{
    "created": "2021-11-15 09:07:20",
    "updated": "2026-04-28 00:27:05",
    "id": "b222a6a9-cf06-405c-8b41-4849ad885deb",
    "version": 2,
    "ds_topic": null,
    "title_cn": "古尔班通古特荒漠区未来各季节可降水转化率数据集（2021-2080年）",
    "title_en": "Data set of precipitation conversion rate in future seasons in Gurbantunggut Desert Area (2021-2080)",
    "ds_abstract": "<p>&emsp;&emsp;基于空中水资源基本理论，将大气中由特殊的边界层形成的次生环流锁定且具备发生相变转化为云和降水潜力的水物质定义为有效水汽，然后基于水汽辐合区开发有效水汽识别算法，并对区域可开发空中水资源（即有效水汽）的总量和空中水资源降水潜力进行评估。",
    "ds_source": "<p>&emsp;&emsp;源数据为第五次耦合模式比较计划（CMIP5）中的新一代典型浓度排放路径情景（RCP4.5）的月值格点数据，下载地址为：https://esgf-node.llnl.gov/search/cmip5/",
    "ds_process_way": "<p>&emsp;&emsp;（1）基于CMIP5比湿数据，将空间分辨率统一为0.75°×0.75°，利用整层积分公式计算得到可降水量矩阵。 \n<p>&emsp;&emsp;（2）基于CMIP5降水月值格点数据，将空间分辨率统一为0.75°×0.75°，计算各格点中降水与可降水量得比值矩阵，即可降水转化率矩阵，采用python统计分析库裁取研究区域内数据点，做区域平均得可降水转化率数据。\n<p>&emsp;&emsp;（3）最后进行季平均及年平均，得到区域内各级季节数据。",
    "ds_quality": "<p>&emsp;&emsp;严格按照相关方法和标准规范进行统计分析，数据质量良好。",
    "ds_acq_start_time": "2017-07-01 00:00:00",
    "ds_acq_end_time": "2020-12-31 00:00:00",
    "ds_acq_place": "古尔班通古特荒漠区",
    "ds_acq_lon_east": 91.55527777777777,
    "ds_acq_lat_south": 44.02055555555555,
    "ds_acq_lon_west": 85.19638888888889,
    "ds_acq_lat_north": 47.12638888888889,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "apply-access",
    "ds_total_size": 13824,
    "ds_files_count": 2,
    "ds_format": "excel",
    "ds_space_res": null,
    "ds_time_res": "年",
    "ds_coordinate": "无",
    "ds_projection": "",
    "ds_thumbnail": "b222a6a9-cf06-405c-8b41-4849ad885deb.jpg",
    "ds_thumb_from": 0,
    "ds_ref_way": "钟德钰，古尔班通古特荒漠区未来各季节可降水转化率数据集（2021-2080年），国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2021，doi：10.12072/ncdc.XBSAQ.db2264.2022",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "fba361ca-30e1-4a60-a262-c183d8cd6ab3",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "10.12072/ncdc.XBSAQ.db2264.2022",
    "subject_codes": [
        "170.45"
    ],
    "quality_level": 3,
    "publish_time": "2022-06-30 09:32:17",
    "last_updated": "2022-06-30 14:49:36",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.XBSAQ.db2264.2022",
    "i18n": {
        "en": {
            "title": "Data set of precipitation conversion rate in future seasons in Gurbantunggut Desert Area (2021-2080)",
            "ds_format": "",
            "ds_source": "<pre><code>\n</code></pre>\n<p>&emsp;& emsp; The source data is the monthly grid data of the new generation typical concentration emission path scenario (rcp4.5) in the fifth coupled mode comparison plan (cmip5). The download address is: https://esgf-node.llnl.gov/search/cmip5/",
            "ds_quality": "<p>&emsp; Statistical analysis was carried out in strict accordance with relevant methods, standards and specifications, and the data quality was good.",
            "ds_ref_way": "",
            "ds_abstract": "<pre><code>\n</code></pre>\n<p>  Based on the basic theory of air water resources, the water substances in the atmosphere locked by the secondary circulation formed by the special boundary layer and with the potential of phase transformation into clouds and precipitation are defined as effective water vapor, and then the effective water vapor identification algorithm is developed based on the water vapor convergence area, and the regional exploitable air water resources (i.e. effective water vapor) The total amount and air water resources precipitation potential are evaluated.</p>",
            "ds_time_res": "年",
            "ds_acq_place": "Gurbantunggut Desert Area",
            "ds_space_res": "",
            "ds_projection": "",
            "ds_process_way": "<pre><code>\n</code></pre>\n<p>&emsp;& emsp; (1) Based on cmip5 specific humidity data, the spatial resolution is unified to 0.75 ° × 0.75 °, the precipitable water matrix is calculated by using the integral formula of the whole layer.\n<p>&emsp;& emsp; (2) Based on cmip5 monthly precipitation grid data, the spatial resolution is unified to 0.75 ° × 0.75 °, calculate the ratio matrix of precipitation and available precipitation in each grid point, that is, the precipitation conversion rate matrix. Use Python statistical analysis library to cut the data points in the study area and make the regional average to obtain the available precipitation conversion rate data.\n<p>&emsp;& emsp; (3) Finally, the seasonal average and annual average are carried out to obtain the seasonal data at all levels in the region.",
            "ds_ref_instruction": "                    "
        }
    },
    "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,
    "ds_topic_tags": [
        "古尔班通古特荒漠区",
        "可降水转化率",
        "未来情景（2021年-2080年）"
    ],
    "ds_subject_tags": [
        "地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "古尔班通古特荒漠区"
    ],
    "ds_time_tags": [
        2021,
        2080
    ],
    "ds_contributors": [
        {
            "true_name": "钟德钰",
            "email": "zhongdy@tsinghua.edu.cn",
            "work_for": "清华大学水利水电工程系",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "田颖琳",
            "email": "tianyl18@mails.tsinghua.edu.cn",
            "work_for": "清华大学",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "钟德钰",
            "email": "zhongdy@tsinghua.edu.cn",
            "work_for": "清华大学水利水电工程系",
            "country": "中国"
        }
    ],
    "category": "水文"
}