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中国科学院大学学报 ›› 2014, Vol. 31 ›› Issue (6): 776-782.DOI: 10.7523/j.issn.2095-6134.2014.06.008

• 地球科学 • 上一篇    下一篇

利用气象台站浅层地温资料计算地温梯度的讨论

尹凤玲, 张怀, 石耀霖   

  1. 中国科学院大学地球科学学院 中国科学院计算地球动力学重点实验室, 北京 100049
  • 收稿日期:2013-10-21 修回日期:2014-03-25 发布日期:2014-11-15
  • 通讯作者: 石耀霖
  • 基金资助:

    中国科学院、国家外国专家局创新团队国际合作伙伴计划(KZZD-EW-TZ-19)和国土资源部深部探测技术与实验研究专项(201011073)资助

Discussion about calculation of geothermal gradient based on historical meteorological data

YIN Fengling, ZhANG Huai, SHI Yaolin   

  1. Key Laboratory of Computational Geodynamics of Chinese Academy of Sciences, College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2013-10-21 Revised:2014-03-25 Published:2014-11-15

摘要:

对利用浅地表长时间气象地温序列分析提取稳态地温梯度信息的方法中可能存在的 问题进行讨论,提出改进手段.因为与大地热流密度相联系的地温梯度 一般在0.01~0.03 ℃/m左右,而过去气象地温观测一般仅读数到0.1 ℃,本文认为这样的读数精度很难满足大地热流密度测量的要求,但通过对长时间累积的观测资料进行统计分析等合理的数据处理方法有可能实现突破.本文也讨论了气候变暖趋势对浅表地温梯度的影响.百年尺度地表长期单调增温确实会引起浅表地温梯度的减小,使其偏离构造大地热流密度的地温梯度,但是在百年尺度增温1℃的情况下,计算出的地温梯度误差仍在可接受的范围内,且可以利用气象资料对地温梯度进行校正.利用新一代高精度数字气象地温资料进行大地热流反演是可行的方法,但需要从现在起进行长时间的资料积累.

关键词: 气象地温资料, 地温梯度, 全球变暖, 误差估计

Abstract:

Theoretically, one can calculate the information of steady-state geothermal gradient based on long-term temperature observations near the surface. We point out that it is difficult to determine heat flux in actual implementation by using meteorological records with a precision of 0.1 ℃. However, it may make a breakthrough by statistically analyzing a large amount of accumulated temperature observations. The influence of global warming on shallow geothermal gradient is also discussed. Although the monotonous increase in the ground temperature in a long term of centennial scale indeed leads to the decrease in shallow geothermal gradient and to the deviation from the geothermal gradient connected with heat flux, the calculated geothermal gradient errors are still within an acceptable range if the warming amplitude is within 1 ℃. Deriving geothermal flux based on meteorological data by a high-precision digital thermometer is feasible, but it requires us to accumulate data for a long term from now on.

Key words: meteorological data, geothermal gradient, global warming, error estimation

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