High resolution snow distribution data from complex Arctic terrain: A tool for model validation
High resolution snow distribution data from complex Arctic terrain: A tool for model validation
复制标题
来自复杂北极地形的高分辨率雪分布数据：模型验证工具
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
A. Sandvik
中科院分区：
文献类型：
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作者：
C. Jaedicke;A. Sandvik
抽象的。吹雪和雪堆是北极的常见特征。由于植被稀疏，气温低，风速大，积雪不断移动。这给受影响地区的交通和基础设施造成严重问题。为了最大限度地减少新结构设计阶段的积雪影响，必须开发和测试适当的模型。在这项研究中，1999年和2000年春季在两个研究区的北极地形积雪分布调查。积雪深度通过探地雷达和人工方法测量。研究区域面积为4乘4公里，部分被冰川覆盖。调查结果显示了侵蚀、堆积区和积雪随时间演变的明显模式。这种高分辨率的数据集是有价值的数值模式的验证。使用一个简单的数值雪漂模型来模拟1998/1999年冬季其中一个地区的实测积雪分布。该模式是一个耦合到风场的两层漂移模式，由中尺度气象模式生成。模拟基于来自主导风向的五个风场。该模型产生了一个令人满意的积雪分布，但未能再现所观察到的积雪的细节。结果清楚地表明，高质量的现场数据的重要性，以检测和分析数值模拟中的错误。
Abstract. Blowing snow and snow drifts are common features in the Arctic. Due to sparse vegetation, low temperatures and high wind speeds, the snow is constantly moving. This causes severe problems for transportation and infrastructure in the affected areas. To minimise the effect of drifting snow already in the designing phase of new structures, adequate models have to be developed and tested. In this study, snow distribution in Arctic topography is surveyed in two study areas during the spring of 1999 and 2000. Snow depth is measured by ground penetrating radar and manual methods. The study areas encompass four by four kilometres and are partly glaciated. The results of the surveys show a clear pattern of erosion, accumulation areas and the evolution of the snow cover over time. This high resolution data set is valuable for the validation of numerical models. A simple numerical snow drift model was used to simulate the measured snow distribution in one of the areas for the winter of 1998/1999. The model is a two-level drift model coupled to the wind field, generated by a mesoscale meteorological model. The simulations are based on five wind fields from the dominating wind directions. The model produces a satisfying snow distribution but fails to reproduce the details of the observed snow cover. The results clearly demonstrate the importance of quality field data to detect and analyse errors in numerical simulations.