Interpretable Machine Learning Quantifies Composition and Size Controls on Aerosol Spectral Absorption
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资源简介：
The data file includes (1) AERONET aerosol optical,chemical composition and size data, (2) the absorption coefficients of total aerosols at 405,532, and 870 nm, and absorption Ångström exponent (AAE), (3) chemical composition data obtained from in-situ observation. The code file contains Python scripts for generating each graph and for implementing the interpretable machine-learning framework used to predict AAE, radiative forcing, and radiative forcing efficiency.
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Zenodo创建时间：
2026-01-09
