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Environmental controls on ground temperature and permafrost in Labrador, northeast Canada

机译:加拿大东北部拉布拉多的地面温度和多年冻土环境控制

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Field data from 83 environmental monitoring stations across Labrador, 17 with permafrost, were used to analyze the interrelationships of key variables considered in the temperature at the top of permafrost model. Snow depth, not mean annual air temperature, was the strongest climatic determinant of mean temperatures at the ground surface and at the base of the annual freeze-thaw layer, and its variability was most closely related to land cover class. A critical late-winter snow depth of 70 cm or more was inferred to be sufficient to prevent the formation of permafrost at the monitoring sites, which meant that permafrost was absent beneath forest but present in some tundra, peatland and bedrock locations. Analyses showed no statistically significant relations identified between topographic indices and various station parameters, challenging their utility for regional modeling. Testing of several different land cover datasets for model parameterization gave errors in ground surface temperature ranging from +/- 0.9 to 2.1 degrees C. These results highlight the importance of local field data and emphasize the necessity of high-quality national-scale land cover datasets suitable for permafrost modeling.
机译:来自拉布拉多地区83个环境监测站的现场数据(其中17个具有多年冻土)被用于分析永久冻土模型顶部温度中考虑的关键变量之间的相互关系。雪深而不是年平均气温是决定地面和年冻融层底部平均温度的最强气候决定因素,其变化与土地覆盖类别最密切相关。据推断,冬季末临界雪深为70 cm或以上足以防止在监测点形成永久冻土,这意味着永久冻土在森林下方不存在,但存在于冻原,泥炭地和基岩中。分析表明,在地形指数和各种测站参数之间没有发现统计上显着的关系,这对区域建模的实用性提出了挑战。对几个不同的土地覆盖数据集进行模型参数化测试得出的地表温度误差范围为+/- 0.9至2.1摄氏度。这些结果突出了当地野外数据的重要性,并强调了高质量国家级土地覆盖数据集的必要性适用于多年冻土模型。

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