Evidence map›Paper›PMID 41781617›Full record

ArticleNature2026

Advancing operational global aerosol forecasting with machine learning.

Ke Gui, Xutao Zhang, Huizheng Che, Lei Li, Yu Zheng, Linchang An, Yucong Miao, Hujia Zhao, Oleg Dubovik, Brent Holben and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Ke Gui *State Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.ORCID 0000-0002-8444-9547
Xutao Zhang *State Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.
Huizheng CheState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China. chehz@cma.gov.cn.ORCID 0000-0002-9458-3387
Lei LiState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.ORCID 0000-0003-4502-7533
Yu ZhengState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.ORCID 0000-0002-5991-8014
Linchang AnNational Meteorological Center, CMA, Beijing, China.ORCID 0009-0003-7242-0522
Yucong MiaoState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.
Hujia ZhaoInstitute of Atmospheric Environment, China Meteorological Administration, Shenyang, China.
Oleg DubovikUniversité de Lille, CNRS, UMR 8518-Laboratoire d'Optique Atmosphérique, Lille, France.ORCID 0000-0003-3482-6460
Brent HolbenNASA Goddard Space Flight Center, Greenbelt, MD, USA.
Jun WangDepartment of Chemical and Biochemical Engineering, The University of Iowa, Iowa City, IA, USA.ORCID 0000-0002-7334-0490
Pawan GuptaNASA Goddard Space Flight Center, Greenbelt, MD, USA.
Elena S LindNASA Goddard Space Flight Center, Greenbelt, MD, USA.
Carlos ToledanoGroup of Atmospheric Optics, University of Valladolid, Valladolid, Spain.ORCID 0000-0002-6890-6648
Hong WangState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.
Zhili WangState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China.ORCID 0000-0002-4392-3230
Yaqiang WangInstitute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, China.
Xiaomeng HuangDepartment of Earth System Science, Tsinghua University, Beijing, China.ORCID 0000-0002-4158-1089
Kan DaiNational Meteorological Center, CMA, Beijing, China.ORCID 0009-0009-5923-2109
Xiangao XiaLaboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
Xiaofeng XuChina Meteorological Administration, Beijing, China.
Xiaoye ZhangState Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW) and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China. xiaoye@cma.gov.cn.ORCID 0000-0003-2853-9596

Funding

National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaYouth Innovation Team of China Meteorological Administration
6 · The paper itself

Abstract

Aerosol forecasting is important for air-quality management, health risk assessment and climate change mitigation

Indexed as

Air PollutantsMachine LearningAerosolsAtmosphereDustForecastingMeteorologyWeatherAerosolsAir PollutantsDust

Identifiers

PMID41781617
PMCPMC12999505

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.