Incorporating remotely‐sensed snow albedo into a spatially‐distributed snowmelt model
Incorporating remotely‐sensed snow albedo into a spatially‐distributed snowmelt model
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DOI：
10.1029/2003gl019063
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发表时间：
2004-02
影响因子：
5.2
通讯作者：
N. Molotch;T. Painter;R. Bales;J. Dozier
中科院分区：
文献类型：
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作者：
N. Molotch;T. Painter;R. Bales;J. Dozier
根据特定于集水区的遥感机载可见光/红外成像光谱仪（AVIRIS）数据估计的流域平均降雨量通常与使用常见的基于雪龄的经验关系估计的降雨量相差20%。在盆地的某些地方，差异高达0.31。在一个分布式的融雪模型中使用AVIRIS EQUIPDO估计值，该模型明确包括净太阳辐射，与经验EQUIPDO的相同模型相比，对融雪的时间和量级的估计更加准确（R2为0.73对0.59，量级误差为2%对36%）。在入射太阳辐射相对较高和温度较低的地区和时间，模型的改进最为显著。
Basin‐average albedo estimated from remotely‐sensed Airborne Visible/Infrared Imaging Spectroradiometer (AVIRIS) data specific to the catchment typically differed by 20% from albedo estimated using a common snow‐age‐based empirical relation. In some parts of the basin, differences were as large as 0.31. Using the AVIRIS albedo estimates in a distributed snowmelt model that explicitly includes net solar radiation resulted in a much more accurate estimate of the timing and magnitude of snowmelt as compared to the same model with the empirical albedo (R2 of 0.73 versus 0.59 and magnitude error of 2% versus 36%). Model improvement was most significant in areas and at times where incident solar radiation was relatively high and temperatures low.