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Evaluating the performance of coupled snow–soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site

机译:在SURFEXv8中评估雪土耦合模型的性能,以模拟北极高海拔地区的多年冻土热状况

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Climate change projections still suffer from a limited representation of the permafrost–carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.
机译:气候变化的预测仍然受冻土-碳反馈的代表性有限的困扰。预测多年冻土温度对气候变化的响应,需要对北极雪和土壤特性进行精确的模拟。这项研究评估了耦合的地表和降雪模型ISBA-Crocus和ISBA-ES在北极高空Bylot岛上模拟雪和土壤特性的能力。现场测量加上ERA-Interim重新分析被用来驱动模型和评估模拟输出。检查雪的高度,密度,温度,导热系数和热吸力,以确定涉及土壤和雪热状况的关键变量。将模拟的土壤特性与热导率,温度和水含量的测量结果进行比较。模拟的雪密度剖面是不切实际的,这很可能是由于雪模型中缺乏由积雪内部强烈的温度梯度产生的向上的水蒸气通量的表示所致。与观测值相比,所得的垂直导热系数垂直分布被反转,在积雪的底部具有较高的模拟值。尽管如此,ISBA-Crocus仍成功地模拟了冬季的土壤温度。夏季的结果令人满意,但是通过充分代表苔藓和垫料的表面有机层,尤其是它们的保水能力,可以更好地再现表层土壤的温度。过渡期(土壤冻结和融化)的再现最少,因为在模拟中,高的基雪导热系数会导致土壤和雪之间的热量传递过快。因此,全球气候模型应仔细考虑北极积雪的热特性,尤其是基底积雪层的热导率,以准确预测气候变化下的多年冻土演变。

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