CoLM模式地表温度变分同化研究

孟春雷; 张朝林; 刘长友

doi:10.3878/j.issn.1006-9895.2012.11184

CoLM模式地表温度变分同化研究

doi: 10.3878/j.issn.1006-9895.2012.11184

1.
中国气象局北京城市气象研究所,北京 100089
2.
国家自然科学基金委员会地球科学部,北京 100085
3.
国家气候中心,北京 100081

基金项目: 国家自然科学基金资助项目41005156,国家科技支撑计划重点项目2008BAC37B04

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出版历程
- 收稿日期: 2011-10-09
- 修回日期: 2012-02-10

Variational Assimilation of Land Surface Temperature from Common Land Model (CoLM)

1.
Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089
2.
Department of Earth Sciences, National Natural Science Foundation of China, Beijing 100085
3.
National Climate Center, China Meteorological Administration, Beijing 100081

摘要

摘要: 本文采用变分方法对通用陆面模式 (CoLM) 中的地表温度进行同化.同化伴随约束条件采用CoLM模式中的地表及植被能量平衡方程,调节因子采用裸土及植被蒸发比.采用美国通量网 (AmeriFlux) 中的Bonville站数据对同化方法进行了单点验证,验证结果表明同化后地表温度以及蒸散结果更加接近于实测值.选取中国华北地区对同化方法进行区域验证,结果显示每天仅采用白天一次观测值对地表温度进行同化的方法是有效的.通过对同化前后地表温度误差直方图比较可以发现,在有MODIS观测值的区域,同化后白天地表温度误差大大降低,同时,同化后地表蒸散空间分布图也发生了变化.单点验证以及区域验证结果都表明了变分同化方法是可靠的.变分同化方法可以改进陆面模式模拟结果,对于地表过程研究中的植被生态、水文等研究具有重要意义,同时,陆面模式可以与数值预报模式进行耦合,改进数值预报结果.
- 变分同化 /
- CoLM模式 /
- 地表温度 /
- 蒸发比 /
- 蒸散
Abstract: A variational data assimilation algorithm for assimilating land surface temperature (LST) in the Common Land Model (CoLM) is implemented using the land surface and canopy energy balance as the adjoint physical constraint. In this data assimilation algorithm, the evaporative fraction (EF) of soil and canopy is adjusted according to the surface temperature observations. The analysis results from CoLM with the LST assimilation algorithm are well compared with the field observations from AmeriFlux data at Bondville site. This algorithm is also tested at the regional scale located in East China. These results indicate that the surface temperature assimilation method is efficient and effective when only one-time observational data per day are available. From the histogram of the LST error, it can be concluded that the LST after assimilation is improved much compared with the MODIS observations especially in the daytime. The evapotranspiration patterns also change much after the assimilation. All these can prove the robustness of the algorithm which this paper proposes in assimilation applications to the CoLM. The variational assimilation method this paper develops can improve the simulation results of land surface model, and has an important meaning to the land surface processes such as land surface hydrology and vegetation ecology etc. Meanwhile, the land surface model also could be coupled with the numerical prediction model, and then the variational algorithm also can improve the results of numerical forecast.
- variational data assimilation /
- Common Land Model (CoLM) /
- land surface temperature /
- evaporative fraction /
- evapotranspiration

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