Tao Jing, Reichle Rolf H, Koster Randal D, Forman Barton A, Xue Yuan
Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland.
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland.
J Adv Model Earth Syst. 2017 Nov;9(7):2771-2795. doi: 10.1002/2017ms001019. Epub 2017 Nov 8.
Besides soil hydrology and snow processes, the NASA Catchment Land Surface Model (CLSM) simulates soil temperature in six layers from the surface down to 13m depth. In this study, to examine CLSM's treatment of subsurface thermodynamics, a baseline simulation produced subsurface temperatures for 1980-2014 across Alaska at 9-km resolution. The results were evaluated using in situ observations from permafrost sites across Alaska. The baseline simulation was found to capture the broad features of inter- and intra-annual variations in soil temperature. Additional model experiments revealed that: (i) the representativeness of local meteorological forcing limits the model's ability to accurately reproduce soil temperature, and (ii) vegetation heterogeneity has a profound influence on subsurface thermodynamics via impacts on the snow physics and energy exchange at surface. Specifically, the profile-average RMSE for soil temperature was reduced from 2.96°C to 2.10°C at one site and from 2.38°C to 2.25°C at another by using local forcing and land cover, respectively. Moreover, accounting for the influence of soil organic carbon on the soil thermal properties in CLSM leads to further improvements in profile-average soil temperature RMSE, with reductions of 16% to 56% across the different study sites. The mean bias of climatological ALT is reduced by 36% to 89%, and the RMSE is reduced by 11% to 47%. Finally, results reveal that at some sites it may be essential to include a purely organic soil layer to obtain, in conjunction with vegetation and snow effects, a realistic "buffer zone" between the atmospheric forcing and soil thermal processes.
除了土壤水文学和积雪过程外,美国国家航空航天局流域陆面模型(CLSM)还模拟了从地表到地下13米深度的六层土壤温度。在本研究中,为了检验CLSM对地下热力学的处理方式,进行了一次基线模拟,以9公里的分辨率生成了1980 - 2014年阿拉斯加地区的地下温度。利用阿拉斯加各地多年冻土观测点的实地观测数据对结果进行了评估。结果发现,基线模拟捕捉到了土壤温度年际和年内变化的主要特征。额外的模型实验表明:(i)当地气象强迫的代表性限制了模型准确再现土壤温度的能力;(ii)植被异质性通过对雪物理和地表能量交换的影响,对地下热力学有深远影响。具体而言,在一个站点,通过使用当地强迫数据和土地覆盖数据,土壤温度的剖面平均均方根误差(RMSE)分别从2.96°C降至2.10°C,在另一个站点从2.38°C降至2.25°C。此外,在CLSM中考虑土壤有机碳对土壤热性质的影响,可进一步改善剖面平均土壤温度RMSE,不同研究站点的降幅在16%至56%之间。气候学ALT的平均偏差降低了36%至89%,RMSE降低了11%至47%。最后,结果表明,在某些站点,可能有必要加入一个纯有机土壤层,以便结合植被和积雪效应,在大气强迫和土壤热过程之间获得一个现实的“缓冲区”。