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城市化对成都地区夏季气候变化影响的数值模拟研究 被引量:5

Simulation of the Impact of Urbanization on Summer Climate in Chengdu
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摘要 为探讨成都城市化对成都地区夏季气候变化的影响,利用耦合了单层城市冠层模型的中尺度模式WRF对成都地区1991~2000年10年夏季进行高精度(2 km)的数值模拟,并进行有城市下垫面的控制试验和无城市下垫面的敏感性试验。结果表明:(1)WRF模式较好模拟出成都地区的夏季气温特征,城市化带来的热岛效应十分明显,且夜间城市热岛强度高于白天;(2)城市化使成都地区形成了城市干岛,地表水汽显著减小而一定高度处水汽增加;(3)城市建筑物的增加使城区及城区下风方向风速减小,建筑物的阻挡作用使主导风产生绕流,城区迎风侧及两边风速略微增加;(4)城市下垫面使潜热通量减小,感热通量增大,城市下垫面在白天吸收净辐射能量并将部分能量存储为储热项,并通过感热、潜热加热大气,夜间则作为热源释放热量。 In order to investigate the impact of urbanization on summer climate in Chengdu,WRF and its coupled Urban Canopy Models were used to simulate summer climate in Chengdu from 1991 to 2000. And the data of urban land use in Chengdu and the surrounding region was replaced by that of irrigation,to study the urbanization impact on summer climate and explore its effect mechanism. The results are shown as follows :( 1) The WRF model could simulate the main distribution of climatological summer temperature,which is very close to observation. Urbanization increased the urban heat island effect( UHI),and the surface UHI much stronger during night.( 2) Urbanization results in dry island in Chengdu. Water vapor content decrease obviously on the surface and increases at a certain height.( 3) The wind speed over urban district and its leeward district decreases. Urban building ma prevailing wind flow around,but the wind speed of the windward and two sides slightly increase in Chengdu district.( 4) The expansion of urban changewith a significant increase of sensible heat flux and decrease of latent flux. The construction structures in the urban area absorbed a large amount of net radiation and stored part of them,which warm the surface atmosphere in the daytime in the form of latent and sensible heat flux and release heat content as heat source.
出处 《成都信息工程大学学报》 2016年第4期386-393,共8页 Journal of Chengdu University of Information Technology
基金 国家自然科学基金资助项目(41275033) 四川省教育厅重点资助项目(13ZA0076)
关键词 气象学 数值模拟 城市化 下垫面 WRF 气候变化 meteorology numerical simulation urbanization underlying surface the weather research forecasting model climate change
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