Multi-scale statistical properties of disaggregated SMOS soil moisture products in Australia
Multi-scale statistical properties of disaggregated SMOS soil moisture products in Australia
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DOI：
10.1016/j.advwatres.2019.103426
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发表时间：
2019-12
影响因子：
4.7
通讯作者：
M. Neuhauser;S. Verrier;O. Merlin;B. Molero;C. Suere;S. Mangiarotti
中科院分区：
文献类型：
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作者：
M. Neuhauser;S. Verrier;O. Merlin;B. Molero;C. Suere;S. Mangiarotti
土壤湿度对不同空间尺度（从大陆全球尺度到局部流域）的气候、水文和农学产生强烈影响。无源微波传感器，如 SMOS 卫星（土壤湿度和海洋盐度），可以对全球土壤湿度进行全球研究。为了获得公里变异性，已经开发了分解算法，例如基于物理和理论尺度变化的分解（DisPATCh）。该方法将SMOS土壤湿度的空间分辨率从40 km提高到1 km。为此，它将粗尺度（约 40 km）SMOS 产品与细尺度（约 1 km）光学/热数据相结合。特定尺度的验证研究表明，在低植被半干旱地区，DisPATCh 有潜力增强分类 SM 与原位测量的时空相关性。尽管该方法的效率在这些区域得到了揭示，但没有研究充分探讨其在连续空间尺度上的统计行为。在本文中，我们研究并比较了 DisPATCh 降尺度所涉及的不同输入和输出数据集的空间多尺度统计。为此，我们从 2010 年 6 月到 12 月对澳大利亚东南部地区的相应产品进行了光谱和多重分形分析。在 DisPATCh（SMOS 土壤湿度、MODIS 植被指数和地表温度）的输入中观察了分形和多重分形特性（在通用多重分形模型的框架内），这证实并完成了现有文献中报告的一些结果。对于输出的分解土壤湿度，观察到两种尺度范围，并在约十公里处观察到过渡尺度。考虑到光谱分析，在大尺度（> 10 km）上，分解的土壤湿度被发现与原始 SMOS 土壤湿度具有相同的尺度。在更精细的尺度（< 10 km）上，我们注意到不同的行为，功率谱的斜率值更高。在统计矩上检测到相同的尺度断裂，表明 DisPATCH 土壤水分的光谱和多重分形特性都以这种双重尺度特征为特征。
Soil moisture has a strong impact on climate, hydrology and agronomy at different space scales, from the continent global scale to the local watershed. Passive microwave sensors, like SMOS satellite (Soil Moisture and Ocean Salinity), allow a global study of soil moisture on the entire globe. To have access to kilometric variability, disaggregation algorithms have been developed, such as the Disaggregation based on Physical And Theoretical scale Change (DisPATCh). This method improves the space resolution of SMOS soil moisture from 40 km to 1 km. To do this, it combines coarse-scale (≈40 km) SMOS products with fine-scale (≈1 km) optical/thermal data. Validation studies on specific scales showed the potential of DisPATCh to enhance the spatio-temporal correlation of disaggregated SM with in-situ measurements, under low-vegetated semi-arid regions. Although the efficiency of the method was revealed in these regions, no studies fully explored its statistical behavior over a continuum of space scales. In this paper, we studied and compared the spatial multi-scale statistics of the different input and output datasets involved in DisPATCh downscaling. To do this, we applied spectral and multifractal analysis on the respective products for the region of southeastern Australia, from June to December 2010. Fractal and multifractal properties (in the framework of the Universal Multifractal model) were observed on inputs of DisPATCh (SMOS soil moisture, MODIS vegetation indices and surface temperature), which confirmed and completed some results reported in existing literature. For the output disaggregated soil moisture, two scaling regimes were observed, with a transition scale observed at about ten kilometers. Considering spectral analysis, at large scales (> 10 km), disaggregated soil moisture was found to have the same scaling as the original SMOS soil moisture. On finer scales (< 10 km), a different behavior was noticed, with a higher value of the slope of the power spectrum. The same scale break was detected on statistical moments, showing that both spectral and multifractal properties of DisPATCh soil moisture are characterized by this twofold scaling signature.