地表太阳辐射(SSR)是地表能量流动的重要因素，可以准确捕捉长期气候变化，了解地球大气系统的能量平衡。
\n全球综合和均质化的太阳表面辐射数据集包括均质化的SSR数据集(SSRIHgrid)和人工智能重构的SSR数据集(SSRIH20CR)。SSRIHgrid是一个5°×5°均匀化的全球月度SSR异常数据集，SSRIH20CR是基于20CRv3人工智能模型的5°×2.5°全覆盖月度陆地(南极洲除外)SSR异常重建数据集。", "ds_source": "
原始SSR数据主要有两个来源:苏黎世联邦理工学院GEBA数据来自1922年至2020年全球分布的2445个站点的月度数据;WRDC数据来自1964年以来全球分布的1136个站点的月度数据。", "ds_process_way": "
基于GEBA和WRDC的原始观测SSRs，结合其他已有的均一化SSR数据集，对全球站观测进行了整合。此外，还使用RHtestV4软件包对全球分布的站点数据进行了均匀化。随后使用改进的CNN深度学习算法重建SSR异常。基于训练集(20CRv3)，获得1955-2018年SSR异常重构数据集SSRIH2ocR，分辨率为5°× 2.5°。", "ds_quality": "
数据质量较好。", "ds_acq_start_time": "1955-01-01 00:00:00", "ds_acq_end_time": "2018-12-31 00:00:00", "ds_acq_place": "中国,日本,欧洲,意大利", "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": 28155659, "ds_files_count": 2, "ds_format": "NC", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "c09739c5-9f1c-4f8a-9bfa-5ec83e90299e.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a4dd5849-78f2-44c5-b0f1-3450e952b2a2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 3, "publish_time": "2023-12-27 14:54:22", "last_updated": "2026-01-14 11:00:11", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.FIGSHARE.DB4155.2023", "i18n": { "en": { "title": "Global Integrated and Uniform Solar Surface Radiation Dataset (1955-2018)", "ds_format": "nc", "ds_source": "
The original SSR data mainly comes from two sources: the GEBA data from the Federal Institute of Technology Zurich comes from monthly data from 2445 globally distributed sites from 1922 to 2020; The WRDC data comes from monthly data from 1136 globally distributed sites since 1964.", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
Surface solar radiation (SSR) is an important factor in surface energy flow, which can accurately capture long-term climate change and understand the energy balance of the Earth's atmospheric system
\nThe globally integrated and homogenized solar surface radiation dataset includes the homogenized SSR dataset (SSRIHgrid) and the artificial intelligence reconstructed SSR dataset (SSRIH20CR). SSRIHgrid is a 5 ° × A global monthly SSR anomaly dataset with 5 ° homogenization, SSRIH20CR is based on a 20CRv3 artificial intelligence model with 5 ° × 2.5 ° full coverage monthly land (excluding Antarctica) SSR anomaly reconstruction dataset.
", "ds_time_res": "", "ds_acq_place": "China, Japan, Europe, Italy", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Based on the original observation SSRs of GEBA and WRDC, combined with other existing homogenized SSR datasets, global station observations were integrated. In addition, the RHtestV4 software package was also used to homogenize the globally distributed site data. Subsequently, an improved CNN deep learning algorithm was used to reconstruct SSR anomalies. Based on the training set (20CRv3), obtain the SSR anomaly reconstruction dataset SSRIH2ocR from 1955 to 2018 with a resolution of 5 ° × 2.5 °.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "ds_topic_tags": [ "地表太阳辐射", "均质化", "人工智能", "重建" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国", "日本", "欧洲", "意大利" ], "ds_time_tags": [ 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 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 ], "ds_contributors": [ { "true_name": "李庆祥", "email": "liqingx5@mail.sysu.edu.cn", "work_for": "中山大学大气科学学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "李庆祥", "email": "liqingx5@mail.sysu.edu.cn", "work_for": "中山大学大气科学学院", "country": "中国" } ], "ds_managers": [ { "true_name": "李庆祥", "email": "liqingx5@mail.sysu.edu.cn", "work_for": "中山大学大气科学学院", "country": "中国" } ], "category": "气象" }