积雪密度是表征积雪特征的重要参数，也是将积雪深度转化为雪水当量的重要指标，在山区雪水资源估算、融雪洪水等水资源管理、自然灾害预报、气候研究等中发挥着重要作用。该数据将为青藏高原水资源评估和水文过程模拟提供数据支持。
", "ds_source": "以1960–2020年青藏高原132个逐日国家气象站资料、中国区域地面气象要素驱动数据集、卫星融合雪深数据集为主要数据源，分不同地表类型比较几种机器学习模型在积雪密度模拟中的性能，选取最优模型，综合地面、卫星和再分析资料，制作了青藏高原逐月积雪密度数据集。
", "ds_process_way": "对青藏高原132个国家级气象台的多年平均积雪密度数据进行精度检查发现，平均均方根误差为0.019 g/cm3，平均相对误差为11.88%，表明数据具有较高的准确率。
", "ds_quality": "数据质量良好。
", "ds_acq_start_time": "1960-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "青藏高原", "ds_acq_lon_east": 105.0, "ds_acq_lat_south": 40.0, "ds_acq_lon_west": 73.0, "ds_acq_lat_north": 25.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 4017055, "ds_files_count": 2, "ds_format": "*.tif", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "af7bbd77-93ac-4d77-966d-4104d31d9fee.png", "ds_thumb_from": 2, "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": "", "subject_codes": [ "170" ], "quality_level": 3, "publish_time": "2024-06-29 16:58:03", "last_updated": "2025-07-02 10:48:15", "protected": false, "protected_to": null, "lang": "zh", "cstr": "31253.11.sciencedb.j00001.00823", "i18n": { "en": { "title": "A dataset of monthly multi-year average snow density grids on the Tibetan Plateau", "ds_format": "", "ds_source": "Using data from 132 national level meteorological stations on the Qinghai Tibet Plateau from 1960 to 2020, the Chinese regional surface meteorological element driven dataset, and the satellite fusion snow depth dataset as the main data sources, we compared the performance of several machine learning models in snow density simulation under different surface types and selected the optimal model. We integrated ground, satellite, and reanalysis data to generate a monthly snow density dataset for the Qinghai Tibet Plateau.", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
Snow density is an important parameter that characterizes the characteristics of snow accumulation and is also an important indicator for converting snow depth into snow water equivalent. It plays an important role in estimating snow water resources in mountainous areas, managing water resources such as snowmelt floods, predicting natural disasters, and conducting climate research. This data will provide data support for water resource assessment and hydrological process simulation on the Qinghai Tibet Plateau.
", "ds_time_res": "", "ds_acq_place": "Qinghai-Tibet Plateau", "ds_space_res": "", "ds_projection": "", "ds_process_way": "An accuracy check of the multi-year average snow density data from 132 national meteorological stations on the Qinghai Tibet Plateau revealed an average root mean square error of 0.019 g/cm3and an average relative error of 11.88%, indicating high accuracy of the data.", "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": [ "青藏高原", "积雪密度", "气象站", "机器学习" ], "ds_subject_tags": [ "地球科学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原" ], "ds_time_tags": [ 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": "曹晓云", "email": "xiaoyun_cao@126.com", "work_for": "青海省气象科学研究所", "country": "中国" }, { "true_name": "史飞飞", "email": "shifeifei1203@126.com", "work_for": "青海省气象科学研究所", "country": "中国" }, { "true_name": "刘致远", "email": "liuzhiyuangis@163.com", "work_for": "青海省气象科学研究所", "country": "中国" }, { "true_name": "张娟", "email": "7845944@qq.com", "work_for": "青海省气象科学研究所", "country": "中国" }, { "true_name": "李弘毅", "email": "lihongyi@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": "肖建设", "email": "xiaojianshe@126.com", "work_for": "青海省气象科学研究所", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "曹晓云", "email": "xiaoyun_cao@126.com", "work_for": "青海省气象科学研究所", "country": "中国" }, { "true_name": "肖建设", "email": "xiaojianshe@126.com", "work_for": "青海省气象科学研究所", "country": "中国" } ], "ds_managers": [ { "true_name": "曹晓云", "email": "xiaoyun_cao@126.com", "work_for": "青海省气象科学研究所", "country": "中国" } ], "category": "水文" }