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冰川冻土 ›› 2018, Vol. 40 ›› Issue (2): 322-334.doi: 10.7522/j.issn.1000-0240.2018.0037

• 寒区科学与技术 • 上一篇    下一篇

陆面模式CLM4.5在青藏高原土壤冻融期的偏差特征及其原因

李时越, 杨凯, 王澄海   

  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
  • 收稿日期:2017-09-23 修回日期:2018-01-17 出版日期:2018-04-25 发布日期:2018-07-02
  • 通讯作者: 王澄海,E-mail:wch@lzu.edu.cn E-mail:wch@lzu.edu.cn
  • 作者简介:李时越(1992-),女,陕西西安人,2015年在中国海洋大学获学士学位,现为兰州大学在读硕士研究生,从事数值模式、陆气相互作用研究.E-mail:lishy2015@lzu.edu.cn
  • 基金资助:
    国家自然科学基金项目(91437217;41275061;41471034)资助

Bias characteristics of land surface model (CLM4.5) over the Tibetan Plateau during soil freezing-thawing period and its causes

LI Shiyue, YANG Kai, WANG Chenghai   

  1. College of Atmospheric Sciences, Lanzhou University/Key Laboratory of Arid Climatic Change and Disaster Reduction of Gansu Province, Lanzhou 730000, China
  • Received:2017-09-23 Revised:2018-01-17 Online:2018-04-25 Published:2018-07-02

摘要: 利用中国区域地面气象要素数据集制作的大气强迫场驱动通用陆面模式CLM4.5(Community Land Model version 4.5)对青藏高原区域进行离线模拟试验,模拟结果与D66、沱沱河(TTH)和玛曲(Maqu)3个站点的观测资料以及GLDAS(Global Land Data Assimilation System)-CLM2模拟结果进行了对比,并分析了陆面模式对冻融过程中土壤温度和湿度模拟的偏差及其可能原因。结果表明:CLM4.5对土壤温度模拟较好(平均RMSE≈3℃),而GLDAS-CLM2计算的土壤温度偏高,偏差较大(平均RMSE>6℃),且其偏差大于CLM4.5,尤其在冻融期;CLM4.5能较好地模拟出冻融过程中土壤湿度季节变化,但土壤湿度的模拟值与观测值存在一定偏差(平均RMSE≈0.1 mm3·mm-3),GLDAS-CLM2不能反映出土壤湿度在冻融过程中的变化特征。CLM4.5的模拟偏差主要来自大气强迫场,而GLDAS-CLM2的偏差除了大气强迫场的不确定性外,还来自于模式冻融参数化方案的不完善。大气强迫场中的气温和降水对土壤温度和湿度的影响在冻融期和非冻融期表现不同。在非冻融期,土壤温度的模拟主要受气温的影响(r>0.6),气温偏差对土壤温度偏差的贡献率大于50%;土壤湿度的变化则主要受降水的影响,降水偏差对土壤湿度偏差的贡献率为20%~40%。在冻融期,受土壤水热相互作用的影响,气温和降水对土壤温度和湿度的作用效果减弱;土壤湿度的变化受气温影响显著,其贡献率为10%~20%。陆面模式中冻融参数方案的不完善是冻融过程中土壤温度和湿度偏差的重要来源之一。

关键词: 土壤温度, 土壤湿度, 陆面模式, 模拟偏差, 冻融过程

Abstract: The offline simulation experiments over the Tibetan Plateau was conducted through CLM4.5 (Community Land Model version 4.5) forced by China Meteorological Forcing Dataset. The observations in three sites (D66, TTH and Maqu) were chosen. The CLM4.5 simulation was compared to the observation and GLDAS (Global Land Data Assimilation System)-CLM2 simulation to analyze the biases of land surface model in simulating soil temperature and moisture during freezing-thawing process and its possible causes. The results showed that simulated soil temperature of CLM4.5 generally agreed with the observation (averaged RMSE ≈3℃), while soil temperature of GLDAS-CLM2 was higher than the observation with the biases (averaged RMSE >6℃) larger than that in CLM4.5, especially in freezing-thawing period; CLM4.5 can reproduce the seasonal variation of soil moisture, but content of soil moisture had some differences from the observation (averaged RMSE≈0.1 mm3·mm-3); GLDAS-CLM2 cannot reproduce the seasonal variation of soil moisture. The biases of CLM4.5 simulation mainly come from the uncertainties of atmospheric forcing, while the biases of GLDAS-CLM2 mainly come from the imperfection of frozen soil parameterizations, besides the uncertainties of atmospheric forcing. Air temperature and precipitation in atmospheric forcing have different effects on the performance of land surface model in freezing-thawing period and non-freezing-thawing period. In non-freezing-thawing period, simulation of soil temperature is mainly affected by the air temperature (r >0.6), especially before freezing period, the contribution of air temperature biases to soil temperature biases is larger than 50%, the variation of soil moisture is mainly influenced by precipitation, the contribution of precipitation biases to soil moisture biases is about 20%-40%. In freezing-thawing period, soil water flow and heat flux are coupled, the effects of air temperature and precipitation on soil temperature and moisture have reduced, the variation of soil moisture is significantly influenced by air temperature; contribution of air temperature biases to soil moisture biases is 10%-20%. The imperfection of freezing-thawing parameterization schemes in land surface model is the main factor for simulation biases of soil temperature and moisture during freezing-thawing; its effects are larger than the impacts of atmospheric forcing.

Key words: soil temperature, soil moisture, land surface model, simulation bias, freezing-thawing process

中图分类号: 

  • P435