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首页> 外文会议>International conference on cold regions engineering;Canadian permafrost conference >Site-Level Permafrost Simulation in Remote Areas Driven by Atmospheric Re-Analyses: A Case Study from the Northwest Territories
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Site-Level Permafrost Simulation in Remote Areas Driven by Atmospheric Re-Analyses: A Case Study from the Northwest Territories

机译：大气再分析驱动的偏远地区的站点级多年冻土模拟：以西北地区为例

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Simulating permafrost is impeded by the lack of meteorological forcing datasets at most locations of interest. Here, we present the first application of GlobSim, a new Python toolkit that extracts site-level meteorological time series from global atmospheric re-analyses and makes them easily available for forcing permafrost simulations using land-surface models. The software downloads, interpolates, and heuristically scales data to point locations. In this example, we use the model GEOtop and four re-analyses datasets to simulate permafrost in five terrain types that characterize the variability of tundra environments in the Northwest Territories. We evaluated model results using two years of air- and ground-temperature observations from sites near Lac de Gras. The range of observed mean annual ground surface temperatures during the two years was 6.0℃. Results show that the reanalysis data can support permafrost simulations quite well. Compared to individual re-analyses, the ensemble mean improved results for all terrain types. Using the ensemble mean reduced the root-mean-square error by 0.07-1.78℃ for mean annual air temperature, 0.10-0.34℃ for daily ground surface temperature, 0.11-0.31℃ for mean annual ground surface temperature, and 0.08-1.03℃ for surface offset. These results demonstrate that reanalysis-driven ensemble simulation is a promising tool for simulating permafrost in remote locations.
机译：由于大多数感兴趣的位置缺少气象强迫数据集，因此无法模拟多年冻土。在这里，我们介绍了GlobSim的第一个应用程序，它是一个新的Python工具包，可从全球大气重新分析中提取站点级别的气象时间序列，并使它们易于用于使用陆面模型进行永久冻土模拟。该软件下载，插值和启发式缩放数据以指向点位置。在此示例中，我们使用模型GEOtop和四个重新分析数据集来模拟表征西北地区冻土带环境变化的五种地形类型中的多年冻土。我们使用两年来从Lac de Gras附近的地点进行的空气和地面温度观测评估了模型结果。两年中观测到的年平均地表温度范围为6.0℃。结果表明，再分析数据可以很好地支持多年冻土模拟。与单独的重新分析相比，该集成意味着所有地形类型的结果均得到改善。使用集合平均可将平均年均气温的均方根误差降低0.07-1.78℃，将每日平均地表温度降低0.10-0.34℃，将平均年地表温度降低0.11-0.31℃，将平均年地表温度降低0.08-1.03℃表面偏移。这些结果表明，重新分析驱动的集合模拟是用于模拟偏远地区多年冻土的有前途的工具。

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