通用陆面模式(CoLM)湖泊过程方案与性能评估  

The lake scheme of the Common Land Model and its performance evaluation

作　　者：戴永久 魏楠 黄安宁[2] 朱司光[3,4] 上官微 袁华 张树鹏 刘少锋 Yongjiu Dal;Nan We;Arming Huang;Siguang Zhu;Wei Shangguanl;Hua Yuanl;Shupeng Zhang;Shaofeng Liu(Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies,School of Atmospheric Sciences,Sun Yat-sen University,Guangzhou 510275,China;CMA-NJU Joint Laboratory for Climate Prediction Studies,School of Atmospheric Sciences,Nanjing University,Nanjing 210023,China;Key Laboratory of Meteorological Disaster,Ministry of Education（KLME）,International Joint Research Laboratory of Climate and Environment Change（ILCEC）/ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters（CIC-FEMD）,Nanjing University of Information Science and Technology,Nanjing 210044,China;College of Atmospheric Science,Nanjing University of Information Science and Technology,Nanjing 210044,China)

机构地区：[1]广东省气候变化与自然灾害研究重点实验室,中山大学大气科学学院,广州510275 [2]中国气象局-南京大学气候预测研究联合实验室,南京大学大气科学学院,南京210023 [3]南京信息工程大学气象灾害预报预警与评估协同创新中心,气候与环境变化国际合作联合实验室,气象灾害教育部重点实验室,南京210044 [4]南京信息工程大学大气科学学院,南京210044

出　　处：《科学通报》2018年第28期3002-3021,共20页Chinese Science Bulletin

基　　金：国家重点研发计划重点专项(2017YFA0604300,2016YFB0200801);国家自然科学基金重点项目(41730962)资助

摘　　要：对新版通用陆面模式CoLM(the Common Land Model)中的湖泊过程方案CoLM-Lake做了介绍,并通过10个湖泊的观测数据评估了它的模拟性能,同时讨论了模拟结果对模型关键参数的敏感性.模拟结果显示,CoLM-Lake对于浅湖的模拟效果非常理想,对于表层温度、湍流通量和垂直热力结构的量级和季节变化特征模拟的比较准确,同时对湖泊冻融循环过程给出了合理的刻画.CoLM-Lake对于深湖垂直结构及其变化的模拟亦较为准确,但对垂直混合强度的刻画仍然不足.虽然模型对于北美五大湖表层温度的模拟误差相对明显,但其量级和季节变化特征仍在合理的范围之内.通过模型参数的敏感性分析发现,动力学地表粗糙度可通过改变湍流通量的大小修正湖泊表层温度的模拟.湖泊深度、辐射消光系数和热力扩散系数可共同影响湖泊的热力结构.较大的湖泊深度,较小的消光系数和较大的热力扩散系数均使得湖泊内部传递和存储更多的热量,从而增加湖泊的热力惯性,降低湖泊各层温度的季节震荡和变化幅度,推迟湖泊冬季的冻结时间.湖泊到达最大密度时的温度受湖泊盐度的影响,调整此温度同样可使得模型的模拟结果得到改进.以上敏感性分析说明CoLM-Lake对于湖泊热力过程的模拟可以通过模型参数优化进行改进.总体上,CoLM-Lake可以合理地刻画各个湖泊的主要特征,模拟的误差均在参数取值的不确定性范围之内,因此CoLM-Lake在全球尺度上适用于对湖泊物理过程的模拟.The Common Land Model （CoLM） has been updated to a new version, but the lake scheme in CoLM （CoLM-Lake） has never been evaluated. This paper introduces the structure and physical processes of CoLM-Lake, and evaluates its simulation perfor- mance through the observations from 10 lakes over different regions. It also discusses the sensitivities of simulated results to some important parameters in the model. Results show that CoLM-Lake performs very well over the three shallow lakes （Kos- senblatter, Taihu and Sparkling Lake） where the model accurately captures the magnitudes and seasonal variations of lake sur- face temperature, turbulent fluxes, and vertical thermal structure. The freeze-thaw cycle of Sparkling Lake is reproduced at a reasonable level as well. Also, CoLM-Lake show acceptable performance in simulating vertical structures and their variations for deep lakes, although the vertical mixing strength remains underestimated. The biases of surface temperatures in the Great Lakes of North America are relatively larger, but the magnitudes and seasonal variations in temperature fall within a reasonable range. In general, CoLM-Lake is suitable for the simulation of lake physical processes on the global scale. The simulated results have strong sensitivities to some parameters with values that have large uncertainties. The surface roughness lengths determine the amounts of turbulent fluxes which are emitted into the atmosphere, and thus affecting the sim- ulated lake surface temperature. Although the surface roughness based on the dynamic diagnosis of lake properties in the model has made the simulated turbulent fluxes very accurate, the further adjustment of surface roughness can improve the realism of the simulated turbulent fluxes and temperature on lake surface. Lake depth, optical extinction coefficient and thermal diffusivity affect the simulated lake thermal structure from different angles. Lake depth determines the amount of water in vertical mixing; optical extinction coefficient determines

关 键 词：湖泊模型 陆面模式 模型评估 敏感性分析 

分 类 号：P343.3[天文地球—水文科学]