Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities

Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities
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截雪模型:孤立的观测导致许多地表模型缺乏适当的温度敏感性

DOI:
10.1002/hyp.14274
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发表时间:
2021
影响因子:
3.2
通讯作者:
Reynolds, Dylan
Reynolds, Dylan
中科院分区:
地球科学3区
文献类型:
--
作者:
Lundquist, Jessica D.;Dickerson‐Lange, Susan;Gutmann, Ethan;Jonas, Tobias;Lumbrazo, Cassie;Reynolds, Dylan

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在制定水文模型时,科学家们依赖于基于现场数据的多个过程的参数化,但文献综述表明,人们更频繁地选择包含在现有模型中的参数化,而不是重新评估底层的现场实验。当有限的现场数据存在时,当“可信”的方法没有得到重新评估时,当敏感性在不同的环境中发生根本变化时,就会出现问题。针叶树对积雪的物理和动力学拦截就是这样一种情况,它是模拟水分收支和地表径流的关键。最常用的拦截参数化是基于从四棵树从一个网站的数据,但从这个领域的研究结果是不能直接转移到相对温暖的冬天,在那里的主导过程差异显着的位置。在这里,我们结合联合收割机的文献综述与模型实验,以证明所需的改进。我们的结果表明,模型形式和参数的选择可以使通过拦截损失的雪的比例变化高达30%。在大多数模拟中,冬季平均气温从-7 °C上升到0°C,与开放相比,树冠下的模拟雪量减少了,但模拟减少的幅度从10%到40%不等。当考虑忽略在较高湿度环境中冠层升华作用较小的冠层内雪融化的模型时,结果的范围甚至更大。因此,我们建议所有模型都要表现出树冠融雪,并包括当温度从−3 °C上升到0°C时,由于粘附力和凝聚力增加而增加的载荷的表现。除了改进模型外,还需要进行跨气候和森林类型的实地实验,以研究如何最好地模拟动态变化的森林覆盖和积雪的组合,以更好地了解和预测干旱和供水的变化。
When formulating a hydrologic model, scientists rely on parameterizations of multiple processes based on field data, but literature review suggests that more frequently people select parameterizations that were included in pre‐existing models rather than re‐evaluating the underlying field experiments. Problems arise when limited field data exist, when “trusted” approaches do not get reevaluated, and when sensitivities fundamentally change in different environments. The physics and dynamics of snow interception by conifers is just such a case, and it is critical to simulation of the water budget and surface albedo. The most commonly used interception parameterization is based on data from four trees from one site, but results from this field study are not directly transferable to locations with relatively warmer winters, where the dominant processes differ dramatically. Here, we combine a literature review with model experiments to demonstrate needed improvements. Our results show that the choice of model form and parameters can vary the fraction of snow lost through interception by as much as 30%. In most simulations, the warming of mean winter temperatures from −7 to 0°C reduces the modelled fraction of snow under the canopy compared to the open, but the magnitude of simulated decrease varies from about 10% to 40%. The range of results is even larger when considering models that neglect the melting of in‐canopy snow in higher‐humidity environments where canopy sublimation plays less of a role. Thus, we recommend that all models represent canopy snowmelt and include representation of increased loading due to increased adhesion and cohesion when temperatures rise from −3 to 0°C. In addition to model improvements, field experiments across climates and forest types are needed to investigate how to best model the combination of dynamically changing forest cover and snow cover to better understand and predict changes to albedo and water supplies.
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