优质且时空分辨率精细的降水估算数据，对于解析全球及区域水循环、碳循环与能量循环过程具有重要意义。卫星降水产品能够精细捕捉降水的空间分布特征与时间变化规律，在地面观测站点稀疏的区域尤为实用。但卫星降水数据属于间接反演结果，普遍存在区域性、季节性系统偏差与随机误差。\n
全球降水观测计划多卫星联合反演产品（IMERG）及其回溯版本依托热带降雨测量任务（TRMM）构建，相关工作于 2019 年 7 月全部完成。该系列产品仅利用全球降水气候中心数据集（GPCC，空间分辨率 1.0°、时间分辨率逐月）的地面观测数据开展月尺度校准，存在明显局限。针对这一问题，本研究提出一种日尺度 IMERG 新型校准算法，并结合亚洲高分辨率降水数据集（APHRODITE，空间分辨率 0.25°、时间分辨率逐日）完成日尺度校准，面向亚洲区域研制出全新的 AIMERG 降水数据集（空间分辨率 0.1°、时间分辨率半小时，时间范围 2000-2015 年）。\n
数据源及相信加工方法见论文。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2015-12-31 00:00:00", "ds_acq_place": "亚洲地区", "ds_acq_lon_east": 150.0, "ds_acq_lat_south": -15.0, "ds_acq_lon_west": 60.0, "ds_acq_lat_north": 55.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 78866225445, "ds_files_count": 0, "ds_format": "Geotiff", "ds_space_res": "0.1°", "ds_time_res": "半小时", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "1b94b265-7d45-4a92-a110-f008f8ad495d.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": [ "170.45" ], "quality_level": 0, "publish_time": "2026-06-11 08:56:26", "last_updated": "2026-06-11 08:57:45", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.precipitation.db7449.2026", "i18n": { "en": { "title": "AIMERG: a new Asian precipitation dataset (0.1°/half-hourly, 2000–2015) by calibrating the GPM-era IMERG at a daily scale using APHRODITE", "ds_format": "Geotiff", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
Precipitation estimates with fine quality and spatio-temporal resolutions play significant roles in understanding the global and regional cycles of water, carbon, and energy. Satellite-based precipitation products are capable of detecting spatial patterns and temporal variations of precipitation at fine resolutions, which is particularly useful over poorly gauged regions. However, satellite-based precipitation products are the indirect estimates of precipitation, inherently containing regional and seasonal systematic biases and random errors. In this study, focusing on the potential drawbacks in generating Integrated Multi-satellitE Retrievals for \r\n
Global Precipitation Measurement (IMERG) and its recently updated retrospective IMERG in the Tropical Rainfall Measuring Mission (TRMM) era (finished in July 2019), which were only calibrated at a monthly scale using ground observations, Global Precipitation Climatology Centre (GPCC, 1.0∘/monthly), we aim to propose a new calibration algorithm for IMERG at a daily scale and to provide a new AIMERG precipitation dataset (0.1∘/half-hourly, 2000–2015, Asia) with better quality, calibrated by Asian Precipitation – Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE, 0.25∘/daily) at the daily scale for the Asian applications. The main conclusions include but are not limited to the following: (1) the proposed daily calibration algorithm (Daily Spatio-Temporal Disaggregation Calibration Algorithm, DSTDCA) is effective in considering the advantages from both satellite-based precipitation estimates and the ground observations; (2) AIMERG performs better than IMERG at different spatio-temporal scales, in terms of both systematic biases and random errors, over mainland China; and (3) APHRODITE demonstrates significant advantages compared to GPCC in calibrating IMERG, especially over mountainous regions with complex terrain, e.g. the Tibetan Plateau. Additionally, results of this study suggest that it is a promising and applicable daily calibration algorithm for GPM in generating the future IMERG in either an operational scheme or a retrospective manner.\r\n
For data sources and data processing methods, see the paper.", "ds_time_res": "", "ds_acq_place": "Asian region", "ds_space_res": "", "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, "ds_topic_tags": [ "AIMERG", "亚洲降水数据产品", "GPM", "APHRODITE" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "亚洲地区" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015 ], "ds_contributors": [ { "true_name": "马自强", "email": "ziqma@pku.edu.cn", "work_for": "北京大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "马自强", "email": "ziqma@pku.edu.cn", "work_for": "北京大学", "country": "中国" } ], "ds_managers": [ { "true_name": "马自强", "email": "ziqma@pku.edu.cn", "work_for": "北京大学", "country": "中国" } ], "category": "气象" }