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Simulation of the specific surface area of snow using a one-dimensional physical snowpack model: implementation and evaluation for subarctic snow in Alaska

机译:使用一维物理积雪模型模拟雪的比表面积:阿拉斯加的北极北极雪的实现和评估

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The specific surface area (SSA) of the snow constitutes a powerful parameter to quantify the exchange of matter and energy between the snow and the atmosphere. However, currently no snow physics model can simulate the SSA. Therefore, two different types of empirical parameterizations of the specific surface area (SSA) of snow are implemented into the existing one-dimensional snow physics model CROCUS. The parameterizations are either based on diagnostic equations relating the SSA to parameters like snow type and density or on prognostic equations that describe the change of SSA depending on snow age, snowpack temperature, and the temperature gradient within the snowpack. Simulations with the upgraded CROCUS model were performed for a subarctic snowpack, for which an extensive data set including SSA measurements is available at Fairbanks, Alaska for the winter season 2003/2004. While a reasonable agreement between simulated and observed SSA values is obtained using both parameterizations, the model tends to overestimate the SSA. This overestimation is more pronounced using the diagnostic equations compared to the results of the prognostic equations. Parts of the SSA deviations using both parameterizations can be attributed to differences between simulated and observed snow heights, densities, and temperatures. Therefore, further sensitivity studies regarding the thermal budget of the snowpack were performed. They revealed that reducing the thermal conductivity of the snow or increasing the turbulent fluxes at the snow surfaces leads to a slight improvement of the simulated thermal budget of the snowpack compared to the observations. However, their impact on further simulated parameters like snow height and SSA remains small. Including additional physical processes in the snow model may have the potential to advance the simulations of the thermal budget of the snowpack and, thus, the SSA simulations.
机译:雪的比表面积(SSA)构成了一个强大的参数,可以量化雪与大气之间物质和能量的交换。但是,目前尚无雪物理学模型可以模拟SSA。因此,在现有的一维雪物理学模型CROCUS中实现了雪的比表面积(SSA)的两种不同类型的经验参数化。参数化或者基于将SSA与诸如雪类型和密度之类的参数相关的诊断方程式,或者基于描述SSA随雪龄,积雪温度和积雪内温度梯度变化的预测方程式。使用升级后的CROCUS模型对亚北极积雪进行了仿真,2003/2004年冬季,阿拉斯加的费尔班克斯可获得包括SSA测量在内的大量数据集。尽管使用这两个参数化都获得了模拟的和观察到的SSA值之间的合理一致性,但该模型往往会高估SSA。与诊断方程式的结果相比,使用诊断方程式时,这种高估更为明显。使用这两个参数设置的部分SSA偏差可以归因于模拟和观测到的雪高,密度和温度之间的差异。因此,进行了有关积雪的热预算的进一步敏感性研究。他们发现,与观测相比,降低雪的热导率或增加雪表面的湍流会导致模拟的积雪的热收支稍微改善。但是,它们对进一步模拟的参数(如雪高和SSA)的影响仍然很小。在雪模型中包括其他物理过程可能有可能推动对积雪的热收支的模拟,从而推动SSA模拟。

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