AI-Resolved Atmosphere

Constraining Global Black Carbon Radiative Forcing
Using Particle Mixing State Information

Bridging the Gap between Micro-Scale Aerosol Physics and Global Climate Forcing
through Foundation Models and Active Learning

Explore Research

Core Research

The Methodology & Global Impact

Active Learning Strategy

Confidence-aware acquisition for expensive aerosol labels. Like a master calligrapher knowing exactly where to place the brush, AI guides the simulation to maximum efficiency.

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Foundation Model

A global atmospheric model constrained by extensive ground and aircraft observations. Bridging the theoretical gap between idealized physics and reality.

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Direct Forcing

Calculating mixing-state-resolved optical properties. Understanding how black carbon absorbs light and warms the planet at a granular level.

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Cloud Interaction

Investigating Black Carbon as Cloud Condensation Nuclei (CCN). Tracing the invisible paths of aerosols as they alter cloud microphysics.

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Emerging Frontiers

Nanoplastics in the Atmosphere

Modeling Review

A comprehensive review of atmospheric nanoplastics modeling. Analyzing transport mechanisms and identifying critical knowledge gaps.

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Urban Nano-Plastics

Quantifying the impact of urban atmospheric nanoplastics on cloud processes. Revealing the hidden footprint of our cities in the skies above.

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