本数据集整合了来自ICE-D（Informal Cosmogenic-Nuclide Exposure-age Database）的北半球802个冰碛垄的4003个10Be暴露年龄数据（时间跨度为26.5-10 ka）。所有暴露年龄均采用统一的全球平均10Be产率和LSDn产率缩放模型进行重新计算，并运用P-CAAT（Probabilistic Cosmogenic Age Analysis Tool）方法重新确定了冰碛垄年龄。数据集完整记录了每个冰碛垄的数据来源、ICE-D中的冰碛垄名称及样品编号，包含样品类型、单个样品的年龄及其1σ内外部误差等详细信息。同时，还提供了P-CAAT计算过程中使用的带宽估计类型、带宽大小、拟合R2值，以及最终确定的冰碛垄峰值年龄及其1σ内外部误差和所选高斯组分包含的样品数量。数据覆盖亚洲、欧洲、北美及格陵兰等主要冰川区，是目前北半球尺度上最系统、最完整的末次冰盛期至早全新世冰川年代学数据集。该数据集显著提升了冰川退缩历史的解析精度，为研究末次冰消期冰川-气候相互作用、校验古气候模型以及重建古冰量变化提供了重要基础数据支持。", "ds_source": "
本研究使用的原始冰碛垄10Be年龄数据均来自国际公开数据库ICE-D（Informal Cosmogenic-Nuclide Exposure-age Database，访问地址：https://version2.ice-d.org/），单个冰碛垄年龄计算采用P-CAAT（Probabilistic Cosmogenic Age Analysis Tool）分析工具完成（工具获取网址：https://kgs.uky.edu/anorthite/PCAAT）。", "ds_process_way": "
（1）从ICE-D数据库提取原始10Be暴露年龄数据后，随后按照包含≥3个年龄数据且年龄介于26.5-10 ka的标准筛选冰碛垄，并限定样品类型为漂砾、砾石和卵石；（2）采用P-CAAT工具的概率密度估计方法，通过Mean、MADD和Std/IQR三种带宽估计器将年龄数据分解为高斯组分，以最大R²值为标准选择最优带宽，并选取概率最大的高斯组分作为冰碛垄代表性年龄（含峰值年龄±1σ误差及样品数量），最终保留重算后年龄在26.5-10 ka范围内的数据。", "ds_quality": "
所有年龄数据均提供1σ内外误差范围。P-CAAT计算通过χ²最小化优化（Levenberg-Marquardt算法，最大1000次迭代）和蒙特卡洛扰动（典型1-20次循环）分解高斯组分，峰值年龄误差整合测量误差与系统误差。总不确定度通过公式t = σ + P*mean((E-I)/A)量化地质继承效应影响。", "ds_acq_start_time": "1990-01-01 00:00:00", "ds_acq_end_time": "2024-12-31 00:00:00", "ds_acq_place": "北半球", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 1677188, "ds_files_count": 2, "ds_format": "Excel", "ds_space_res": null, "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "6db9eea3-bda1-4af5-8bfa-a1f0e7f15810.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2025-08-18 09:41:31", "last_updated": "2025-08-18 09:45:17", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.GLACIAL_GEOCHRONOLOGY.DB6941.2025", "i18n": { "en": { "title": "10Be exposure ages of moraines in the Northern Hemisphere from the Last Glacial Maximum to the Early Holocene (26.5–10 ka)", "ds_format": "", "ds_source": "
The original 10Be exposure age data of moraines used in this study were obtained from the ICE-D (Informal Cosmogenic-Nuclide Exposure-age Database, available at: https://version2.ice-d.org/). The calculation of individual moraine ages was performed using the P-CAAT (Probabilistic Cosmogenic Age Analysis Tool, available at: https://kgs.uky.edu/anorthite/PCAAT).", "ds_quality": "
All age data are provided with complete 1σ internal and external error ranges. The P-CAAT calculations employ χ² minimization optimization (Levenberg-Marquardt algorithm, maximum 1000 iterations) and Monte Carlo perturbation (typically 1-20 cycles) to decompose Gaussian components, with peak age errors incorporating both measurement and systematic uncertainties. The total uncertainty is quantified through the formula t = σ + P*mean((E-I)/A) to account for geological inheritance effects.", "ds_ref_way": "", "ds_abstract": "
This dataset integrates 4,003 10Be exposure ages from 802 moraines across the Northern Hemisphere (spanning 26.5-10 ka) sourced from the ICE-D (Informal Cosmogenic-Nuclide Exposure-age Database). All exposure ages were recalculated using a consistent global average 10Be production rate and the LSDn production rate scaling model, with moraine ages determined through P-CAAT (Probabilistic Cosmogenic Age Analysis Tool) analysis.The dataset comprehensively documents each moraine's data source, corresponding ICE-D moraine name and sample IDs, including sample type, individual sample ages with their 1σ internal and external errors. It also provides detailed parameters from the P-CAAT calculations: bandwidth estimator type, bandwidth size, goodness-of-fit R² values, final moraine peak ages with their 1σ internal and external errors, and the number of samples included in the selected Gaussian component.Covering major glacial regions including Asia, Europe, North America and Greenland, this represents the most systematic and complete glacial chronology dataset for the Last Glacial Maximum through Early Holocene at a Northern Hemisphere scale. The dataset significantly improves the resolution for reconstructing glacial retreat history and provides essential baseline data for studying glacier-climate interactions during the last deglaciation, validating paleoclimate models, and reconstructing paleo-ice volume changes.
", "ds_time_res": "年", "ds_acq_place": "Northern Hemisphere", "ds_space_res": "", "ds_projection": "", "ds_process_way": "(1) After extracting the original 10Be exposure age data from the ICE-D database, moraines were selected based on the criteria of containing ≥3 age data points within the 26.5-10 ka range, with sample types restricted to boulders, cobbles, and pebbles; (2) Using the probabilistic density estimation method of the P-CAAT tool, the age data were decomposed into Gaussian components through three bandwidth estimators (Mean, MADD, and Std/IQR). The optimal bandwidth was selected based on the maximum R² value, and the Gaussian component with the highest probability was chosen as the representative moraine age (including peak age ±1σ error and sample count). Finally, only recalculated ages within the 26.5-10 ka range were retained.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "北半球", "P-CAAT", "ICE-D", "10Be年龄" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "甘肃省" ], "ds_time_tags": [ 1990, 2024 ], "ds_contributors": [ { "true_name": "郑超刚", "email": "201301006@njnu.edu.cn", "work_for": "南京师范大学", "country": "中国" }, { "true_name": "赵志军", "email": "zhaozhijun@njnu.edu.cn", "work_for": "南京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "郑超刚", "email": "201301006@njnu.edu.cn", "work_for": "南京师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "赵志军", "email": "zhaozhijun@njnu.edu.cn", "work_for": "南京师范大学", "country": "中国" } ], "category": "冰川" }