首页> 外文会议>2011 IEEE International Geoscience Remote Sensing Symposium >Improving land surface energy and water fluxes simulation over the Tibetan Plateau with using a land data assimilation system
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Improving land surface energy and water fluxes simulation over the Tibetan Plateau with using a land data assimilation system

机译:利用土地数据同化系统改善青藏高原的地表能量和水通量模拟

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The land-atmosphere interaction in the Tibetan Plateau plays an important role in the Asian summer monsoon and the global energy and water cycle. This study presents a method to improve the land surface water and energy fluxes simulation by using a land data assimilation system (LDAS), which merging microwave remote sensing data and GCM output into a land surface model. NCEP reanalysis data is used as the background field and also as the meteorological forcing for the land surface model. Two experiments were designed as by driving LDAS-UT with two sets of atmospheric forcing data, (1) with in situ observed forcing data and (2) with NCEP reanalysis data at Gaize and Naqu sites. Results show that LDAS is able to estimate land surface soil moisture and energy fluxes accurately. The RMSE of soil moisture simulation is around 0.03–0.05 and RMSE of net radiation simulation is around 30W/M2. This study reveals the potential for using satellite remote sensing data to improve land surface fluxes estimation.
机译:青藏高原的土地-大气相互作用在亚洲夏季风和全球能源与水循环中起着重要作用。这项研究提出了一种利用土地数据同化系统(LDAS)改进土地表面水和能量通量模拟的方法,该系统将微波遥感数据和GCM输出合并到土地表面模型中。 NCEP重新分析数据被用作背景场,也被用作陆地表面模型的气象强迫。通过用两组大气强迫数据驱动LDAS-UT,设计了两个实验,(1)使用在Gaize和Naqu站点的现场观测到的强迫数据,以及(2)使用NCEP再分析数据。结果表明,LDAS能够准确估算土地表层土壤的水分和能量通量。土壤水分模拟的RMSE约为0.03-0.05,净辐射模拟的RMSE约为30W / M 2 。这项研究揭示了使用卫星遥感数据来改善地表通量估计的潜力。

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