Global multi-model projections of local urban climates
Global multi-model projections of local urban climates
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DOI：
10.1038/s41558-020-00958-8
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发表时间：
2021-01
影响因子：
30.7
通讯作者：
LE I Zhao
中科院分区：
文献类型：
--
作者：
LE I Zhao
针对气候驱动风险的有效城市规划依赖于针对建筑景观的稳健气候预测。由于全球尺度的地球系统模型中几乎普遍缺乏城市代表性，因此没有这种预测。在这里，我们结合联合收割机气候建模和数据驱动的方法，提供全球多模式预测城市气候在21世纪。结果表明，在气候变化的特定区域的城市变暖的特定水平的模型间的鲁棒性。在高排放情景下，到世纪末，美国、中东、北方中亚、中国东北部以及南美洲和非洲内陆的城市估计将经历超过4 K的大幅变暖--大于区域变暖--模型间的置信度很高。我们的研究结果强调了对气候敏感的发展和支持绿色基础设施干预作为大规模减少城市热应力的有效手段的多模型全球预测的迫切需要。
Effective urban planning for climate-driven risks relies on robust climate projections specific to built landscapes. Such projections are absent because of a near-universal lack of urban representation in global-scale Earth system models. Here, we combine climate modelling and data-driven approaches to provide global multi-model projections of urban climates over the twenty-first century. The results demonstrate the inter-model robustness of specific levels of urban warming over certain regions under climate change. Under a high-emissions scenario, cities in the United States, Middle East, northern Central Asia, northeastern China and inland South America and Africa are estimated to experience substantial warming of more than 4 K—larger than regional warming—by the end of the century, with high inter-model confidence. Our findings highlight the critical need for multi-model global projections of local urban climates for climate-sensitive development and support green infrastructure intervention as an effective means of reducing urban heat stress on large scales.