Use of a thermal imager for snow pit temperatures
Use of a thermal imager for snow pit temperatures
复制标题
使用热像仪测量雪坑温度
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
K. Birkeland
中科院分区：
文献类型：
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作者：
C. Shea;B. Jamieson;K. Birkeland
雪崩预报所关注的弱雪通常以薄层的形式形成和变化。温度计是目前用于测量这些层的温度梯度并由此估计预期的蒸汽通量和未来晶体变质类型的现场技术，但在小于1厘米的距离上难以使用。相比之下，热成像仪可以在小距离内提供数千个同时进行的温度测量，并且精度更高。然而，热成像仪只感测暴露的表面，使其访问和准确的埋藏温度的方法复杂化。本文介绍了暴露坑壁上埋层的方法，并使用热成像仪测量这些墙壁上的温度，雪校正透镜效应，调整温度梯度，调整暴露时间，并计算毫米距离上的温度梯度。我们发现透镜的温度梯度误差在图像中心和角落之间为0.03 °C的量级。我们发现温度梯度随时间的变化通常会降低-正如预期的那样，大气均衡是一种强烈的影响。案例研究，包括热图像和视觉宏观照片的晶体，在2010-2011年冬季收集，证明了大的温度差异超过毫米级的距离，与观察到的动力变质作用。需要进一步研究，以使用独立于支持梯度数据的绝对温度。
Weak snow of interest to avalanche forecasting often forms and changes as thin layers. Thermometers, the current field technology for measuring the temperature gradients across such layers – and for thus estimating the expected vapour flux and future type of crystal metamorphism – are difficult to use at distances shorter than 1 cm. In contrast, a thermal imager can provide thousands of simultaneous temperature measurements across small distances with better accuracy. However, a thermal imager only senses the exposed surface, complicating its methods for access and accuracy of buried temperatures. This paper presents methods for exposing buried layers on pit walls and using a thermal imager to measure temperatures on these walls, correct for lens effects with snow, adjust temperature gradients, adjust time exposed, and calculate temperature gradients over millimetre distances. We find lens error on temperature gradients to be on the order of 0.03 °C between image centre and corners. We find temperature gradient change over time to usually decrease – as expected with atmospheric equalization as a strong effect. Case studies including thermal images and visual macro photographs of crystals, collected during the 2010–2011 winter, demonstrate large temperature differences over millimetre-scale distances that are consistent with observed kinetic metamorphism. Further study is needed to use absolute temperatures independently of supporting gradient data.