High road-surface temperature due to heat waves can lead to dangerous driving conditions such as tire blowouts and deformation induced by thermal stress on the roads. In this study, a Mobile Observation Vehicle datase...High road-surface temperature due to heat waves can lead to dangerous driving conditions such as tire blowouts and deformation induced by thermal stress on the roads. In this study, a Mobile Observation Vehicle dataset, with high spatial and temporal resolutions for the heat-wave episode that occurred on 16–17 August 2018, is used to understand environmental characteristics on urban road-surface and air temperatures in Seoul. This study demonstrates that the magnitude of urban road-surface temperature is dependent on the differences in incoming solar radiation due to screening of high-rise buildings in the Gangnam area, and is associated with the topographical features in the Gangbuk area. The road-surface temperature in the section of darker-colored asphalts was higher than that of lighter-colored asphalts, with a mean difference of 6.8°C, and both surface and air temperatures on the iron plate were highest, with means of 51.7°C and 35.1°C,respectively. In addition, during the water-sprinkling period, road-surface temperature was cooled by about 8.7°C(19%) compared with that in the period without water-sprinkling, but there was no significant change in air temperature. The current results could be practically used to improve roadsurface temperature prediction models for civil engineers or road managers.展开更多
在全球气候变暖和快速城市化的背景下,极端高温事件频发已成为威胁人类健康和社会可持续发展的重要问题,尤其是在人口稠密、经济发达的长江三角洲(简称“长三角”)地区。本研究基于1961-2020年长三角地区气象观测数据,系统分析了日最高...在全球气候变暖和快速城市化的背景下,极端高温事件频发已成为威胁人类健康和社会可持续发展的重要问题,尤其是在人口稠密、经济发达的长江三角洲(简称“长三角”)地区。本研究基于1961-2020年长三角地区气象观测数据,系统分析了日最高气温、日平均气温及高温热浪指数的变化趋势。同时,结合WRF(Weather Research and Forecasting)模式开展敏感性试验,评估城市下垫面对极端高温的影响。结果表明:(1)长三角地区的日最高气温和日平均气温在过去几十年间均呈显著上升趋势,其中日最高气温的增幅[0.194℃·(10a)^(-1)]高于日平均气温[0.187℃·(10a)^(-1)]。通过Pettitt检验,研究发现两类气温序列在1993年发生显著突变,突变前气温呈下降趋势,而突变后则转为上升趋势。(2)高温热浪发生频次、持续时间和强度分别以0.190 time·(10a)^(-1)、0.475 d·(10a)^(-1)和0.772℃·time^(-1)·(10a)^(-1)的速率显著上升。通过分析热浪指数的突变情况,发现热浪指数的突变点出现在2000年,滞后于气温的突变点。突变前,热浪指数呈现下降趋势,而突变后则转为上升趋势,且热浪强度的增幅远超频次和持续时间。(3)进一步分析表明,城市化对气温和高温热浪的影响显著。城市站点的日最高气温[0.243℃·(10a)^(-1)]和日平均气温[0.261℃·(10a)^(-1)]上升速率均显著高于农村站点[0.171℃·(10a)^(-1)、0.167℃·(10a)^(-1)],表明城市化对增温具有放大作用。同时,城市站点的高温热浪指数上升趋势明显强于农村站点,表明城市化可能增强了高温热浪的发生。(4)数值模拟表明,WRF模式能够较好地再现模拟区域的气温变化特征。城市下垫面的存在显著影响了城市站点的气温,尤其在高温日时期,在夜间表现更明显。城市下垫面通过改变地表能量收支(如感热通量、潜热通量和地表储热),增强了城市站点在高温日时期的地表能量变化,加剧了在高温日时期的气温,而农村站点受城市化影响较小,表明城市化过程对城市区域的高温影响更加明显。综上所述,长三角地区的极端高温事件频次、强度和持续时间在过去几十年间呈现显著上升趋势,且城市化在其中发挥了重要的放大作用。随着城市化的进一步发展,极端高温事件的频率和强度可能持续增加,因此,制定有效的适应策略和缓解措施至关重要。展开更多
本研究旨在提升湖南省盛夏(7、8月)高温过程的延伸期预报技巧。本文利用1999—2022年湖南省97个站点逐日最高气温资料以及次季节-季节(sub-seasonal to seasonal prediction,S2S)模式数据中欧洲中期天气预报中心(ECMWF)和美国国家环境...本研究旨在提升湖南省盛夏(7、8月)高温过程的延伸期预报技巧。本文利用1999—2022年湖南省97个站点逐日最高气温资料以及次季节-季节(sub-seasonal to seasonal prediction,S2S)模式数据中欧洲中期天气预报中心(ECMWF)和美国国家环境预报中心(NCEP)两种模式预报产品,并基于模式温度与环流预报产品提取物理因子,结合卷积神经网络(convolutional neural network,CNN)构建了湖南省盛夏高温过程的预报模型(high temperature prediction model,HTPM);对订正后的S2S模式和构建的预报模型结果进行集成,以实现对区域高温过程较为稳定的相对高技巧预报。结果表明:S2S模式的原始预报技巧较低,偏差订正能显著提高预报效果,但存在较高的空报率;基于ECMWF的S2S数据训练的高温预报模型(HTPM-ECS2S)和基于NCEP的S2S数据训练的高温预报模型(HTPM-NCEPS2S)能有效捕捉高温事件,在高温预报中具有较高的预报技巧;集成方案有效整合了多模型优点,可提升预报的准确性和可靠性。展开更多
基金supported by the Korea Meteorological Administration Research and Development Program’s‘Research and Development for KMA Weather,Climate,and Earth system Services-Development and Application of Monitoring,Analysis and Prediction Technology for HighImpact Weather’[KMA2018-00123]
文摘High road-surface temperature due to heat waves can lead to dangerous driving conditions such as tire blowouts and deformation induced by thermal stress on the roads. In this study, a Mobile Observation Vehicle dataset, with high spatial and temporal resolutions for the heat-wave episode that occurred on 16–17 August 2018, is used to understand environmental characteristics on urban road-surface and air temperatures in Seoul. This study demonstrates that the magnitude of urban road-surface temperature is dependent on the differences in incoming solar radiation due to screening of high-rise buildings in the Gangnam area, and is associated with the topographical features in the Gangbuk area. The road-surface temperature in the section of darker-colored asphalts was higher than that of lighter-colored asphalts, with a mean difference of 6.8°C, and both surface and air temperatures on the iron plate were highest, with means of 51.7°C and 35.1°C,respectively. In addition, during the water-sprinkling period, road-surface temperature was cooled by about 8.7°C(19%) compared with that in the period without water-sprinkling, but there was no significant change in air temperature. The current results could be practically used to improve roadsurface temperature prediction models for civil engineers or road managers.
文摘在全球气候变暖和快速城市化的背景下,极端高温事件频发已成为威胁人类健康和社会可持续发展的重要问题,尤其是在人口稠密、经济发达的长江三角洲(简称“长三角”)地区。本研究基于1961-2020年长三角地区气象观测数据,系统分析了日最高气温、日平均气温及高温热浪指数的变化趋势。同时,结合WRF(Weather Research and Forecasting)模式开展敏感性试验,评估城市下垫面对极端高温的影响。结果表明:(1)长三角地区的日最高气温和日平均气温在过去几十年间均呈显著上升趋势,其中日最高气温的增幅[0.194℃·(10a)^(-1)]高于日平均气温[0.187℃·(10a)^(-1)]。通过Pettitt检验,研究发现两类气温序列在1993年发生显著突变,突变前气温呈下降趋势,而突变后则转为上升趋势。(2)高温热浪发生频次、持续时间和强度分别以0.190 time·(10a)^(-1)、0.475 d·(10a)^(-1)和0.772℃·time^(-1)·(10a)^(-1)的速率显著上升。通过分析热浪指数的突变情况,发现热浪指数的突变点出现在2000年,滞后于气温的突变点。突变前,热浪指数呈现下降趋势,而突变后则转为上升趋势,且热浪强度的增幅远超频次和持续时间。(3)进一步分析表明,城市化对气温和高温热浪的影响显著。城市站点的日最高气温[0.243℃·(10a)^(-1)]和日平均气温[0.261℃·(10a)^(-1)]上升速率均显著高于农村站点[0.171℃·(10a)^(-1)、0.167℃·(10a)^(-1)],表明城市化对增温具有放大作用。同时,城市站点的高温热浪指数上升趋势明显强于农村站点,表明城市化可能增强了高温热浪的发生。(4)数值模拟表明,WRF模式能够较好地再现模拟区域的气温变化特征。城市下垫面的存在显著影响了城市站点的气温,尤其在高温日时期,在夜间表现更明显。城市下垫面通过改变地表能量收支(如感热通量、潜热通量和地表储热),增强了城市站点在高温日时期的地表能量变化,加剧了在高温日时期的气温,而农村站点受城市化影响较小,表明城市化过程对城市区域的高温影响更加明显。综上所述,长三角地区的极端高温事件频次、强度和持续时间在过去几十年间呈现显著上升趋势,且城市化在其中发挥了重要的放大作用。随着城市化的进一步发展,极端高温事件的频率和强度可能持续增加,因此,制定有效的适应策略和缓解措施至关重要。
文摘本研究旨在提升湖南省盛夏(7、8月)高温过程的延伸期预报技巧。本文利用1999—2022年湖南省97个站点逐日最高气温资料以及次季节-季节(sub-seasonal to seasonal prediction,S2S)模式数据中欧洲中期天气预报中心(ECMWF)和美国国家环境预报中心(NCEP)两种模式预报产品,并基于模式温度与环流预报产品提取物理因子,结合卷积神经网络(convolutional neural network,CNN)构建了湖南省盛夏高温过程的预报模型(high temperature prediction model,HTPM);对订正后的S2S模式和构建的预报模型结果进行集成,以实现对区域高温过程较为稳定的相对高技巧预报。结果表明:S2S模式的原始预报技巧较低,偏差订正能显著提高预报效果,但存在较高的空报率;基于ECMWF的S2S数据训练的高温预报模型(HTPM-ECS2S)和基于NCEP的S2S数据训练的高温预报模型(HTPM-NCEPS2S)能有效捕捉高温事件,在高温预报中具有较高的预报技巧;集成方案有效整合了多模型优点,可提升预报的准确性和可靠性。
