本数据集为中国区域 0.1° 网格产品，包含多年平均与逐年降雨侵蚀力（R 因子），基于 2015-2023 年全国 57740 个气象站经过质量控制的逐小时降水观测构建。数据集包含经偏差校正（校正系数 ×1.871）的 2015-2023 多年平均年降雨侵蚀力，以及 2015-2023 逐年未经校正的降雨侵蚀力，数据格式为 GeoTIFF，坐标系为 WGS84（EPSG:4326）。该数据集可支撑土壤侵蚀评估（如 RUSLE 模型）、水文模拟、土地退化研究与气候变化影响分析。\n
本数据集对应曾等人（2026）发表的论文《中国降雨侵蚀力（2015-2023）：基于全国逐小时气象站观测记录构建的全新年值数据集》。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": "2015-01-01 00:00:00", "ds_acq_end_time": "2023-12-31 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": "open-access", "ds_total_size": 586905, "ds_files_count": 5, "ds_format": "*tif", "ds_space_res": "0.1°", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "16770a84-2783-4f98-a164-bb0eae5a4e53.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": null, "ds_serv_phone": null, "ds_serv_mail": null, "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 0, "publish_time": "2026-10-20 09:28:12", "last_updated": "2026-10-20 09:30:02", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.db7850.2026", "i18n": { "en": { "title": "China rainfall erosivity (2015-2023): A new annual dataset inferred from national hourly meteorological station records", "ds_format": "*tif", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
This dataset provides a 0.1° gridded product of multi-year mean and annual rainfall erosivity (R-factor) for China, derived from quality-controlled hourly precipitation observations at 57,740 meteorological stations over the period 2015-2023. It includes bias-corrected (×1.871) multi-year mean annual rainfall erosivity (2015-2023) and annual rainfall erosivity for each year from 2015 to 2023 (uncorrected) in GeoTIFF format (WGS84, EPSG:4326). This dataset can support soil erosion assessment (e.g., RUSLE), hydrological modeling, land degradation studies, and climate change impact analysis. \r\n
This dataset is asscoated to the \"China rainfall erosivity (2015-2023): A new annual dataset inferred from national hourly meteorological station records\" by Zeng et al. (2026).", "ds_time_res": "year", "ds_acq_place": "China", "ds_space_res": "0.1°", "ds_projection": "", "ds_process_way": "", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 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, "belong_to_nieer": false, "allow_update_data": false, "created_from": "admin", "ds_topic_tags": [ "降雨侵蚀力", "土壤侵蚀", "降水" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 ], "ds_contributors": [ { "true_name": "陈颂超", "email": "chensongchao@zju.edu.cn", "work_for": "浙江大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "陈颂超", "email": "chensongchao@zju.edu.cn", "work_for": "浙江大学", "country": "中国" } ], "ds_managers": [ { "true_name": "陈颂超", "email": "chensongchao@zju.edu.cn", "work_for": "浙江大学", "country": "中国" } ], "category": "气象" }