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首页> 外文期刊>Journal of Hydrology >Validation of remotely sensed estimates of snow water equivalent using multiple reference datasets from the middle and high latitudes of China
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Validation of remotely sensed estimates of snow water equivalent using multiple reference datasets from the middle and high latitudes of China

机译:基于中国中高纬度地区多个参考数据集的雪水当量遥感估计值的验证

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A key variable describing the mass of seasonal snow cover is snow water equivalent (SWE), which plays an important role in hydrological applications, weather forecasting and land surface process simulations. In this paper, the accuracy of an SWE product, GlobSnow-2, which combines microwave satellite data and in situ measurements, is assessed using three reference evaluation datasets north of 35°N in China. The GlobSnow-2 estimates are also compared with stand-alone satellite products (AMSR2, Chang and FY-3D SWE). The overall unbiased root mean square error (RMSE) and bias of the GlobSnow-2 SWE product validated with three reference datasets are 17.4 mm and 11.2 mm, respectively, which outperforms the AMSR2 SWE (39.3 mm and 37.3 mm, respectively) and Chang SWE (57.5 mm and 46.2 mm, respectively) products. The FY-3D SWE product performs better than the GlobSnow-2 estimate for shallow snow (SWE < 50 mm) and tends to underestimate snow cover, particularly when SWE exceeds 80 mm. A retrieval sensitivity analysis against land cover types shows that the highest SWE uncertainties for GlobSnow-2 are exhibited in grassland (unbiased RMSE, 27.8 mm),and the most serious overestimation occurs in forested areas (bias, 23.6 mm). The GlobSnow-2 performances at various elevations show an increasing bias trend, ranging from 5 to 61 mm with increasing elevation. The GlobSnow-2 estimate analyses under different snow regimes show that the GlobSnow-2 SWE product performs best in taiga snow, with high uncertainties (unbiased RMSE, 28.3 mm) in prairie snow and serious overestimations (bias, 23.2 mm) for alpine snow. The results of this study demonstrate that the GlobSnow-2 assimilation approach tends to overestimate SWE in China. One of the major reasons that overestimations occur is that the GlobSnow-2 SWE retrieval scheme utilizes a fixed density of 240 kg/m~3, which is larger than the average value derived from ground measurements for China (180 kg/m~3), which undoubtedly contributes
机译:描述季节性积雪质量的一个关键变量是雪水当量 (SWE),它在水文应用、天气预报和地表过程模拟中发挥着重要作用。本文使用中国北纬35°以北的三个参考评估数据集,评估了SWE产品GlobSnow-2的准确性,该产品结合了微波卫星数据和原位测量。还将GlobSnow-2的估计值与独立卫星产品(AMSR2、Chang和FY-3D SWE)进行了比较。使用三个参考数据集验证的GlobSnow-2 SWE产品的总体无偏均方根误差(RMSE)和偏差分别为17.4 mm和11.2 mm,优于AMSR2 SWE(分别为39.3 mm和37.3 mm)和Chang SWE(分别为57.5 mm和46.2 mm)产品。FY-3D SWE产品对浅雪(SWE < 50 mm)的估计性能优于GlobSnow-2估计值,并且往往会低估积雪覆盖率,特别是当SWE超过80毫米时。对土地覆被类型的反演敏感性分析表明,GlobSnow-2的SWE不确定性在草地上最高(无偏RMSE,27.8 mm),在森林地区被高估最严重的是草地(偏差,23.6 mm)。GlobSnow-2在不同海拔处的表现显示出越来越大的偏差趋势,随着海拔的增加,偏差范围从5到61 mm不等。不同积雪条件下的GlobSnow-2估计分析表明,GlobSnow-2 SWE产品在针叶林雪中表现最好,在草原雪中具有很高的不确定性(无偏RMSE,28.3 mm),而在高山积雪中则存在严重的高估(偏差,23.2 mm)。本研究结果表明,GlobSnow-2同化方法倾向于高估中国的SWE值。高估的主要原因之一是GlobSnow-2 SWE反演方案采用的固定密度为240 kg/m~3,大于中国地面测量的平均值(180 kg/m~3),这无疑有助于

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