本数据集面向中国自然冷能资源的定量评价、空间识别与区域利用研究，基于1973-2024年中国气象站日平均气温资料构建。原始资料包含798个气象站，经数据完整性与长期代表性筛选后保留771个有效站点。在日平均气温数据基础上，计算冷季持续时间（D0）、冻结度日（FDD）、融化度日（TDD）、有效冻结度日（F−2）等基础指标，并进一步构建冷季持续时间因子（D）、冷热平衡比（TEMP）和冻结质量因子（F）。在此基础上建立综合冷能质量与平衡指数（Integrated Cold Quality and Balance Index，ICQBI），用于表征区域自然冷能资源的综合气候潜力。ICQBI采用乘法型非补偿结构，将自然冷能的时间可利用性、全年冷热平衡特征和有效冻结质量综合考虑。其中，冷季定义为日平均气温低于0 ℃的时期，−2 ℃作为区分近冻结弱冷条件与较强冻结条件的操作参考温度。基于771个有效站点的长期评价结果，采用普通克里金（Ordinary Kriging）方法进行空间插值，并按照ICQBI阈值0.01、0.03、0.10和0.20划分为匮乏区、边缘区、可利用区、丰富区和极丰富区五个自然冷能资源等级。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": "1973-01-01 00:00:00", "ds_acq_end_time": "2024-12-31 00:00:00", "ds_acq_place": "中国", "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": "apply-access", "ds_total_size": 12106572, "ds_files_count": 0, "ds_format": "*csv,*.jpg", "ds_space_res": "", "ds_time_res": "日", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "e600a63e-1f62-4892-b601-c585c984b71e.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "None", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": null, "ds_serv_phone": null, "ds_serv_mail": null, "doi_value": "", "subject_codes": [ "170.1535", "170.4510" ], "quality_level": 0, "publish_time": "2026-08-28 09:40:10", "last_updated": "2026-08-28 09:40:10", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.energy.db7741.2026", "i18n": { "en": { "title": "Dataset of Integrated Assessment of Renewable Cold Energy Resources in China Based on ICQBI, 1973–2024", "ds_format": "*csv,*.jpg", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
This dataset is aimed at quantitative evaluation, spatial identification and regional utilization research of China's natural cold energy resources. It is constructed based on the daily average temperature data of China Meteorological Station from 1973 to 2024. The original data includes 798 meteorological stations, and 771 valid stations are retained after data integrity and long-term representativeness screening. Based on the daily average temperature data, basic indicators such as cold season duration (D0), freezing degree days (FDD), melting degree days (TDD), and effective freezing degree days (F−2) are calculated, and the cold season duration time factor (D), cool-heat balance ratio (TEMP), and freezing quality factor (F) are further constructed. On this basis, the Integrated Cold Quality and Balance Index (ICQBI) was established to characterize the comprehensive climate potential of regional natural cold energy resources.\r\n\r\nICQBI adopts a multiplicative non-compensated structure that comprehensively considers the time availability of natural cooling energy, the year-round cold and heat balance characteristics, and the effective freezing quality. Among them, the cold season is defined as the period when the daily average temperature is lower than 0 ℃, and −2 ℃ is used as the operating reference temperature to distinguish near-freezing weak cold conditions from strong freezing conditions. Based on the long-term evaluation results of 771 effective stations, the Ordinary Kriging method was used for spatial interpolation, and the natural cold energy resource levels were divided into five levels: scarce area, marginal area, usable area, rich area and extremely rich area according to ICQBI thresholds of 0.01, 0.03, 0.10 and 0.20.\r\n\r\nThe dataset also constructed annual ICQBI sequences for 771 sites from 1973 to 2024. For missing years, on the basis of retaining existing observation results, annual anomaly information from nearby long-term stations is used to reconstruct to form a complete 52-year annual series. On this basis, short-term statistical forecasts from 2025 to 2034 are carried out through the site-level ARIMA model and rolling starting point verification method. This dataset can be used for research on the spatial distribution and long-term changes of natural cold energy resources in China, zoning of natural cold energy resources, regional comparison, preliminary screening of the suitability of seasonal cold storage and natural cooling technologies, and related climate change and low-carbon refrigeration research. It should be noted that ICQBI is a national-scale climate resource screening indicator and does not directly represent the actual cooling capacity, cold storage efficiency or economic benefits of specific engineering systems.", "ds_time_res": "日", "ds_acq_place": "China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "", "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, "belong_to_nieer": false, "allow_update_data": false, "ds_topic_tags": [ "自然冷能", "综合冷能质量与平衡指数", "资源评价", "空间分区" ], "ds_subject_tags": [ "气候学", "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 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 ], "ds_contributors": [ { "true_name": "张泽", "email": "zez@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "孟祥熙", "email": "mxx@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "李冶平", "email": "liyeping2030@163.com", "work_for": "黑龙江省自然资源调查院", "country": "中国" }, { "true_name": "王恩宝", "email": "95223937@qq.com", "work_for": "黑龙江省自然资源调查院", "country": "中国" }, { "true_name": "鞠梦瑶", "email": "2024122057@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "Andrei Zhang", "email": "zhang0993@yandex.ru", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "袁鑫宇", "email": "yxy69z@126.com", "work_for": "国网哈尔滨供电公司", "country": "中国" }, { "true_name": "袁名扬", "email": "ymy@nefu.edu.cn", "work_for": "黑龙江省生态地质调查研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "张泽", "email": "zez@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "孟祥熙", "email": "mxx@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "李冶平", "email": "liyeping2030@163.com", "work_for": "黑龙江省自然资源调查院", "country": "中国" }, { "true_name": "王恩宝", "email": "95223937@qq.com", "work_for": "黑龙江省自然资源调查院", "country": "中国" }, { "true_name": "鞠梦瑶", "email": "2024122057@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "Andrei Zhang", "email": "zhang0993@yandex.ru", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "袁鑫宇", "email": "yxy69z@126.com", "work_for": "国网哈尔滨供电公司", "country": "中国" }, { "true_name": "袁名扬", "email": "ymy@nefu.edu.cn", "work_for": "黑龙江省生态地质调查研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "张泽", "email": "zez@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" } ], "category": "气象" }