Habiba Kallel, A. Thiboult, M. Mackay, D. Nadeau, F. Anctil
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引用次数: 0
Abstract
Accurately modeling the interactions between inland water bodies and the atmosphere in meteorological and climate models is crucial, given the marked differences with surrounding landmasses. Modeling surface heat fluxes remains a challenge because direct observations available for validation are rare, especially at high latitudes. This study presents a detailed evaluation of the Canadian Small Lake Model (CSLM), a one-dimensional mixed-layer dynamic lake model, in reproducing the surface energy budget and the thermal stratification of a subarctic reservoir in eastern Canada. The analysis is supported by multi-year direct observations of turbulent heat fluxes collected on and around the 85-km2 Romaine-2 hydropower reservoir (50.7°N, 63.2°W) by two flux towers: one operating year-round on the shore and one on a raft during ice-free conditions. The CSLM, which simulates the thermal regime of the water body including ice formation and snow physics, is run in offline mode and forced by local weather observations from 25 June 2018 to 8 June 2021. Comparisons between observations and simulations confirm that CSLM can reasonably reproduce the turbulent heat fluxes and the temperature behavior of the reservoir, despite the one-dimensional nature of the model which cannot account for energy inputs and outputs associated with reservoir operations. The best performance is achieved during the first few months after the ice break-up (mean error= −0.3 W m−2 and mean error= −2.7 W m−2 for latent and sensible heat fluxes). The model overreacts to strong wind events, leading to subsequent poor estimates of water temperature and eventually to an early freeze-up. The model overestimated the measured annual evaporation corrected for the lack of energy balance closure by 5% and 16% in 2019 and 2020.
考虑到内陆水体与周围陆地的显著差异,在气象和气候模式中准确模拟内陆水体与大气之间的相互作用至关重要。地表热通量的建模仍然是一个挑战,因为可用于验证的直接观测很少,特别是在高纬度地区。本文对加拿大小湖模型(CSLM)进行了详细的评价,该模型是一种一维混合层动态湖泊模型,用于再现加拿大东部亚北极储层的地表能量收支和热分层。该分析得到了在85平方公里的Romaine-2水电站水库(50.7°N, 63.2°W)上和周围收集的湍流热通量的多年直接观测的支持,这两个通量塔:一个在岸上全年运行,另一个在无冰条件下在木筏上运行。CSLM模拟了水体的热状态,包括冰的形成和雪的物理,在离线模式下运行,并在2018年6月25日至2021年6月8日期间受到当地天气观测的影响。尽管CSLM模型的一维性质不能解释与水库运行相关的能量输入和输出,但观测值和模拟值的比较证实了CSLM可以合理地再现水库的湍流热通量和温度行为。潜热通量和感热通量的平均误差为- 0.3 W m−2,平均误差为- 2.7 W m−2,在融冰后的头几个月达到最佳效果。该模型对强风事件反应过度,导致随后对水温的估计不准确,最终导致提前冻结。该模型在2019年和2020年将经校正的年蒸汽量分别高估了5%和16%。
期刊介绍:
The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.