北半球多年冻土数据集（1986-2098年）是根据Kudryavtsev模型算出的多年冻土融化深度处的温度（℃），其中，温度小于零的区域表示存在多年冻土。此数据集包含在Historical(1986-2005年)以及RCP2.6、RCP4.5、RCP8.5三种未来排放情景下（2006-2098年）北半球多年冻土融化深度处的温度数据。数据集覆盖时间为1986-2098年，共计93年。其时间分辨率为年尺度，空间分辨率为1°×1°。
", "ds_source": "参与CMIP5计划的5个模式在HIS、RCP2.6、RCP4.5、RCP8.5情景下的月平均温度、降水、土壤湿度数据集。在HIS情景下，数据长短为1986-2005年，各RCP情景下数据长度为2006-2098年。数据下载网址为http://www.ipcc-data.org/sim/gcm_monthly/AR5/Reference-Archive.html。
", "ds_process_way": "首先将各模式温度、降水、土壤湿度数据统一插值到1°×1°格点上。然后使用Kudryavtsev方法计算得到冻结融化深度处的温度。\nKudryavtsev模型具体计算过程见：Anisimov O.A., N.I. Shiklomanov and F.E. Nelson. Global warming and active-layer thickness: results from transient general circulation models. Global and Planetary Change. 15, 61-77 (1997).
", "ds_quality": "1、在模式筛选过程中，通过对比CMIP5模式数据在北半球区域与再分析资料的时空分布、相关系数等，选取了在北半球适用性较好，与再分析资料时空分布较为一致且相关性较高的五个模式，完成了模式的优选过程。2、数据处理、插值过程中逐步与原数据进行对比，每一步进行了严格的检查，确保了数据的准确性。3、使用本数据集估算的多年冻土面积与IPA观测结果进行比较，从空间分布于数值上均高度接近，北半球多年冻土面积在数值上偏差小于3%。综上，本数据集在北半球适用性较好，数据质量合格。
", "ds_acq_start_time": "1986-01-01 00:00:00", "ds_acq_end_time": "2005-12-31 00:00:00", "ds_acq_place": "北半球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 0.0, "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": "apply-access", "ds_total_size": 17676791, "ds_files_count": 3, "ds_format": "nc", "ds_space_res": "", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "31302b03-5442-44cc-b156-51fe0041d0b7.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "使用本数据集时，请在文章中标注数据来源：国家重点基础研究发展计划（973计划）“冰冻圈变化及其影响研究”", "ds_from_station": null, "organization_id": "b3c14ec7-0cc1-417f-8986-b6fc1352242f", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [], "quality_level": 3, "publish_time": "2020-12-03 08:55:14", "last_updated": "2026-05-12 11:44:26", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.CCI.2020.67", "i18n": { "en": { "title": "Northern Hemisphere Permafrost Dataset (1986-2098)", "ds_format": "nc", "ds_source": "Monthly average temperature, precipitation, and soil moisture datasets for the five modes participating in the CMIP5 program under HIS, RCP2.6, RCP4.5, and RCP8.5 scenarios. In the HIS scenario, the data length is from 1986 to 2005, while in each RCP scenario, the data length is from 2006 to 2098. The data download website is http://www.ipcc-data.org/sim/gcm_monthly/AR5/Reference-Archive.html 。
", "ds_quality": "1、 In the process of pattern selection, by comparing the spatiotemporal distribution and correlation coefficient of CMIP5 pattern data with reanalysis data in the northern hemisphere region, five patterns with good applicability in the northern hemisphere, consistent spatiotemporal distribution with reanalysis data, and high correlation were selected to complete the pattern selection process. 2. During the data processing and interpolation process, the data is gradually compared with the original data, and each step is rigorously checked to ensure the accuracy of the data. 3. The estimated permafrost area using this dataset is compared with the IPA observation results, and the spatial distribution is highly similar numerically. The numerical deviation of the permafrost area in the northern hemisphere is less than 3%. Overall, this dataset has good applicability in the Northern Hemisphere and meets the required data quality standards.
", "ds_ref_way": "", "ds_abstract": "The Northern Hemisphere Permafrost Dataset (1986-2098) is the temperature (℃) at the depth of permafrost melting calculated based on the Kudryavtsev model, where areas with temperatures below zero indicate the presence of permafrost. This dataset contains temperature data at the depth of permafrost melting in the Northern Hemisphere under three future emission scenarios: Historical (1986-2005) and RCP2.6, RCP4.5, and RCP8.5 (2006-2098). The dataset covers the period from 1986 to 2098, totaling 93 years. Its time resolution is on an annual scale, and its spatial resolution is 1 °× 1 °.
", "ds_time_res": "", "ds_acq_place": "Northern Hemisphere", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Firstly, interpolate the temperature, precipitation, and soil moisture data of each mode uniformly onto a 1 °× 1 ° grid point. Then use the Kudryavtsev method to calculate the temperature at the depth of freezing and melting.\r\nThe specific calculation process of Kudryavtsev model is shown in: Anisimov O.A., N.I. Shiklomanov and F.E. Nelson. Global warming and active-layer thickness: results from transient general circulation models. Global and Planetary Change. 15, 61-77 (1997).
", "ds_ref_instruction": "When using this dataset, please indicate the data source in the article: \"Research on Cryosphere Changes and Their Effects\" under the National Key Basic Research Development Program (973 Program)" } }, "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, "belong_to_nieer": false, "ds_topic_tags": [ "北半球", "多年冻土", "面积" ], "ds_subject_tags": [], "ds_class_tags": [], "ds_locus_tags": [ "北半球" ], "ds_time_tags": [ 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067, 2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079, 2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091, 2092, 2093, 2094, 2095, 2096, 2097, 2098 ], "ds_contributors": [ { "true_name": "王澄海", "email": "wch@lzu.edu.cn", "work_for": "兰州大学大气科学学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "王澄海", "email": "wch@lzu.edu.cn", "work_for": "兰州大学大气科学学院", "country": "中国" } ], "ds_managers": [ { "true_name": "王澄海", "email": "wch@lzu.edu.cn", "work_for": "兰州大学大气科学学院", "country": "中国" } ], "category": "冻土" }