化对东京都会区夏季未来气候的影响比较

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摘要

In this study, the impact of global climate change and anticipated urbanization over the next 70 years is estimated with regard to the summertime local climate in the Tokyo metropolitan area (TMA), whose population is already near its peak now. First,five climate projections for the 2070s calculated with the aid of general circulation models (GCMs) are used for dynamical downscaling experiments to evaluate the impact of global climate changes using a regional climate model. Second, the sensitivity of future urbanization until the 2070s is examined assuming a simple developing urban scenario for the TMA. These two sensitivity analyses indicate that the increase in the surface air temperature from the 1990s to the 2070s is about 2.0°C as a result ofglobal climate changes under the A1B scenario in the Intergovernmental Panel on Climate Change’s Special Report on Emissions Scenarios (SRES) and about 0.5°C as a result of urbanization. Considering the current urban heat island intensity (UHII) of 1.0°C, the possible UHII in the future reaches an average of 1.5°C in the TMA. This means that the mitigation of the UHII should be one of the ways to adapt to a local temperature increase caused by changes in the future global climate. In addition, theestimation of temperature increase due to global climate change has an uncertainty of about 2.0°C depending on the GCM projection, suggesting that the local climate should be projected on the basis of multiple GCM projections.
机译:在本研究中,针对东京都会区(TMA)的夏季局部气候,估计了未来70年全球气候变化和预期的城市化的影响,东京都会区的人口目前已接近峰值。首先,借助通用循环模型(GCM)计算出的2070年代的五个气候预测被用于动态降尺度实验,以使用区域气候模型评估全球气候变化的影响。其次,假设TMA的城市发展情况简单,那么研究2070年代之前的未来城市化的敏感性。这两项敏感性分析表明,由于政府间气候变化专门委员会《排放情景特别报告》(SRES)中的A1B情景下的全球气候变化,从1990年代到2070年代的地面空气温度升高约2.0°C。由于城市化,温度约为0.5°C。考虑到当前的城市热岛强度(UHII)为1.0°C,未来可能的UHII在TMA中平均达到1.5°C。这意味着,缓解UHII应该是适应由未来全球气候变化引起的局部温度升高的方法之一。此外,根据全球气候变化的预测,全球气候变化引起的温度升高的估计不确定性约为2.0°C,这表明应根据多个全球气候变化的预测来预测当地气候。

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