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Parameter sensitivity of soil moisture retrievals from airborne L-band radiometer measurements in SMEX02

机译:SMEX02中机载L波段辐射计测量的土壤水分反演的参数敏感性

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Over the past two decades, successful estimation of soil moisture has been accomplished using L-band microwave radiometer data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. Surface characteristics are highly variable in space and time, and there has been little effort made to determine the parameter estimation accuracies required to meet a given soil moisture retrieval accuracy specification. This study quantifies the sensitivities of soil moisture retrieved using an L-band single-polarization algorithm to three land surface parameters for corn and soybean sites in Iowa, United States. Model sensitivity to the input parameters was found to be much greater when soil moisture is high. For even moderately wet soils, extremely high sensitivity of retrieved soil moisture to some model parameters for corn and soybeans caused the retrievals to be unstable. Parameter accuracies required for consistent estimation of soil moisture in mixed agricultural areas within retrieval algorithm specifications are estimated. Given the spatial and temporal variability of vegetation and soil conditions for agricultural regions it seems unlikely that, for the single-frequency, single-polarization retrieval algorithm used in this analysis, the parameter accuracy requirements can be met with current satellite-based land surface products. We conclude that for regions with substantial vegetation, particularly where the vegetation is changing rapidly, any soil moisture retrieval algorithm that is based on the physics and parameterizations used in this study will require multiple frequencies, polarizations, or look angles to produce stable, reliable soil moisture estimates.
机译:在过去的二十年中,使用L波段微波辐射计数据成功地估算了土壤湿度。但是,必须先解决与表面粗糙度以及植被吸收,散射和发射有关的不确定性,然后才能使用卫星观测技术以已知且可接受的精度应用土壤水分检索算法。表面特征在空间和时间上变化很大,因此几乎没有做出任何努力来确定满足给定土壤水分取回精度规格所需的参数估计精度。这项研究量化了使用L带单极化算法获取的土壤水分对美国爱荷华州玉米和大豆站点的三个陆地表面参数的敏感性。当土壤湿度高时,发现模型对输入参数的敏感性要高得多。对于即使是中等湿度的土壤,恢复的土壤水分对玉米和大豆的某些模型参数的极高敏感性也会导致恢复不稳定。估算了在检索算法规范范围内一致估算混合农业地区土壤水分所需的参数精度。考虑到农业地区植被和土壤条件的时空变化,对于本分析中使用的单频,单极化检索算法,当前基于卫星的陆表产品似乎无法满足参数精度要求。我们得出结论,对于植被茂密的地区,尤其是植被变化迅速的地区,任何基于本研究中使用的物理学和参数化方法的土壤水分反演算法都将需要多个频率,极化或视角以产生稳定,可靠的土壤湿度估计。

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