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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Multi-sensor assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for soil moisture and shallow groundwater estimation
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Multi-sensor assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for soil moisture and shallow groundwater estimation

机译:SMOS亮度温度的多传感器同化和宽容土壤水分和浅层地下水估计

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摘要

The Gravity Recovery and Climate Experiment (GRACE) mission provided monthly global estimates of the vertically integrated terrestrial water storage with about 300-400-km horizontal resolution between 2002 and 2017. Since 2009, the Soil Moisture and Ocean Salinity (SMOS) mission observes global L-band brightness temperatures, which are sensitive to near-surface soil moisture, with a revisit time of 1-3 days at a nominal 43-km spatial resolution. This work investigates if the multi-sensor assimilation of these observations into the Catchment land surface model can improve the estimation of 0-5 cm "surface" soil moisture, 0-100 cm "root-zone" soil moisture, and shallow (unconfined) groundwater levels. Single-sensor GRACE or SMOS assimilation and multi-sensor GRACE + SMOS assimilation experiments were performed over the continental U.S. for 6 years (July 2010 June 2016). GRACE data assimilation mostly improves estimates of shallow groundwater, whereas SMOS data assimilation mainly improves estimates of surface soil moisture. The benefits introduced by the single-sensor assimilation are merged in the multi-sensor assimilation experiment, suggesting that better and more consistent soil moisture and groundwater estimates can be achieved when multiple observation types are assimilated. Interestingly, in the multi-sensor GRACE + SMOS experiment, the water storage increments introduced by the GRACE analysis and the SMOS analysis are anti-correlated. That is, when the GRACE assimilation increments remove water from the overall profile storage, the SMOS assimilation increments add water to it, and vice versa. This anti-correlation could be caused by the SMOS analysis trying to undo the increments from the GRACE analysis.
机译:重力恢复和气候实验(Grace)使命为2002年至2017年间的垂直综合陆地储存的全球估计提供了大约300-400公里的横向分辨率。自2009年以来,土壤水分和海洋盐度(SMOS)使命观察全球L波段亮度温度,对近表面土壤水分敏感,重新审视时间为1-3天,以标称为43 km空间分辨率。这项工作调查了这些观察到集水区面积模型的多传感器同化,可以改善0-5厘米“表面”土壤水分,0-100cm“根区”土壤水分,浅(无排成)地下水位。单传感器恩典或SMOS同化和多传感器Grace + SMOS同化实验是在美国大陆美国进行的6年(2016年6月2010年6月)。 Grace Data Assmilation大多提高了浅地下水的估计,而SMOS数据同化主要提高了表面土壤水分的估计。单传感器同化引入的益处在多传感器同化实验中合并,表明当多种观察类型被同化时,可以实现更好,更一致的土壤水分和地下水估计。有趣的是,在多传感器Grace + SMOS实验中,由Grace分析和SMOS分析引入的储水增量是反相关的。也就是说,当优雅同化增量从整体轮廓存储中移除水时,SMOS同化增量增加水,反之亦然。这种反相关可能是由SMOS分析引起的,试图撤消Grace分析中的增量。

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