Larisa Sogacheva

Finnish Meteorological Institute

Papers

15

Total Citations

668

H-Index

9

About

Larisa Sogacheva is a prominent atmospheric scientist whose research focuses on satellite-based aerosol remote sensing, aerosol optical depth (AOD) retrieval, and the integration of multi-satellite observations for climate and air quality applications. Her work has made substantial contributions to our understanding of aerosol loading across regional and global scales, particularly through the development and harmonization of long-term satellite aerosol records. Among her most influential contributions is her research on merging aerosol optical depth records from multiple satellite platforms — a methodologically challenging task essential for climate studies spanning decades — which has garnered over 213 citations. Her extensive analysis of two decades of AOD observations over mainland China, combining data from ATSR-2, AATSR, and MODIS instruments, has provided invaluable insights into large-scale aerosol patterns and trends, accumulating nearly 150 citations. Sogacheva has also played a key role in major international initiatives such as AeroCom-AeroSat, where she contributed to intercomparison studies evaluating 14 satellite products for aerosol model evaluation. More recently, she has pioneered the application of deep learning techniques to improve aerosol parameter accuracy in Sentinel-3 satellite products. Her body of work collectively represents a foundational resource for researchers working at the intersection of atmospheric science, satellite remote sensing, and climate modeling.

Research Focus

Key Achievements

9
H-Index
15
Papers
668
Total Citations
45
Avg Citations/Paper
🏆 Most Cited Paper
Merging regional and global aerosol optical depth records from major available satellite products
213 citations · 2020
📈 Most Prolific Year: 2020 (4 Papers)
🤝 Key Collaborators: 81
🏛 Institutions: Finnish Meteorological Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago