探究大气气溶胶的时空变化规律，对气候变化与环境科学研究具有重要意义。多角度大气校正算法（MAIAC）反演的卫星气溶胶光学厚度（AOD），凭借高时空分辨率，为刻画全球气溶胶负荷提供了有力支撑。但该数据存在非随机缺失问题，难以实现全国范围气溶胶负荷的长时序精准评估。本数据集构建一套自适应高时空分辨率 AOD 插补模型框架，融合随机森林模型与多源数据（模拟 AOD、气象数据、地表环境数据），为我国全域气溶胶长、短期研究提供全覆盖数据集支撑。研究采用时间分层策略，以 MAIAC AOD 为目标变量，逐日构建插补模型。该方法能够有效捕捉海量数据中复杂的时空分异特征，生成逐日全覆盖 AOD 产品，整体精度较高：与地面实测 AOD 对比验证，决定系数R2达 0.77。\n
本数据集整合了MAIAC 原始气溶胶光学厚度反演结果与基于随机森林算法得到的缺值区域估算结果，形成逐日全覆盖气溶胶光学厚度（AOD）数据。数据以 CSV 格式存储，单个压缩包包含整月数据。本研究得到的全覆盖 AOD 插补数据集，可完整呈现大气气溶胶短期污染过程与长期变化趋势，能够为相关科研工作及环境管理提供数据支撑。\n
使用本数据集请引用下文所列相关文献。如需 2012 年及更早时段的数据，可发送邮件至邮箱 qqhe@whut.edu.cn 联系作者。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": "2013-01-01 00:00:00", "ds_acq_end_time": "2022-12-31 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": 52424434712, "ds_files_count": 0, "ds_format": "CSV", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "82bab287-bbbe-4f73-bca4-228253f30e2a.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a3ce23a2-c353-4383-a544-65c8f218579f", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 0, "publish_time": "2026-06-12 17:26:45", "last_updated": "2026-06-12 17:26:45", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.atmosphere.db7451.2026", "i18n": { "en": { "title": "Daily full-coverage, 1-km MAIAC Aerosol Optical Depth (AOD) data in China (2013-2022) - Daily data", "ds_format": "CSV", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
Investigating spatiotemporal variations of atmospheric aerosols is important for climate change and environmental research. Although satellite aerosol optical depth (AOD) retrieved by the MAIAC (Multiangle Implementation of Atmospheric Correct) algorithm provides a unique opportunity to represent global aerosol loading with high spatiotemporal resolution, accurate assessment of long-term aerosol loading countrywide is still challenging due to its non-random missingness. This study aimed to develop an adaptive spatiotemporal high-resolution imputation modeling framework for AOD that incorporates random forest models and multisource data (the simulated AOD, meteorological, and surface condition data) to support full-coverage long- and short-term aerosol studies in China. Aided by the time-stratified approach, the imputation model was constructed for each day, and the MAIAC AOD was used as the target variable. The proposed approach could effectively capture the massive spatiotemporal variability in a large amount of data and deliver full-coverage AODs with high accuracies at a daily timescale (i.e., overall validation R2 against ground-level AOD measurements of 0.77). \r\n
Here we share the daily full-coverage AOD data, which combined the random forest estimates over the areas without MAIAC AOD retrievals and MAIAC original AOD retrievals wherever available. This daily dataset is archived in CSV format and each zip file contains one-month data. Consequently, our full-coverage AOD imputations can advance scientific research and environmental management by supporting national and local complete pictures of both short-term episodes and long-term trends in atmospheric aerosols.\r\n
Please cite the relevant references listed below when using this dataset. For data from 2012 and earlier, please contact the authors via email at qqhe@whut.edu.cn.", "ds_time_res": "", "ds_acq_place": "China", "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": [ "AOD", "气溶胶光学厚度", "无缝全覆盖" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 ], "ds_contributors": [ { "true_name": "何青青", "email": "qqhe@whut.edu.cn", "work_for": "武汉理工大学资源与环境工程学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "何青青", "email": "qqhe@whut.edu.cn", "work_for": "武汉理工大学资源与环境工程学院", "country": "中国" } ], "ds_managers": [ { "true_name": "何青青", "email": "qqhe@whut.edu.cn", "work_for": "武汉理工大学资源与环境工程学院", "country": "中国" } ], "category": "气象" }