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Instruments and methods - A physically based method for correcting temperature profile measurements made using thermocouples

机译:仪器和方法-一种基于物理的方法来校正使用热电偶进行的温度分布测量

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摘要

High-frequency (diurnal) temperature variations occur simultaneously at multiple depths separated by meters of snow in at least several and probably many Arctic and Antarctic thermocouple datasets. These temperature variations cannot be caused by heat conduction from the surface because their amplitudes are too large and there is no phase lag with depth, and they cannot be caused by heat advection because the air flux required is greater than is available. Rather, the simultaneous temperature variations (STVs) appear to originate within the box that houses the data logger as thermocouple-like offset voltages, wire heating or thermistor error. The STVs can be corrected by requiring that the temperatures vary smoothly with time at the greatest depth at which temperature is measured. The correction voltage determined in this fashion, when applied to the thermocouples at other depths, corrects the entire dataset. The method successfully removes STVs with 24 hour period that are up to 3.8 degrees C in amplitude, and is superior to the averaging techniques commonly used to correct thermocouple data because it introduces no spurious (non-physical) temperature variations. The correction method described can be applied to all thermocouple data where temperature measurements have been made at depths similar to 0.5 m into the snowpack. The corrections should allow more physical process and parameter information to be extracted more confidently from existing firm temperature data. Identification of the STVs and their probable cause also suggests how better data might be collected in the future.
机译:在至少几个(可能还有许多)北极和南极热电偶数据集中,高频(昼夜)温度变化同时发生在被几米积雪隔开的多个深度处。这些温度变化不能由表面的热传导引起,因为它们的幅度太大并且没有随深度的相位滞后,也不能由热对流引起,因为所需的空气通量大于可用的通量。相反,同时温度变化(STV)似乎是在装有数据记录器的盒子内产生的,就像热电偶一样的偏移电压,导线发热或热敏电阻误差。通过要求温度在测量温度的最大深度处随时间平稳变化,可以校正STV。以这种方式确定的校正电压在应用于其他深度的热电偶时会校正整个数据集。该方法成功去除了振幅高达3.8摄氏度的24小时周期的STV,并且由于它不会引入虚假(非物理)温度变化,因此优于通常用于校正热电偶数据的平均技术。所描述的校正方法可以应用于所有热电偶数据,其中已经在进入积雪的深度约0.5 m处进行了温度测量。这些修正应允许从现有的公司温度数据中更可靠地提取更多的物理过程和参数信息。 STV的标识及其可能的原因还表明,将来如何收集更好的数据。

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