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Quantification of the radiative impact of light-absorbing particles during two contrasted snow seasons at Col du Lautaret (2058ma.s.l., French Alps)

机译:在三个对比的雪季辐射颗粒在Col du Lautaret(2058ma.s.l.,法国阿尔卑斯山)中的辐射影响

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The presence of light-absorbing particles (LAPs) in snow leads to a decrease in short-wave albedo affecting the surface energy budget. However, the understanding of the impacts of LAPs is hampered by the lack of dedicated datasets, as well as the scarcity of models able to represent the interactions between LAPs and snow metamorphism. The present study aims to address both these limitations by introducing a survey of LAP concentrations over two snow seasons in the French Alps and an estimation of their impacts based on the Crocus snowpack model that represents the complex interplays between LAP dynamics and snow metamorphism. First, a unique dataset collected at Col du Lautaret (2058?m?a.s.l., above sea level, French Alps) for the two snow seasons 2016–2017 and 2017–2018 is presented. This dataset consists of spectral albedo measurements, vertical profiles of snow specific surface area (SSA), density and concentrations of different LAP species. Spectral albedos are processed to estimate SSA and LAP absorption-equivalent concentrations near the surface of the snowpack. These estimates are then compared to chemical measurements of LAP concentrations and SSA measurements. Our dataset highlights, among others, large discrepancies between two measurement techniques of black carbon (BC) concentrations in snow (namely thermal-optical and laser-induced incandescence). Second, we present ensemble snowpack simulations of the multi-physics version of the detailed snowpack model Crocus, forced with in situ meteorological data, as well as dust and BC deposition fluxes from an atmospheric model. The temporal variations of near-surface LAP concentrations and SSA are most of the time correctly simulated. The simulated seasonal radiative forcing of LAPs is 33?% higher for the 2017–2018 snow season than for the 2016–2017 one, highlighting a strong variability between these two seasons. However, the shortening of the snow season caused by LAPs is similar with 10?±?5 and 11?±?1?d for the first and the second snow seasons, respectively. This counter-intuitive result is attributed to two small snowfalls at the end of the first season and highlights the importance in accounting for meteorological conditions to correctly predict the impact of LAPs. The strong variability of season shortening caused by LAPs in the multi-physics ensemble for the first season (10?±?5?d) also points out the sensitivity of model-based estimations of LAP impact on modelling uncertainties of other processes. Finally, the indirect impact of LAPs (i.e. the enhancement of energy absorption due to the acceleration of the metamorphism by LAPs) is negligible for the?2 years considered here, which is contrary to what was found in previous studies for other sites.
机译:积雪中的光吸收颗粒(圈)的存在导致影响表面能预算的短波Albedo的降低。然而,对圈的影响的理解受到专用数据集的缺乏阻碍,以及能够代表圈和雪变质之间的相互作用的模型的稀缺性。本研究旨在通过在法国阿尔卑斯阿尔卑斯山区的两个雪季的速度浓度和基于番红花雪橇模型的估计来解决这些限制,以及基于番红花的雪橇模型来估算它们的搭扣动力学和雪变质之间的复杂相互作用。首先,在Col du Lautaret(2058年?M?A.S.L)上收集了一个独特的数据集,这是2016-2017和2017-2018的两个雪季的两雪季。该数据集包括光谱反玻璃测量,雪比表面积(SSA)的垂直轮廓,不同液体物种的密度和浓度。将光谱反玻璃加工以估计靠近积雪表面附近的SSA和液体吸收 - 等效浓度。然后将这些估计与圈浓度和SSA测量的化学测量进行比较。我们的数据集在雪中的黑碳(BC)浓度的两个测量技术之间的突出显示(即热 - 光和激光诱导的白炽)之间的大致差异。其次,我们呈现出详细的积雪模型番红花的多物理版的集合雪橇模拟,强制使用灰气象数据,以及来自大气模型的灰尘和BC沉积通量。近表面圈浓度和SSA的时间变化是大多数正确模拟的时间。 2017-2018雪季的模拟季节性辐射强制暂停锻炼效率比2016-2017雪季节更高,突出了这两个季节之间的强大变异性。然而,由圈引起的雪季缩短了第一个和第二雪季的10?±5和11?±1?d。这种反向直观的结果归因于第一季结束时的两次小雪,并突出了核算气象条件的重要性,以正确预测圈的影响。第一个季节的多物理集合圈引起的季节缩短的强烈变化(10?±5?d)还指出了基于模型的液体估算对其他过程的不确定性的影响的灵敏度。最后,LAP的间接影响(即,由于圈数变质的加速而导致的能量吸收)可忽略不计,因为这里考虑的2年,这与其他网站的先前研究中发现的相反。

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