About

Dr. Jianglong Zhang is a leading figure in aerosol remote sensing and data assimilation, whose work has fundamentally advanced our understanding of atmospheric aerosols and their climate impacts. His research centers on satellite-based aerosol optical property retrieval, aerosol data assimilation, and the characterization of biomass burning emissions. Dr. Zhang's most influential contribution is his seminal 2005 review on the intensive optical properties of biomass burning particles, which has garnered over 1,200 citations and remains a cornerstone reference in the field. He has also pioneered the development of fused aerosol products, notably the 11-year global gridded aerosol optical thickness reanalysis (v1.0), which provides a critical, regularly-gridded dataset for climate and atmospheric sciences. His methodological innovations include the SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm and the identification of cloud artifacts in MODIS aerosol products, both of which have improved the accuracy of satellite-derived aerosol data. Dr. Zhang's impact extends to operational forecasting through his leadership in the International Cooperative for Aerosol Prediction (ICAP) multi-model ensemble, which now integrates nine global models. His work on assimilating AERONET and MODIS observations into the Navy Aerosol Analysis Prediction System (NAAPS) has directly enhanced aerosol forecasting skill, demonstrating the practical value of his research for air quality and climate prediction.

Research Focus

Key Achievements

21
H-Index
35
Papers
3,125
Total Citations
89
Avg Citations/Paper
🏆 Most Cited Paper
A review of biomass burning emissions part III: intensive optical properties of biomass burning particles
1,227 citations · 2005
📈 Most Prolific Year: 2018 (5 Papers)
🤝 Key Collaborators: 128
🏛 Institutions: University of Alabama in Huntsville, University of North Dakota, United States Naval Research Laboratory, Grand Forks Air Force Base

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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