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首页> 外文期刊>Journal of hydrometeorology >Characterization of errors in a coupled snow hydrology-microwave emission model
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Characterization of errors in a coupled snow hydrology-microwave emission model

机译：雪水文-微波耦合耦合模型中的误差特征

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摘要

Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (T-B) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while T-B model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), aircraft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] T-B measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the T-B spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, T-B prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on T-B predictions.
机译：通过被动微波遥感直接估计雪性的传统方法受到局限性的困扰，例如中等深度积雪的估计趋于饱和以及遥感像素内混合土地覆盖的影响。另一种方法是直接吸收卫星微波发射观测值，这需要将准确的微波发射模型嵌入水文预测方案中，以及模型和观测误差的定量信息。在这项研究中，使用来自冷陆过程实验（CLPX）的多尺度亮度温度（T-B）测量评估了耦合的积雪水文学[变量入渗能力（VIC）]和微波发射[稠密介质辐射传递（DMRT）]模型。通过使用雪坑测量显示了VIC再现积雪性质的能力，同时通过与地面微波辐射计（GBMR），飞机[测色扫描辐射计（PSR）]和卫星[高级]进行比较来评估TB模型的预测。用于地球观测系统的微波扫描辐射计（AMSR-E）] TB测量。比较面积估计值时，模型在点尺度上的局限性并不那么明显。耦合模型能够重现PSR在三个站点中的两个站点中观察到的T-B空间模式。但是，这主要是由于存在相对茂密的森林覆盖。当检查高分辨率错误的空间缩放行为时，会产生一个有趣的结果。卫星尺度误差可以由较小尺度的误差（空间）直方图的模式很好地近似。此外，将T-B预测误差加总到卫星规模时几乎不变，而大于30％的森林覆盖率对T-B预测有重大影响。

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