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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau
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Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau

机译:根据青藏高原中部土壤水分网络的观测评估AMSR-E取回和GLDAS模拟

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摘要

A multi-scale soil moisture and temperature monitoring network, consisting of 55 soil moisture and temperature measurement stations, has been established in central Tibetan Plateau (TP). In this study, the station-averaged surface soil moisture data from the network are used to evaluate four soil moisture products retrieved from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and four land surface modeling products from the Global Land Data Assimilation System (GLDAS). Major findings are (1) none of the four AMSR-E products provides reliable estimates in the unfrozen season, in terms of the mission requirement of the root mean square error (RMSE) < 0.06 m3m-3. These algorithms either evidently overestimate soil moisture or obviously underestimate it, although some of them showed the soil moisture dynamic range, indicating that the retrieval algorithms have much space to be improved for the cold semi-arid regions. (2) The four GLDAS models tend to systematically underestimate the surface soil moisture (0-5 cm) while well simulate the soil moisture for 20-40 cm layer. In comparison with the satellite surface soil moisture products, three among the four models give low RMSE and BIAS values, but still falling out of the acceptable range. The causes for the modeling biases in this cold region were discussed. Key Points Installed a dense soil moisture monitoring network on central Tibetan PlateauEvaluation of four AMSR-E retrieved soil moisture productsEvaluation of four GLDAS simulated soil moisture outputs
机译:在青藏高原中部建立了一个由55个土壤水分和温度测量站组成的多尺度土壤水分和温度监测网络。在这项研究中,该站的网络平均地表土壤湿度数据用于评估从高级微波扫描辐射计-地球观测系统(AMSR-E)检索到的四种土壤水分产品和从全球陆地数据中获取的四种陆地表面模拟产品同化系统(GLDAS)。主要发现是(1)就均方根误差(RMSE)<0.06 m3m-3的任务要求而言,四种AMSR-E产品都无法在未冻结的季节提供可靠的估计。这些算法要么明显高估了土壤湿度,要么明显低估了土壤湿度,尽管其中一些算法显示了土壤湿度的动态范围,这表明对于寒冷的半干旱地区,检索算法还有很大的改进空间。 (2)四种GLDAS模型倾向于系统地低估地表土壤水分(0-5 cm),同时很好地模拟20-40 cm层的土壤水分。与卫星表层土壤水分产品相比,这四个模型中的三个给出了较低的RMSE和BIAS值,但仍超出了可接受的范围。讨论了在这个寒冷地区建模偏见的原因。要点在青藏高原中部安装了密集的土壤水分监测网络评估四种AMSR-E回收的土壤水分产品评估四种GLDAS模拟的土壤水分输出

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