本数据集基于MSWEP V2.1和地面站点观测降水数据，通过考虑分类-回归-校正的三阶段多源降水信息的融合框架，并具体采用地理加权逻辑回归（GWLR）与地理加权回归（GWR）模型开展汉江流域日降水融合，得到了2010-2016年时间分辨率为日，空间分辨率为0.1°×0.1°，汉江流域的降水数据，量化了较遥感反演降水数据及降水空间插值数据的统计精度增益，精细刻画了复杂流域地形变化对降水空间格局的影响，构建了长系列高精度数据集。
", "ds_source": "数据为汉江流域2010-2016年时间分辨率为日，空间分辨率为0.1°×0.1°的降水数据。", "ds_process_way": "
地理加权逻辑回归（GWLR）与地理加权回归（GWR）
", "ds_quality": "数据比较准确，达到精度要求。
", "ds_acq_start_time": "2010-01-01 00:00:00", "ds_acq_end_time": "2016-12-31 00:00:00", "ds_acq_place": "汉江流域", "ds_acq_lon_east": 106.25, "ds_acq_lat_south": 30.17, "ds_acq_lon_west": 114.33, "ds_acq_lat_north": 34.330000000000005, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 42209932, "ds_files_count": 0, "ds_format": "*.mat", "ds_space_res": "0.1°", "ds_time_res": "日", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "daa4e8ab-de33-4113-9373-f82cd86fd95a.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": "", "organization_id": "44547705-9513-4685-a641-661bdf406520", "ds_serv_man": "", "ds_serv_phone": "", "ds_serv_mail": "", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 0, "publish_time": "2026-07-13 17:55:50", "last_updated": "2026-07-13 17:55:50", "protected": false, "protected_to": "2027-01-01 00:00:00", "lang": "zh", "cstr": "", "i18n": { "en": { "title": "Daily Precipitation Dataset for the Hanjiang River Basin from 2010 to 2016 Based on Classification, Regression, and Correction with Multi-source Fusion", "ds_format": "*.mat", "ds_source": "The data is precipitation data in the Hanjiang River Basin from 2010 to 2016 with a temporal resolution of day and a spatial resolution of 0.1°×0.1°.", "ds_quality": "
The data is relatively accurate and meets the accuracy requirements.
", "ds_ref_way": "", "ds_abstract": "This dataset is based on MSWEP V2.1 and observed precipitation data from ground stations. Through a three-stage fusion framework of multi-source precipitation information that considers classification, regression and correction, and specifically uses geographically weighted logistic regression (GWLR) and geographically weighted regression (GWR) models to carry out daily precipitation fusion in the Hanjiang River Basin. The precipitation data of the Hanjiang River Basin from 2010 to 2016 is obtained, with a temporal resolution of day and a spatial resolution of 0.1°×0.1°. The statistical accuracy gain of remote sensing retrieved precipitation data and precipitation spatial interpolation data is quantified, the impact of terrain changes in complex river basins on the spatial pattern of precipitation is carefully described, and a long series of high-precision data sets are constructed.
", "ds_time_res": "", "ds_acq_place": "hanjiang River Basin", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Geographically weighted logistic regression (GWLR) and Geographically weighted regression (GWR)
", "ds_ref_instruction": "None" } }, "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, "ds_topic_tags": [ "降水" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "汉江流域" ], "ds_time_tags": [ 2010, 2011, 2012, 2013, 2014, 2015, 2016 ], "ds_contributors": [ { "true_name": "李伶杰", "email": "ljli@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "李伶杰", "email": "ljli@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "李伶杰", "email": "ljli@nhri.cn", "work_for": "南京水利科学研究院", "country": "中国" } ], "category": "其他" }