中国1000年石笋和树轮集成年平均温度重建数据（1000 A.D.-2000 A.D.）

通用环流模式（GCM）的应用可以提高我们对气候强迫的理解。此外，更长的气候记录跨越更广泛的气候状态有助于评估模型的技能，以模拟不同于现在的气候。首先试图找到一种结合不同季节温度影响的代用指标，然后结合北京石笋层序列和祁连树轮序列，在过去的千年里对中国进行大规模的温度重建，与基于GCM的ECH-G模拟中国千年温度记录进行比较。基于31年的平均值（超过P＜0.01），模拟与重建温度记录的相关系数为0.61。由组合的代用指标和模拟系列所显示的不对称V型低频变化是中国上千年温度的主要长期模式，这表明太阳辐照度和温室气体可以解释低频变化的大部分。实验中为了保留低频信息，使用保守的去趋势方法消除与年龄有关的生长趋势。每个树环系列都安装了一个负指数曲线，同时保留所有的变化。
1000年(公元1000年-公元2000年)石笋和树轮集成年平均温度重建数据（excel 表格）的字段包括（4个）：
1）年份
2）年平均温度重建
3）重建温度偏差
4）模拟温度偏差

Application of General Circulation Models (GCMs) enhances our understanding of climate forcing.
Additionally, longer climate records spanning a wider range of climatic states facilitate the assessment of model performance in simulating climates distinct from the present.
We first developed a proxy indicator that integrates temperature influences across different seasons, then combined stalagmite layer sequences from Beijing and tree-ring sequences from the Qilian Mountains to conduct a large-scale temperature reconstruction for China over the past millennium, and compared the reconstruction with the millennial temperature record of China simulated by the GCM-based ECH-G model.
Based on 31-year averaged values (P < 0.01), the correlation coefficient between the simulated and reconstructed temperature records is 0.61.
The asymmetric V-shaped low-frequency variations revealed by the combined proxy indicators and simulated series represent the dominant long-term pattern of China's millennial-scale temperatures, suggesting that solar irradiance and greenhouse gases can explain most of these low-frequency changes.
To preserve low-frequency information in this study, a conservative detrending method was employed to eliminate age-related growth trends.
A negative exponential curve was fitted to each tree-ring series while retaining all temporal variability.
The compiled annual mean temperature reconstruction dataset (Excel spreadsheet) based on stalagmite and tree-ring records spanning 1000 CE to 2000 CE includes the following four fields:
1) Year
2) Annual mean temperature reconstruction
3) Reconstructed temperature anomaly
4) Simulated temperature anomaly

搜集汇总

背景与挑战

背景概述

该数据集覆盖公元1000年至2000年，基于中国北京石笋和祁连树轮序列，结合代用指标重建了千年年平均温度，用于评估气候模型模拟能力。重建数据与通用环流模式（ECH-G）模拟记录比较，相关系数为0.61，揭示太阳辐照度和温室气体是温度低频变化的主要驱动因素。数据以表格形式提供，包括年份、温度重建值及其偏差字段，支持长期气候研究。