{
    "created": "2026-07-21 12:56:14",
    "updated": "2026-07-22 21:52:32",
    "id": "5c3e8923-c506-4130-bb4f-9d46c81baff6",
    "version": 4,
    "ds_topic": null,
    "title_cn": "塔吉克斯坦1950-2023年最大雪水当量空间分布数据",
    "title_en": "",
    "ds_abstract": "<p>塔吉克斯坦年最大雪水当量（单位：m），变量名为“sd”，变量读取后为三维矩阵71（纬度）<em>101（经度）</em>74（年份）。</p>",
    "ds_source": "<p>本研究基于 ERA5-Land 再分析数据集的日尺度雪水当量（SWE）构建年最大雪水当量（SWEmax）。</p>",
    "ds_process_way": "<p>首先下载 1950–2023 年 ERA5-Land 日 SWE 数据，并裁剪至 35°–42°N、66°–76°E 的研究区域，空间分辨率为 0.1°（约 9 km）。随后，对每个格点的日 SWE 时间序列，在每个自然年内取最大值，得到对应年份的 SWEmax。最终生成 1950–2023 年、年尺度、0.1° 分辨率的 SWEmax 数据集。</p>",
    "ds_quality": "",
    "ds_acq_start_time": null,
    "ds_acq_end_time": null,
    "ds_acq_place": "",
    "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": "open-access",
    "ds_total_size": 0,
    "ds_files_count": 0,
    "ds_format": "nc格式",
    "ds_space_res": "0.1度",
    "ds_time_res": "年",
    "ds_coordinate": "WGS84",
    "ds_projection": "WGS84",
    "ds_thumbnail": "5c3e8923-c506-4130-bb4f-9d46c81baff6.png",
    "ds_thumb_from": 0,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6",
    "doi_value": "",
    "subject_codes": [
        "170.15"
    ],
    "quality_level": 1,
    "publish_time": "2026-07-21 16:32:17",
    "first_publish_time": null,
    "last_updated": "2026-07-21 16:37:03",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": null,
    "license": null,
    "extra": null,
    "files_shape": null,
    "features": null,
    "data_level": 0,
    "i18n": {
        "en": {
            "title": "",
            "ds_abstract": "Tajikistan's annual maximum snow-water equivalent (unit: m), the variable is named \"sd\", and the variable is read as a three-dimensional matrix 71 (latitude)*101 (longitude)*74 (year).",
            "ds_source": "This study constructs the annual maximum snow water equivalent (SWEmax) based on the daily scale snow water equivalent (SWE) from the ERA5-Land reanalysis dataset.",
            "ds_process_way": "First, we download the ERA5-Land day SWE data from 1950 to 2023 and clip it to the study area of 35°-42°N and 66°-76°E with a spatial resolution of 0.1° (approximately 9 km). Subsequently, the daily SWE time series of each grid point is taken to the maximum value in each natural year to obtain the SWEmax for the corresponding year. The SWEmax dataset with annual scale and 0.1° resolution from 1950 to 2023 was finally generated.",
            "ds_quality": "",
            "ds_acq_place": "",
            "ds_ref_instruction": "",
            "ds_ref_way": "",
            "ds_format": "NC format",
            "ds_projection": "",
            "ds_space_res": "",
            "ds_time_res": ""
        }
    },
    "license_type": null,
    "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": [
        "雪水当量"
    ],
    "ds_subject_tags": [
        "大气科学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "塔吉克斯坦"
    ],
    "ds_time_tags": [
        1950,
        1951,
        1952,
        1953,
        1954,
        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,
        2019,
        2020,
        2021,
        2022,
        2023
    ],
    "ds_contributors": [
        "李玉朋"
    ],
    "ds_meta_authors": [
        "李玉朋"
    ],
    "ds_managers": [
        "李玉朋"
    ],
    "category": "气象"
}