{
    "created": "2020-11-20 03:39:37",
    "updated": "2026-05-03 13:24:14",
    "id": "819a29a7-cd9e-41d8-83fd-6e72845b82d8",
    "version": 4,
    "ds_topic": null,
    "title_cn": "2001-2010年北半球雪深数据集",
    "title_en": "Data set of snow depth in Northern Hemisphere from 2001 to 2010",
    "ds_abstract": "<p>本数据集为2001-2010年间10年的北半球逐日雪深数据，数据覆盖范围0-86°N，180°W-180°E，该数据集结合积雪过程模型和积雪微波辐射传输模型，并吸收地面观测站点资料对雪深进行提取，引入森林覆盖率因子降低森林对雪深反演的影响，利用集合卡尔曼滤波方法综合卫星观测的微波亮度温度和模拟的亮度温度对积雪参数进行优化；在森林地区通过森林覆盖率降低森林的影响，获得北半球雪深数据集。<p>",
    "ds_source": "<p>本数据集用到的原始数据为星载被动微波亮度温度数据AMSR-E EASE-Grid，数据从美国雪冰数据中心下载。</p>",
    "ds_process_way": "<p>(1)积雪过程模型和积雪微波辐射传输模型、北半球站点积雪观测数据实时更新积雪状态变量、卡尔曼滤波方法综合卫星观测的微波亮度温度和模拟的亮度温度对积雪参数进行优化和森林地区通过森林覆盖率降低森林的影响。</p>",
    "ds_quality": "<p>与站点观测雪深（雪深大于5cm）相比，雪深较深的月份相对偏差较小，而雪深较浅的月份相对偏差较大。对于雪深较深的1-4月，平均雪深月30cm，其相对偏差为-21%，对于雪深较浅的5-6月，10-12月，相对偏差为-63.2%。</p>",
    "ds_acq_start_time": "2001-01-01 00:00:00",
    "ds_acq_end_time": "2010-01-01 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": 86.0,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "login-access",
    "ds_total_size": 383249886,
    "ds_files_count": 3,
    "ds_format": "TXT",
    "ds_space_res": null,
    "ds_time_res": "日",
    "ds_coordinate": "无",
    "ds_projection": "经纬度",
    "ds_thumbnail": "819a29a7-cd9e-41d8-83fd-6e72845b82d8.jpg",
    "ds_thumb_from": 2,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "由于本数据集测定时间不尽一致，指标繁杂，如需要详细原始数据者，请联系数据管理者。\r\n联系信息：联系人姓名：车涛 Email:chetao@lzb.ac.cn  Tel:0931-4967966",
    "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": [
        "170.4510"
    ],
    "quality_level": 3,
    "publish_time": "2020-12-03 08:51:52",
    "last_updated": "2025-05-29 16:23:44",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.CCI.2020.90",
    "i18n": {
        "en": {
            "title": "Data set of snow depth in Northern Hemisphere from 2001 to 2010",
            "ds_format": "TXT",
            "ds_source": "<p>The original data used in this data set is AMSR-E ease grid, which is downloaded from the snow and Ice Data Center of the United States. </p>",
            "ds_quality": "<p>Compared with the observed snow depth (the snow depth is more than 5cm), the relative deviation of the month with deeper snow depth is smaller, while the relative deviation of the month with shallow snow depth is larger. For the deep snow months from January to April, the average snow depth is 30cm, the relative deviation is - 21%; for the shallow snow depth from May to June and October to December, the relative deviation is - 63.2%. </p>",
            "ds_ref_way": "",
            "ds_abstract": "<p>This data set is the daily snow depth data of the Northern Hemisphere from 2001 to 2010, covering the range of 0-86 ° n, 180 ° w-180 ° e. the data set combines the snow process model and snow microwave radiation transmission model, absorbs the ground observation station data to extract the snow depth, introduces the forest coverage factor to reduce the impact of forest on snow depth retrieval, and uses Ensemble Kalman filter method to synthesize The results show that the parameters of snow cover are optimized by microwave brightness temperature and simulated brightness temperature; the influence of forest is reduced by forest coverage in forest area, and the snow depth data set in northern hemisphere is obtained with spatial resolution of 0.250 * 0.250. </p>",
            "ds_time_res": "日",
            "ds_acq_place": "Northern Hemisphere",
            "ds_space_res": "",
            "ds_projection": "latitude and longitude",
            "ds_process_way": "<p>(1) Snow process model and snow microwave radiation transmission model, real-time update of snow state variables from snow observation data of northern hemisphere stations, optimization of snow parameters by integrating microwave brightness temperature observed by satellite and simulated brightness temperature by Kalman filter method, and reducing forest impact through forest coverage rate in forest areas. </p>",
            "ds_ref_instruction": "Because the measurement time of this data set is not consistent and the indicators are complex, if you need detailed original data, please contact the data manager.\r\nContact information: Contact Name: Che Tao Email:chetao@lzb.ac.cn  Tel :0931-4967966"
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "license_type": "CC 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": [
        "雪深，经纬度 ，时间"
    ],
    "ds_subject_tags": [
        "自然地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "北半球"
    ],
    "ds_time_tags": [
        2001,
        2002,
        2003,
        2004,
        2005,
        2006,
        2007,
        2008,
        2009,
        2010
    ],
    "ds_contributors": [
        {
            "true_name": "车涛",
            "email": "chetao@lzb.ac.cn",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "车涛",
            "email": "chetao@lzb.ac.cn",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "车涛",
            "email": "chetao@lzb.ac.cn",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        }
    ],
    "category": "积雪"
}