Jhoon Kim

A gapless 0.05° daytime-hourly tropospheric NO 2 dataset (2019–2024) over key Asian hotspots reconstructed using physics-aware deep learning

Abstract. High-frequency continuous monitoring of tropospheric nitrogen dioxide (NO2) is crucial for assessing regional air quality and investigating photochemical dynamic evolution. Although new-generation geostationary orbit (GEO) satellites (e.g., GEMS) provide hourly observat...

A Physics‐Guided Feature Selection Machine Learning Approach for Cloud Probability Retrieval and Detection From TEMPO Imagery

Abstract Accurate cloud detection is critical for reliable retrievals of aerosols and trace gases from remote‐sensing measurements. TEMPO provides unprecedented hourly observations over North America, but radiometric calibration biases, thousands of spectral channels, and limited...