积雪是重要的水资源。本数据以高空间分辨率月尺度降水气温数据为输入，利用度日因子模型计算积融水量，以降雪、雪深、积雪范围和雪水当量等验证模型输出，获取了中国高空间分辨率（0.5′，约1km）1951-2020年月尺度积雪融水数据。数据集包含的地理空间范围是中国主要陆地，不含南海岛礁等区域。该数据集以nc文件格式存储，文件命名方式为snowmelt_year，year表示年份。
", "ds_source": "1951-2017年降水气温数据来自于https://zenodo.org/record/3114194和https://zenodo.org/record/3185722； 2018-2020年降水气温数据来自于国家地球系统科学数据中心http://www.geodata.cn/。
", "ds_process_way": "1）利用雨雪分离系数获取降雪；\n
2）构建月尺度融雪度日因子模型。\n
具体过程见参考文献。
", "ds_quality": "利用模型输出中间变量降雪、雪深、积雪范围和雪水当量验证。457个站点中，315个站点降雪验证R2 > 0.4；264个站点中，108个站点雪深验证R2 > 0.2；全国及三大稳定积雪区（北疆，东北和青藏高原）的积雪范围验证的R2 分别为0.93，0.81，0.93和0.90；雪水当量验证的R2 分别为0.62，0.67，0.76和0.25。
", "ds_acq_start_time": "1951-01-31 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 136.10833333333332, "ds_acq_lat_south": 16.254444444444445, "ds_acq_lon_west": 72.25, "ds_acq_lat_north": 55.32944444444445, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 3787278050, "ds_files_count": 71, "ds_format": "nc", "ds_space_res": "0.5′", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "Mercator", "ds_thumbnail": "219951d0-5be0-4384-8454-cf6a6b8eaa5f.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.NIEER.db2387.2022", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2022-08-15 15:13:44", "last_updated": "2025-04-29 14:58:53", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.db2387.2022", "i18n": { "en": { "title": "Monthly snowmelt dataset in China during 1951-2020", "ds_format": "nc", "ds_source": "The precipitation and temperature data from 1951 to 2017 were obtained from https://zenodo.org/record/3114194 and https://zenodo.org/record/3185722 ; Precipitation and temperature data from 2018 to 2020 from the National Earth System Science Data Center http://www.geodata.cn/
", "ds_quality": "Use the model to output intermediate variables such as snowfall, snow depth, snow cover range, and snow water equivalent for validation. Out of 457 sites, 315 sites have snow verification R2> 0.4; Out of 264 sites, 108 sites have snow depth verification R2> 0.2; The R2 values for snow cover verification in the national and three stable snow cover areas (North Xinjiang, Northeast China, and Qinghai Tibet Plateau) are 0.93, 0.81, 0.93, and 0.90, respectively; The R2 values for snow water equivalent validation are 0.62, 0.67, 0.76, and 0.25, respectively
", "ds_ref_way": "", "ds_abstract": "Snow is an important water resource. This data is based on high spatial resolution monthly scale precipitation and temperature data as input. The degree day factor model is used to calculate the amount of snow melting water. The model output is validated by snowfall, snow depth, snow coverage, and snow water equivalent. High spatial resolution (0.5 ', approximately 1km) monthly scale snow melting water data from 1951 to 2020 in China was obtained. The geographic spatial range included in the dataset is the main land of China, excluding areas such as islands and reefs in the South China Sea. This dataset is stored in an NC file format, with the file naming method being snowmelt_ Year, year represents the year
", "ds_time_res": "月", "ds_acq_place": "China", "ds_space_res": "0.5′", "ds_projection": "Mercator", "ds_process_way": "1) Obtain snowfall using the rain snow separation coefficient;\n
2) Construct a monthly scale snowmelt day factor model.\n
The specific process can be found in the references.
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "https://creativecommons.org/licenses/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": [ "积雪融水", "度日因子模型", "验证模型" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国陆域" ], "ds_time_tags": [ 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 ], "ds_contributors": [ { "true_name": "阳勇", "email": "yy177@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "刘国华", "email": "lgh1990@lzb.ac.cn", "work_for": "衡阳师范学院地理与旅游学院", "country": "中国" }, { "true_name": "刘章文", "email": "zwliu@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "王希强", "email": "wangxq@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": "阳勇", "email": "yy177@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "刘国华", "email": "lgh1990@lzb.ac.cn", "work_for": "衡阳师范学院地理与旅游学院", "country": "中国" }, { "true_name": "刘章文", "email": "zwliu@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "王希强", "email": "wangxq@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": "阳勇", "email": "yy177@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" }