自从2013年全球变暖“停滞期”结束后，全球近地表温度快速升高，引起多年冻土状态发生变化。缺乏停滞期前后十年的多年冻土顶板温度数据，制约了人类对多年冻土状态变化的认识。本研究使用高精度土壤表层温度数据驱动TTOP模型生产了2003-2013年和2014-2023年多年冻土顶板温度，并使用站点观测数据进行精度验证，结果表明：2003–2013年和2014–2023年多年冻土顶板温度（小于0 ℃的区域为多年冻土区）的均方根误差分别为1.52 ℃和1.74 ℃，优于现有研究使用其它参数数据驱动TTOP模型生产的近似时期（2000–2016年）多年冻土顶板温度数据（均方根误差为1.89 ℃），特别是多年冻土边界附近（多年冻土顶板温度接近0 ℃的区域）精度提高明显。数据可用于环北极多年冻土范围判别，多年冻土顶板温度变化趋势分析。", "ds_source": "
环北极土壤表层温度数据来自Guo et al.(2024)使用融入多种环境因子并逐月建模的方法生产的2003-2023年逐月高精度土壤表层温度数据（https://doi.org/https://doi.org/10.1016/j.jag.2024.104114）。土地覆盖类型数据来自欧空局发布的GlobCover产品（https://due.esrin.esa.int/page_globcover.php）。土壤r因子数据来自Obu et al.(2019)发布的查找表数据（https://doi.org/10.1016/j.earscirev.2019.04.023）。", "ds_process_way": "
（1）基于土壤表层温度数据分别计算出2003–2013年和2014–2023年平均地表冻结指数和融化指数。\n
（2）参考Obu et al.2019发布的查找表，按不同土地覆盖类型赋值得到环北极地区r因子数据。\n
（3）使用地表冻融指数和r因子数据驱动TTOP模型，计算出2003–2013年和2014–2023年多年冻土顶板温度数据（小于0 ℃的区域为多年冻土区）。", "ds_quality": "
使用测试集站点观测数据对生产的数据集进行精度验证，采用均方根误差（RMSE）和决定系数（R²）作为指标。\n
验证结果表明，生产的2003–2013年和2014–2023年多年冻土顶板温度的均方根误差分别为1.52 ℃和1.74 ℃，优于现有研究使用其它参数数据驱动TTOP模型，生产的近似时期（2000–2016年）平均多年冻土顶板温度产品（均方根误差为1.89 ℃），特别是多年冻土边界附近（多年冻土顶板温度接近0 ℃的区域）精度提高明显。", "ds_acq_start_time": "2003-01-01 00:00:00", "ds_acq_end_time": "2023-12-31 00:00:00", "ds_acq_place": "环北极地区", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 45.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 90.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 288163387, "ds_files_count": 2, "ds_format": "Geotiff", "ds_space_res": "1 km", "ds_time_res": "10年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "596d4b95-5bbf-457b-b248-3369a502660f.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "53943799-d453-4bf2-a141-56c205c1355b", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15", "170.4510" ], "quality_level": 3, "publish_time": "2026-05-13 15:26:15", "last_updated": "2026-05-13 15:39:37", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ARCTIC-CHANGE.DB7142.2026", "i18n": { "en": { "title": "A dataset of permafrost roof temperature in the Arctic from 2003 to 2023", "ds_format": "Geotiff", "ds_source": "
The circum-Arctic soil surface temperature data were obtained from Guo et al. (2024), who produced monthly high-precision soil surface temperature data for 2003–2023 using a multi-factor integration and month-by-month modeling approach (https://doi.org/10.1016/j.jag.2024.104114).\r\nLand cover type data were derived from the European Space Agency’s GlobCover product (https://due.esrin.esa.int/page_globcover.php).\r\nSoil r-factor data were obtained from the lookup table published by Obu et al. (2019) (https://doi.org/10.1016/j.earscirev.2019.04.023).", "ds_quality": "
The accuracy of the generated dataset was validated using in-situ observations from test stations, with the root mean square error (RMSE) and coefficient of determination (R²) used as evaluation metrics.\r\n
Validation results indicate that the RMSEs of the permafrost top temperature for 2003–2013 and 2014–2023 are 1.52 °C and 1.74 °C, respectively—superior to the RMSE of 1.89 °C reported in existing studies that used other parameter datasets to drive the TTOP model for a comparable period (2000–2016). Notably, accuracy near the permafrost boundary (where permafrost top temperatures approach 0 °C) shows a significant improvement.", "ds_ref_way": "", "ds_abstract": "
Since the end of the \"stagnation period\" of global warming in 2013, the global near surface temperature has rapidly increased, causing changes in the permafrost state over the years. The lack of temperature data on the permafrost roof before and after the stagnation period for ten years has constrained human understanding of the changes in permafrost status. This study used high-precision soil surface temperature data to drive the TTOP model to produce permafrost roof temperatures for the years 2003-2013 and 2014-2023, and validated the accuracy using station observation data. The results showed that the root mean square errors of permafrost roof temperatures (areas below 0 ℃ are permafrost regions) for the years 2003-2013 and 2014-2023 were 1.52 ℃ and 1.74 ℃, respectively, which were better than the approximate period (2000-2016) permafrost roof temperature data (root mean square error of 1.89 ℃) produced by other parameter data driven TTOP models in existing research. Especially near the permafrost boundary (areas where permafrost roof temperatures are close to 0 ℃), the accuracy was significantly improved. The data can be used to distinguish the range of permafrost in the Arctic region and analyze the trend of temperature changes in the permafrost roof.", "ds_time_res": "", "ds_acq_place": "Circumpolar region", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
（1）Based on the soil surface temperature data, the mean surface freezing index and thawing index were calculated for the periods 2003–2013 and 2014–2023, respectively.\r\n
（2）Following the lookup table published by Obu et al. (2019), r-factor values were assigned according to different land cover types to generate the circum-Arctic r-factor dataset.\r\n
（3）The surface freezing and thawing indices, together with the r-factor data, were used to drive the TTOP model to compute permafrost top temperatures for 2003–2013 and 2014–2023 (regions with temperatures below 0 °C are defined as permafrost areas).", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 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": [ "多年冻土顶板温度", "环北极", "TTOP模型", "高精度土壤表层温度" ], "ds_subject_tags": [ "大气科学", "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "环北极地区" ], "ds_time_tags": [ 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 ], "ds_contributors": [ { "true_name": "朱文泉", "email": "zhuwq75@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" }, { "true_name": "郭红翔", "email": "202131051035@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "朱文泉", "email": "zhuwq75@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" }, { "true_name": "郭红翔", "email": "202131051035@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "朱文泉", "email": "zhuwq75@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "category": "极地" }