An Examination of Snow Albedo Estimates From MODIS and Their Impact on Snow Water Equivalent Reconstruction
An Examination of Snow Albedo Estimates From MODIS and Their Impact on Snow Water Equivalent Reconstruction
复制标题
DOI：
10.1029/2019wr024810
复制
发表时间：
2019-09-01
影响因子：
5.4
通讯作者：
Dozier, Jeff
中科院分区：
文献类型：
--
作者：
Bair, Edward H.;Rittger, Karl;Dozier, Jeff
在世界许多地方，雪反照率是对融雪的主要控制因素。 60 多年前开发的经验反照率衰减方程至今仍在融雪模型中使用。此后开发的几种经验雪反照率模型显示出广泛的结果。遥感雪反照率已用于一些研究，但由于难以进行准确的现场测量，因此验证很少。雪水当量 (SWE) 的重建（其中积雪是反向构建的）对反照率特别敏感。我们提出了两项新贡献：（1）更新的反照率模型，其中同时求解颗粒尺寸和光吸收颗粒含量；（2）对来自美国西部三个高海拔地点的遥感和原位反照率测量进行多年比较。我们的遥感反照率显示 4% 到 6% 的 RMSE 和可忽略不计的偏差。相比之下，需要大量现场测量的经验反照率衰减模型显示 RMSE 值为 7% 至 17%，偏差为 -6% 至 -14%。我们检查了 SWE 重建对两个地点的反照率误差的敏感性。由于反照率没有模拟误差，重建的 SWE 的 MAE 值为 7% 至 13%，偏差为 5-6%。实际上，由于一些模拟的附加误差，准确性有所提高，这可能是由于重建方法中存在基本偏差。相反，最好的基于年龄的衰减模型在重建的 SWE 中显示出 18-20% 的 MAE 和偏差。我们得出的结论是，除了简单性之外，遥感反照率在所有方面都优于基于年龄的方法。
Snow albedo is a dominant control on snowmelt in many parts of the world. An empirical albedo decay equation, developed over 60 years ago, is still used in snowmelt models. Several empirical snow albedo models developed since show wide spread in results. Remotely sensed snow albedos have been used in a few studies, but validations are scarce because of the difficulty in making accurate in situ measurements. Reconstruction of snow water equivalent (SWE), where the snowpack is built in reverse, is especially sensitive to albedo. We present two new contributions: (1) an updated albedo model where grain size and light absorbing particle content are solved for simultaneously and (2) multiyear comparisons of remotely sensed and in situ albedo measurements from three high-altitude sites in the western United States. Our remotely sensed albedos show 4 to 6% RMSE and negligible bias. In comparison, empirical albedo decay models, which require extensive in situ measurements, show RMSE values of 7 to 17% with biases of -6 to -14%. We examine the sensitivity of SWE reconstructions to albedo error at two sites. With no simulated error in albedo, reconstructed SWE had MAE values of 7 to 13% and 5-6% bias. The accuracy actually improved with some simulated added error, likely because of a fundamental bias in the reconstruction approach. Conversely, the best age-based decay model showed an 18-20% MAE and bias in reconstructed SWE. We conclude that remotely sensed albedos where available are superior to age-based approaches in all aspects except simplicity.