Spatial representativeness of soil moisture using in situ, remote sensing, and land reanalysis data
Spatial representativeness of soil moisture using in situ, remote sensing, and land reanalysis data
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DOI：
10.1002/2015jd023305
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发表时间：
2015-04
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影响因子：
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通讯作者：
Nadine Nicolai-Shaw;M. Hirschi;H. Mittelbach;S. Seneviratne
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文献类型：
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作者：
Nadine Nicolai-Shaw;M. Hirschi;H. Mittelbach;S. Seneviratne
本研究基于一系列的数据集，研究了北美地区土壤绝对水分的时间动态及其时间异常的空间代表性。我们使用三个主要数据来源：现场观测、欧洲航天局气候变化基本气候可变土壤湿度倡议(ECV-SM)的遥感数据集，以及欧洲中期天气预报中心ERA-LAND的陆地表面模型估计。对三个土壤水分数据源在现场位置以及全网格产品进行了相互比较。应用的方法使我们能够量化土壤水分的空间足迹。在现场位置，ECV-SM和ERA-LAND产品在绝对土壤湿度方面表现相似，而对于时间异常，ECV-SM产品在空间代表性上与现场数据更相似。当考虑ECV-SM和ERA-LAND产品的所有网格单元来计算空间代表性时，我们发现绝对值的空间代表性差异最大。单一产品之间空间代表性的差异可能与其一些内在特征有关，即对于ECV-SM，在地形复杂的地形和植被密集的地区相似性较低，而对于ERA-Land，平滑的模型地形和地表属性影响土壤水分及其空间代表性。此外，我们还表明，应用的方法是稳健的，可以用于分析现有网络，以深入了解更高的站点密度将是最有利的位置。
This study investigates the spatial representativeness of the temporal dynamics of absolute soil moisture and its temporal anomalies over North America based on a range of data sets. We use three main data sources: in situ observations, the remote‐sensing‐based data set of the European Space Agency Climate Change Initiative on the Essential Climate Variable soil moisture (ECV‐SM), and land surface model estimates from European Centre for Medium‐Range Weather Forecasts's ERA‐Land. The intercomparisons of the three soil moisture data sources are performed at the in situ locations as well as for the full‐gridded products. The applied method allows us to quantify the spatial footprint of soil moisture. At the in situ locations it is shown that for absolute soil moisture the ECV‐SM and ERA‐Land products perform similarly, while for the temporal anomalies the ECV‐SM product shows more similarity in spatial representativeness with the in situ data. When taking into account all grid cells of the ECV‐SM and ERA‐Land products to calculate spatial representativeness, we find the largest differences in spatial representativeness for the absolute values. The differences in spatial representativeness between the single products can be related to some of their intrinsic characteristics, i.e., for ECV‐SM low similarities are found in topographically complex terrain and areas with dense vegetation, while for ERA‐Land the smoothed model topography and surface properties affect soil moisture and its spatial representativeness. Additionally, we show that the applied method is robust and can be used to analyze existing networks to provide insight into the locations in which higher station density would be of most benefit.