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作 者:刘彦华[1] 张述文[1] 毛璐[1] 薛宏宇[1]
机构地区:[1]兰州大学大气科学学院,甘肃省干旱气候变化与减灾重点实验室,甘肃兰州730000
出 处:《地球科学进展》2013年第8期913-922,共10页Advances in Earth Science
基 金:国家重点基础研究发展计划项目"突发性强对流天气演变机理和监测预报技术研究"(编号:2013CB430102);国家自然科学基金项目"有预报误差的土壤湿度估算研究"(编号:41075074)资助
摘 要:针对夏季土壤变干过程,利用观测系统模拟试验,比较离线的陆面模式(LSM)和耦合大气边界层的陆面模式(SCM)对土壤温度、湿度和地表热通量等陆面状态的模拟,然后借助数据同化方法,评估2类模式对陆面状态的估算能力。结果显示:2类模式除对地表长波辐射和感热通量的模拟差别较大外,对其余量则较小;只同化表层土壤湿度观测时,LSM对土壤湿度和感热通量的估算好于SCM,对土壤温度的估算则相反,而对潜热通量估算的差距很小;同时同化表层土壤温度、湿度观测会使地表热通量的估算差距增大;最后对2类模式不同表现的可能原因进行分析讨论。上述数值模拟和同化结果:当用某一类模式的模拟结果或同化产品为另一类不同模式提供初边界条件时必须注意它们之间的差异,避免出现输入量引起的模式状态量间的动力不协调现象。By using an observation system simulation experiment, the simulated soil moisture, soil temperature and surface heat fluxes are firstly compared for a period of soil drying process, respectively, from an offline Land Surface Model (LSM) and a Single Column Model (SCM) with coupled atmospheric boundary layer and LSM, and secondly, the ability of estimated land surface states are evaluated from the two models with the aid of data assimilation technique. The results show the differences of all the simulated variables are small except long-wave radiation and sensible heat fluxes being relatively large. For only the near-surface soil moisture observation assimilation, the estimated soil moisture and surface sensible heat flux with LSM are generally better than those with SCM, on the contrary, the estimated soil temperature with SCM is better, and the difference of estimated latent heat fluxes is small. However, the assimilation of both near-surface soil temperature and soil moisture observations at the same time will make the difference of heat flux estimates become large from the two models by the end of data assimilation cycle. Finally, the possible reasons for the different performances of the two models are investigated and analyzed by using the sensitivity tests. The above results imply that it should be careful when we use one-model output as another-model input, and avoid the dynamic inconsistency between the two-model states.
关 键 词:陆面模式 柱状模式 大气边界层 数值模拟 数据同化
分 类 号:P461.4[天文地球—大气科学及气象学]
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