欧亚亚北极现代气候条件下积雪期土壤温度变化规律

L. Kitaev
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引用次数: 0

摘要

通过定量评价参数的季节和长期变化特征,研究了欧亚亚北极地区现代气候条件下积雪对土壤温度动态的影响。稳定雪期土壤温度的季节性和长期值自西向东递减:欧亚大陆自西向东的雪厚和气温递减导致积雪隔热性能减弱,区域气温显著降低。随着稳定积雪的出现,土壤温度的季节和长期标准差较秋季和春季显著降低。积雪出现后,土壤温度标准差较秋春季显著下降。西伯利亚东北部是个例外:在这里,相对较小的积雪厚度决定了土壤温度过程对地表气温动态的明显依赖。冬季土壤温度变异性较低,长期变化趋势不明显。对所研究的特征异常的过程分析表明,它们的巧合数量微不足道且非系统。目前,我们还没有在大范围内发现类似的研究结果。所揭示的模式可用于分析陆地表面状况监测结果、发展遥感算法、改进环境变化的预测情景。
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Regularities of soil temperature changes during the period with snow cover in modern climatic conditions of the Eurasian Subarctic
The influence of snow cover on the dynamics of soil temperature in the modern climatic conditions of the Eurasian Subarctic was investigated through a quantitative assessment of the features of the seasonal and long-term variation of parameters. Seasonal and long-term values of soil temperature for stable snow period decrease from west to east: a decrease of snow thickness and air temperature from west to east of Eurasia leads to a weakening of the heat-insulating properties of the snow cover with a significant decrease in regional air temperatures. With the emergence of a stable snow cover, the soil temperature seasonal and long-term standard deviation sharply decreases compared to the autumn and spring periods. With the appearance of snow cover, the soil temperature standard deviation drops sharply compared to the autumn and spring periods. An exception is the northeast of Siberia: here, a relatively small thickness of snow determines a noticeable dependence of the course of soil temperature on the dynamics of surface air temperature. There are no significant long-term trends in soil temperature due to its low variability during winter period. Analysis of the course of the studied characteristics anomalies showed an insignificant and non-systematic number of their coincidences. Currently, we have not found similar research results for large regions. The revealed patterns can be used in the analysis of the results of monitoring the state of the land surface, in the development of remote sensing algorithms, in the refinement of predictive scenarios of environmental changes.
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12 weeks
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