ChinaMet 一个中国高分辨率（1km）和长时间序列（1980-2024）全要素气象驱动产品，通过融合多源遥感数据、再分析资料以及超过 2000 个气象站的观测数据研制而成。ChinaMet 包括 8个气象要素，分别为：降水量（pre）、近地面2米平均气温（tmpmean）、最高气温（tmpmax）、最低气温（tmpmin）、 10米风速（wind）、相对湿度（rhu）、地面气压（pres）和潜在蒸散发（pet）。数据的时间覆盖范围为1980-2024年，空间分辨率分别为0.1° 和 0.01° ，时间分辨率为年/月/日。每个文件的命名方式为\nChinaMet_%S_%V_%T.nc\"，\"%S\"代表数据空间分辨率，\"%V\"代表变量名称，\"%T\"代表时间，例如1982_01_01。
", "ds_source": "气象站点观测数据来自于国家气象数据中心（CMA）；融合的遥感降水产品主要包括IMERG、SM2RAIN-ASCAT 和 CMORPH；再分析资料使用欧洲中期天气预报中心(ECWMF)最新发布的ERA5-Land产品；其它遥感产品包括AVHRR NDVI数据，MODIS的地表温度数据。
", "ds_process_way": "基于知识引导的机器学习方法，并结合气候场辅助空间降尺度技术研制而成。潜在蒸散发 (PET) 分为两个版本，即 petHG 和 petPM，分别采用 Hargreaves 方法和 Penman-Monteith 方法估算而得。
", "ds_quality": "数据的时空分辨率及精度优于同类产品。
", "ds_acq_start_time": "1980-01-01 00:00:00", "ds_acq_end_time": "2024-12-31 00:00:00", "ds_acq_place": "中国", "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": "login-access", "ds_total_size": 3839836841658, "ds_files_count": 306425, "ds_format": "nc4", "ds_space_res": null, "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "21691d03-bef2-4800-924e-5614e7268b87.jpg", "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": "lihongxing@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 3, "publish_time": "2025-01-06 16:53:09", "last_updated": "2025-09-02 09:20:13", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB6722.2025", "i18n": { "en": { "title": "ChinaMet: A High-resolution Multi-element Meteorological Driving Dataset for China via Multi-source Data Fusion", "ds_format": "nc4", "ds_source": "Meteorological station observations were sourced from the China Meteorological Administration (CMA). Fused remote sensing precipitation products include IMERG, SM2RAIN-ASCAT, and CMORPH. Reanalysis data utilized the ERA5-Land product from the European Centre for Medium-Range Weather Forecasts (ECMWF). Additional remote sensing inputs include AVHRR NDVI and MODIS land surface temperature data.
", "ds_quality": "The temporal and spatial resolution and accuracy of the data are better than those of similar products.
", "ds_ref_way": "", "ds_abstract": "ChinaMet is a high-resolution (1 km) and long-term (1980–2024) meteorological driving dataset for China, developed by fusing multi-source remote sensing data, reanalysis products, and observational data from over 2,000 meteorological stations. The dataset includes eight meteorological variables: precipitation (pre), mean 2-meter air temperature (tmpmean), maximum temperature (tmpmax), minimum temperature (tmpmin), 10-meter wind speed (wind), relative humidity (rhu), surface pressure (pres), and potential evapotranspiration (pet). The data span 1980–2024 with spatial resolutions of 0.1° and 0.01°, and temporal resolutions of annual/monthly/daily. Each file is named as\nChinaMet_%S_%V_%T.nc”, ‘%S’ represents the data space resolution, ‘%V’ represents the variable name, and ‘%T’ represents the time, e.g., 1982_01_01.
", "ds_time_res": "年", "ds_acq_place": "China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "The dataset was developed using knowledge-guided machine learning combined with climate-field-assisted spatial downscaling techniques. Potential evapotranspiration (PET) is provided in two versions: petHG (estimated via the Hargreaves method) and petPM (derived using the Penman-Monteith method).
", "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": [ "相对湿度", "地面气压", "蒸发量", "多源数据融合" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 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, 2024 ], "ds_contributors": [ { "true_name": "张凌", "email": "zhanglingky@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": "胡英屹", "email": "huyingyi@nieer.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": "赵彦博", "email": "eanbo@lab.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": "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": "张凌", "email": "zhanglingky@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": "张凌", "email": "zhanglingky@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": "气象" }