A Finite Volume Blowing Snow Model for Use With Variable Resolution Meshes
A Finite Volume Blowing Snow Model for Use With Variable Resolution Meshes
复制标题
用于可变分辨率网格的有限体积吹雪模型
DOI：
10.1029/2019wr025307
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发表时间：
2020
影响因子：
5.4
通讯作者：
H. Wheater
中科院分区：
文献类型：
--
作者：
C. Marsh;J. Pomeroy;R. Spiteri;H. Wheater
在寒冷多风的环境中，吹雪无处不在。在一些地区，吹雪升华损失可以消融季节性降雪的显著部分。由于积雪再分布对融雪持续时间和融雪量的控制作用，在雪堆（≈1 ~ 100 m）的空间尺度上预测高山积雪状况是有利的。然而，由于计算成本的原因，吹雪过程经常被忽略。本文提出了一个三维吹雪模型，该模型采用变分辨率非结构化网格进行空间离散。这明确地代表了表面的非均匀性，对于案例研究报告来说，与固定分辨率网格相比，计算元素减少了62%，总运行时间减少了44%。利用冻土带流域测量的雪水当量（SWE）样带对该模型进行了评估。包括吹雪过程在内，通过捕捉年内雪堆形成改善了对SWE的预测，使总平均偏倚误差减少了一半以上，并将SWE的变异系数从0.04提高到0.31，更好地匹配观测到的CV（0.41）。使用可变分辨率网格并没有显著降低模型的性能。与恒分辨率网格比较，CV和RMSE与变分辨率网格相似。恒分辨率网格的平均偏置误差较小。敏感性分析表明，雪堆位置和直接向上吹雪源是景观中对风速变化最敏感的区域。
Blowing snow is ubiquitous in cold, windswept environments. In some regions, blowing snow sublimation losses can ablate a notable fraction of the seasonal snowfall. It is advantageous to predict alpine snow regimes at the spatial scale of snowdrifts (≈1 to 100 m) because of the role of snow redistribution in governing the duration and volume of snowmelt. However, blowing snow processes are often neglected due to computational costs. Here, a three‐dimensional blowing snow model is presented that is spatially discretized using a variable resolution unstructured mesh. This represents the heterogeneity of the surface explicitly yet, for the case study reported, gained a 62% reduction in computational elements versus a fixed‐resolution mesh and resulted in a 44% reduction in total runtime. The model was evaluated for a subarctic mountain basin using transects of measured snow water equivalent (SWE) in a tundra valley. Including blowing snow processes improved the prediction of SWE by capturing inner‐annual snowdrift formation, more than halved the total mean bias error, and increased the coefficient of variation of SWE from 0.04 to 0.31 better matching the observed CV (0.41). The use of a variable resolution mesh did not dramatically degrade the model performance. Comparison with a constant resolution mesh showed a similar CV and RMSE as the variable resolution mesh. The constant resolution mesh had a smaller mean bias error. A sensitivity analysis showed that snowdrift locations and immediate up‐wind sources of blowing snow are the most sensitive areas of the landscape to wind speed variations.
影响因子：
4.7
作者：
Essery, Richard;Morin, Samuel;Menard, Cecile B.
通讯作者：
Menard, Cecile B.
影响因子：
6.3
作者：
Menard, C. B.;Essery, R.;Pomeroy, J.
通讯作者：
Pomeroy, J.