A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data: global borehole inversions
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Dataset overwiew This dataset includes global estimates of ground surface temperature for the period 1465-2000 C.E. The time series were created using the profiles available in the Xibalbá dataset (Cuesta-Valero et al., 2021a,b) and three different methods to estimate the global averages and uncertainties. The values were first retrieved and analyzed with the CIBOR v1 software (Cuesta-Valero et al., 2022a) as documented in Cuesta-Valero et al. (2022b). The datasets in this repository were created by applying three different methods to estimate global means and uncertainties:- The results of a typical Singular Value Decomposition (SVD) analysis based on Beltrami et al. (1992) are provided in the file `singular_value_decomposition.csv`.- The results of a perturbed parameter analysis of the thermal properties of the ground are provided in the file `perturbed_parameter_ensemble.csv`.- The results of a bootstraping estimate from a Monte-Carlo ensemble of inversions are provided in the file `bootstrapping.csv`. IMPORTANT: we recommend using the results of the file `bootstrapping.csv`. The other two files are provided for comparison purposes, but the results of the bootstraping technique are more robust (Cuesta-Valero et al., 2022a). Dataset contents The files contain the ground surface temperature histories from geothermal data from 1465 to 2000, the period with more than 200 subsurface temperature profiles. The first column corresponds to the year, the second column corresponds to the 2.5th percentile, the third column corresponds to the 50th percentile, the fourth column corresponds to the 97.5th percentile, and the fifth column corresponds to the number of subsurface temperature profiles available. All inversions were performed retaining the two largest eigenvalues in the SVD algorithm and considering a step change of 30 years in the retrieved surface signal. Inversions in the `singular_value_decomposition.csv` file consider a constant thermal diffusivity of 1.0e-6 m2 s-1, while the other two files consider a range of diffusivities between 0.5e-6 and 1.5e-6 m2 s-1. The `perturbed_parameter_ensemble.csv` file considers an ensemble of 100 members, while the `bootstrapping.csv` file considers a Monte-Carlo ensemble of 1000 members. Citation instructions Please, indicate the following reference when citing this dataset: Cuesta-Valero, F. J., Beltrami, H., Gruber, S., García-García, A., and González-Rouco, J. F.: A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data, Geosci. Model Dev., 15, 7913–7932, https://doi.org/10.5194/gmd-15-7913-2022, 2022a. Additional resources Access to the CIBOR v1 software used for inverting the profiles: Cuesta-Valero, F. J.: CIBOR: Codes for Inverting BOReholes (1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.7152900, 2022b. Access to the Xibalbá dataset: Cuesta-Valero, F. J., Beltrami, H., García-García, A., González-Rourco, J. F., and García-Bustamante, E.: Xibalbá: Underground Temperature Database, figshare [data set], https://doi.org/10.6084/m9.figshare.13516487.v4, 2021a. For further documentation about the inversion methods considered here: Beltrami, H., Jessop, A. M., and Mareschal, J.-C.: Ground temperature histories in eastern and central Canada from geothermal measurements: evidence of climatic change, Global Planet. Change, 6, 167–183, https://doi.org/10.1016/0921-8181(92)90033-7, 1992. Cuesta-Valero, F. J., García-García, A., Beltrami, H., González-Rouco, J. F., and García-Bustamante, E.: Long-term global ground heat flux and continental heat storage from geothermal data, Clim. Past, 17, 451-468, https://doi.org/10.5194/cp-17-451-2021, 2021b.
数据集概览 本数据集包含公元1465年至2000年的全球地表温度估算结果。其时间序列基于Xibalbá数据集（Cuesta-Valero等，2021a、2021b）中的地下温度剖面，通过三种不同方法估算全球平均值与不确定性。所有数值首先通过CIBOR v1软件（Cuesta-Valero等，2022a）进行提取与分析，具体流程详见Cuesta-Valero等（2022b）的文献。 本存储库中的数据集通过三种不同方法估算全球平均值与不确定性，具体如下： - 基于Beltrami等人（1992）提出的典型奇异值分解（Singular Value Decomposition, SVD）分析结果，存放于`singular_value_decomposition.csv`文件中。 - 地下热物性参数扰动分析结果，存放于`perturbed_parameter_ensemble.csv`文件中。 - 基于蒙特卡洛反演集合的自举估计结果，存放于`bootstrapping.csv`文件中。 重要提示：我们推荐使用`bootstrapping.csv`文件的结果。其余两份文件仅用于对比参考，自举法的估算结果更为稳健（Cuesta-Valero等，2022a）。 数据集内容 本数据集文件包含基于地热数据的1465年至2000年地表温度历史序列，该时段拥有超过200条地下温度剖面。文件各列含义如下：第一列为年份，第二列为2.5%分位数，第三列为50%分位数，第四列为97.5%分位数，第五列为可用地下温度剖面的数量。 所有反演均保留SVD算法中的前两大特征值，并假设提取的地表信号存在30年的阶跃变化。`singular_value_decomposition.csv`文件中的反演采用恒定热扩散率1.0×10^-6 m²·s⁻¹，其余两份文件则采用0.5×10^-6至1.5×10^-6 m²·s⁻¹区间内的热扩散率。`perturbed_parameter_ensemble.csv`文件采用包含100个成员的参数扰动集合，而`bootstrapping.csv`文件则采用包含1000个成员的蒙特卡洛集合。 引用说明 引用本数据集时，请注明以下文献： Cuesta-Valero, F. J., Beltrami, H., Gruber, S., García-García, A., and González-Rouco, J. F.: A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data, Geosci. Model Dev., 15, 7913–7932, https://doi.org/10.5194/gmd-15-7913-2022, 2022a. 附加资源 用于反演温度剖面的CIBOR v1软件获取方式： Cuesta-Valero, F. J.: CIBOR: Codes for Inverting BOReholes (1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.7152900, 2022b. Xibalbá数据集获取方式： Cuesta-Valero, F. J., Beltrami, H., García-García, A., González-Rouco, J. F., and García-Bustamante, E.: Xibalbá: Underground Temperature Database, figshare [data set], https://doi.org/10.6084/m9.figshare.13516487.v4, 2021a. 关于本研究采用的反演方法的更多文献： Beltrami, H., Jessop, A. M., and Mareschal, J.-C.: Ground temperature histories in eastern and central Canada from geothermal measurements: evidence of climatic change, Global Planet. Change, 6, 167–183, https://doi.org/10.1016/0921-8181(92)90033-7, 1992. Cuesta-Valero, F. J., García-García, A., Beltrami, H., González-Rouco, J. F., and García-Bustamante, E.: Long-term global ground heat flux and continental heat storage from geothermal data, Clim. Past, 17, 451-468, https://doi.org/10.5194/cp-17-451-2021, 2021b.
