| 路面气象数值预报模型及性能检验 |
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| 引用本文： | 孟春雷,张朝林.路面气象数值预报模型及性能检验[J].应用气象学报,2012,23(4):451-458. |
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| 作者姓名： | 孟春雷 张朝林 |
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| 作者单位： | 1.中国气象局北京城市气象研究所，北京 100089 |
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| 基金项目： | 资助项目：国家自然科学基金青年科学基金项目（41005056） |
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| 摘 要： | 该文基于通用陆面模式 (CoLM) 发展了精细化路面参数数值预报模型 (BJ-ROME)。该模型可以预报路面温度、积雪厚度、积冰厚度以及积水厚度。模型不仅考虑了路面的不透水性、相对较低反照率、低热容以及高热导率等特征，还考虑了城市人为热的影响。模型采用北京市气象局快速更新循环预报系统 (BJ-RUC) 产生的气象强迫场驱动，预报时间跨度为24 h，更新时间为3 h。采用北京地区芬兰Vaisala公司路面观测站2009年8月9—24日路面温度及2010年1月3—4日积雪厚度观测结果对模型预报结果进行验证，同时进行了敏感性试验。结果表明:无论是在晴空还是降水的气象条件下，BJ-ROME均能较准确地预报路面温度极值以及日变化。BJ-ROME还可以较准确地模拟积雪厚度的最大值以及随时间变化情况。
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| 关 键 词： | 路面温度 积雪厚度 人为热 路面蒸发 |
| 收稿时间： | 6/4/2011 12:00:00 AM |
Development and Verification of a Numerical Forecast Model for Road Meteorological Services |
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| Meng Chunlei and Zhang Chaolin.Development and Verification of a Numerical Forecast Model for Road Meteorological Services[J].Quarterly Journal of Applied Meteorology,2012,23(4):451-458. |
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| Authors: | Meng Chunlei and Zhang Chaolin |
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| Institution: | 1.Institute of Urban Meteorology, CMA, Beijing 1000892.Department of Earth Sciences, National Natural Science Foundation of China, Beijing 100085 |
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| Abstract: | Accurate road meteorology forecast and road traffic information are very important to road transportation security. Road surface temperature is a crucial parameter in traffic weather forecast. Now there are three main kinds of road surface parameters forecast model: Statistical model, GIS-based model and physical model. Physical model is widely used and it mainly considers the road surface energy balance model and the effect of anthropogenic heat. In 2008, based on the rapid update cycling forecast system (BJ-RUC), the road weather information system is developed and run operationally by the Institute of Urban Meteorology. Since 2007, Beijing Meteorological Bureau has established 18 weather stations along the express way using the apparatus manufactured by ROSA Vaisala in Finland, and established 8 visibility observation stations using the digital visibility sensor. These all make the fine traffic weather forecast and operational run possible.A fine numerical model for urban road surface temperature (RST), snow depth and ice depth prediction (BJ-ROME) is developed based on Common Land Model (CoLM). The model is developed according to characteristics of the road surface, and based on the data of express way weather observation and fine land surface data of Beijing. The model is forced by the meteorological data output from BJ-RUC, and the forecast and update time span is 24 hours and 3 hours, respectively. The model is validated using in-situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. The sensitivity analysis is also implemented.Nine sites are chosen to validate the RST prediction results of BJ-ROME. The validation time is during 9—24 Aug 2009, when the RST is very high in Beijing. Four sites, i.e., Xihongmen, Wenyuhe, Xiguan and Lugouqiao are chosen to validate the snow depth prediction results of BJ-ROME. The validation time is during 2—5 Jan 2010, when a big snowfall happens in Beijing. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation and maximum value of RST both under clear-sky and rainfall conditions. The validation results also indicate that BJ-ROME can successfully simulate the accumulation time and the variation and maximum value of snow depth. The results of sensitivity analysis indicate that road surface evaporation and the anthropogenic heat are very important in road surface temperature forecast. The forecast results of BJ-ROME can be used as an important reference to take measures by traffic administration department and road administration department.In the near future, BJ-ROME will be coupled in double direction with BJ-RUC to improve the forecast. The anthropogenic heat (AH) should be parameterized more precisely, and the variational assimilation algorithm should be used to assimilate the RST observations. The predicting performance of water depth of BJ-ROME should also be validated. |
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| Keywords: | road surface temperature snow depth anthropogenic heat road surface evaporation |
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