Kai-Lan Chang

Assessing the Impact of Incorporating Bias-Adjusted Satellite Observations into Global Data Fusion for Ground-level Health-Related Ozone Metrics

Understanding global ground-level ozone is hindered by significant monitoring gaps. To address this, we introduce a Bayesian Maximum Entropy data fusion framework that includes satellite ozone observations, generating a global 0.1° surface ozone dataset (2005–2022). Satellite obs...