{
    "created": "2023-11-24 10:00:51",
    "updated": "2026-05-07 10:05:11",
    "id": "ac27e876-72f4-419a-9655-3763d1ef9250",
    "version": 6,
    "ds_topic": null,
    "title_cn": "中国月地面太阳辐射数据集（2000-2017年）",
    "title_en": "Monthly surface solar radiation data over China (2000-2017) by merging satellite cloud and aerosol data with ground-based sunshine duration data",
    "ds_abstract": "<p>&emsp;&emsp;地表入射太阳辐射（Rs）是地表辐射预算的关键组成部分。它驱动全球气候系统，影响全球能量平衡以及水文和碳循环。通过气象观测、卫星检索和再分析来探测地表太阳辐射（Rs）的变化已经取得了很大进展。然而，每种估算方法都有其优缺点。已有研究表明，日照时数（SunDu）推导的太阳辐射数据可以提供可靠的中国地区长期太阳辐射变化；然而，这些数据在空间上是不连续的。因此，我们将 SunDu 导出的 Rs 数据与卫星导出的云分（MODAL2 M CLD）和 CERES SYN 气溶胶光学深度（AOD）数据合并，通过地理加权回归方法生成 Rs 数据。该数据集提供了中国 2000 年至 2017 年的月度 Rs 数据，空间分辨率为 0.1°。",
    "ds_source": "<p>&emsp;&emsp;2000 年至 2017 年的 Rs 直接观测数据来自中国气象局中国气象数据服务中心（CMDC，http://data.cma.cn/data/index.html）\n<p>&emsp;&emsp;",
    "ds_process_way": "<p>&emsp;&emsp;将 SunDu 导出的 Rs 数据与卫星导出的云分（MODAL2 M CLD）和 CERES SYN 气溶胶光学深度（AOD）数据合并，通过地理加权回归方法生成 Rs 数据。",
    "ds_quality": "<p>&emsp;&emsp;数据质量良好。",
    "ds_acq_start_time": "2000-01-01 00:00:00",
    "ds_acq_end_time": "2017-12-31 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": "login-access",
    "ds_total_size": 237223552,
    "ds_files_count": 2,
    "ds_format": "",
    "ds_space_res": "0.1度",
    "ds_time_res": "月",
    "ds_coordinate": "无",
    "ds_projection": "",
    "ds_thumbnail": "ac27e876-72f4-419a-9655-3763d1ef9250.png",
    "ds_thumb_from": 0,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "99c0a56f-14cb-4cfc-a9a1-bb4b8d16a658",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [
        "170.45"
    ],
    "quality_level": 3,
    "publish_time": "2023-11-27 16:42:27",
    "last_updated": "2025-05-29 11:22:01",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.NCDC.PANGAEA.DB4113.2023",
    "i18n": {
        "en": {
            "title": "Monthly surface solar radiation data over China (2000-2017) by merging satellite cloud and aerosol data with ground-based sunshine duration data",
            "ds_format": "",
            "ds_source": "<p>&emsp; &emsp; The direct observation data of Rs from 2000 to 2017 were obtained from the China Meteorological Data Service Center (CMDC) of the China Meteorological Administration, http://data.cma.cn/data/index.html ）\n<p>&emsp; &emsp;",
            "ds_quality": "<p>&emsp; &emsp; The data quality is good.",
            "ds_ref_way": "",
            "ds_abstract": "<p>    The surface incident solar radiation (Rs) is a key component of the surface radiation budget. It drives the global climate system, affects global energy balance, hydrology, and carbon cycling. Significant progress has been made in detecting changes in surface solar radiation (Rs) through meteorological observations, satellite retrieval, and reanalysis. However, each estimation method has its advantages and disadvantages. Previous studies have shown that solar radiation data derived from sunshine hours (SunDu) can provide reliable long-term solar radiation changes in China; However, these data are spatially discontinuous. Therefore, we merged the Rs data exported by SunDu with satellite exported cloud fraction (MODAL2 M CLD) and CERES SYN aerosol optical depth (AOD) data, and generated Rs data through geographically weighted regression method. This dataset provides monthly Rs data for China from 2000 to 2017, with a spatial resolution of 0.1 °.</p>",
            "ds_time_res": "月",
            "ds_acq_place": "China",
            "ds_space_res": "0.1度",
            "ds_projection": "",
            "ds_process_way": "<p>&emsp; &emsp; Merge the Rs data exported by SunDu with satellite exported cloud fraction (MODAL2 M CLD) and CERES SYN aerosol optical depth (AOD) data, and generate Rs data through geographically weighted regression method.",
            "ds_ref_instruction": ""
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "license_type": "https://creativecommons.org/licenses/by/4.0/",
    "doi_reg_from": "reg_outside",
    "cstr_reg_from": "reg_outside",
    "doi_not_reg_reason": null,
    "cstr_not_reg_reason": null,
    "is_paper_in_submitting": false,
    "ds_topic_tags": [
        "中国",
        "短波辐射",
        "地表太阳辐射"
    ],
    "ds_subject_tags": [
        "地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "中国"
    ],
    "ds_time_tags": [
        2000,
        2001,
        2002,
        2003,
        2004,
        2005,
        2006,
        2007,
        2008,
        2009,
        2010,
        2011,
        2012,
        2013,
        2014,
        2015,
        2016,
        2017
    ],
    "ds_contributors": [
        {
            "true_name": "王开存",
            "email": "kcwang@bnu.edu.cn",
            "work_for": "北京大学",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "王开存",
            "email": "kcwang@bnu.edu.cn",
            "work_for": "北京大学",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "王开存",
            "email": "kcwang@bnu.edu.cn",
            "work_for": "北京大学",
            "country": "中国"
        }
    ],
    "category": "遥感及产品"
}