Mika E. Mononen

Papers

1

Total Citations

34

H-Index

1

About

Mika E. Mononen is a leading researcher in atmospheric science, with a primary focus on aerosol optical depth (AOD) retrieval and the application of machine learning to environmental data. His most cited work, a 2016 study, tackles a critical challenge: reconstructing historical aerosol levels before dedicated satellite measurements began in the 1990s. Mononen pioneered the use of machine learning algorithms, combined with non-linear regression and radiative transfer-based look-up tables, to accurately estimate AOD from surface solar radiation measurements. This innovative approach has garnered 34 citations, providing a vital tool for understanding long-term aerosol trends and their impact on climate forcing. By bridging the gap between modern satellite data and historical records, Mononen’s research enables more robust assessments of anthropogenic aerosol effects on the Earth’s energy balance. His work stands as a key contribution to atmospheric physics and climate modeling, demonstrating how computational methods can unlock new insights from existing observational data.

Research Focus

Key Achievements

1
H-Index
1
Papers
34
Total Citations
34
Avg Citations/Paper
🏆 Most Cited Paper
Retrieval of aerosol optical depth from surface solar radiation measurementsusing machine learning algorithms, non-linear regression and a radiativetransfer-based look-up table
34 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 12

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago