Harish Gadhavi
Papers
2
Total Citations
8
H-Index
2
About
Harish Gadhavi is a remote sensing scientist whose work tackles one of climate science’s biggest uncertainties: aerosol–cloud interactions. His research centers on developing novel algorithms to retrieve cloud condensation nuclei (CCN) profiles from lidar observations, bridging a critical gap between satellite measurements and the microphysical processes that govern cloud formation and precipitation. Gadhavi’s major contribution is a pioneering remote-sensing algorithm that quantifies vertically resolved CCN number concentrations from both airborne and spaceborne lidar. This work, detailed in his 2024 paper (6 citations), enables scientists to map where and how aerosols influence cloud properties across the atmospheric column—a feat previously limited to sparse in-situ measurements. His 2022 paper (2 citations) further established the foundation for retrieving these profiles from space, demonstrating the feasibility of global-scale CCN monitoring. By transforming lidar backscatter into actionable CCN data, Gadhavi’s research directly supports improved climate models and a deeper understanding of how pollution and natural aerosols modulate cloud radiative effects. His algorithm represents a significant step toward reducing the largest source of uncertainty in climate projections, making his work essential reading for anyone studying aerosol–cloud interactions or satellite remote sensing.
Research Focus
Key Achievements
Top Papers
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