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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Uncertainty Quantification in Land Surface Hydrologic Modeling: Toward an Integrated Variational Data Assimilation Framework
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Uncertainty Quantification in Land Surface Hydrologic Modeling: Toward an Integrated Variational Data Assimilation Framework

机译：地表水文建模中的不确定性量化：建立综合的变分数据同化框架

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摘要

Variational data assimilation (VDA) is an effective technique for the estimation of land surface heat fluxes. In this method, sequences of remotely sensed land surface temperature measurements are assimilated into a dynamic surface energy balance model to estimate the key unknown parameters of the turbulent heat fluxes. Despite the advantages of the VDA technique in the retrieval of land surface heat fluxes, it suffers from a key limitation, which is its tendency to be ill posed. Moreover, unlike ensemble-based schemes, the VDA method itself does not provide estimates of the predictive uncertainty of estimated parameters and, thus, retrieved fluxes. This research addresses these shortcomings by proposing an uncertainty quantification (UQ) framework for the VDA technique. The proposed framework utilizes uncertainty analysis and analysis of error covariance approximation as a tool to quantify the uncertainty of estimated parameters and to guide the formulation of a well-posed estimation problem. It provides a calibration-free tool to assess the performance of the VDA technique in retrieving land surface heat fluxes over a range of land surfaces and climatic conditions. The UQ framework suggests that the VDA approach performs poorly over wet and highly vegetated land surface regions and when the difference between land surface and air temperature is low. Moreover, it reveals that characterizing the effect of vegetation dynamics on the bulk heat transfer coefficient reduces the correlation between unknown parameters and, hence, leads to a more robust estimation of parameters.
机译：变异数据同化（VDA）是一种有效的技术，可用于估算陆地表面热通量。在这种方法中，将遥感陆地表面温度测量的序列同化为动态表面能量平衡模型，以估算湍流通量的关键未知参数。尽管VDA技术在恢复地表热通量方面具有优势，但仍存在关键局限性，这是它容易引起不适的趋势。而且，与基于集成的方案不同，VDA方法本身不提供估计参数的预测不确定性的估计，因此也无法提供所获取的通量。这项研究通过为VDA技术提出不确定性量化（UQ）框架解决了这些缺点。所提出的框架利用不确定性分析和误差协方差近似分析作为一种工具来量化估计参数的不确定性，并指导提出恰当的估计问题。它提供了一种无需校准的工具，可以评估VDA技术在一系列土地表面和气候条件下获取土地表面热通量的性能。 UQ框架表明，VDA方法在湿润和植被茂密的陆地表面区域以及陆地表面和气温之间的差异较小时效果不佳。此外，它揭示了表征植被动力学对整体传热系数的影响会减少未知参数之间的相关性，从而导致参数的更可靠估计。

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