Knowledge of three-dimensional (3D) cloud structures is critical for a wide range of weather and climate studies. We recently introduced satellite-based cloud vertical cross-section products for aviation weather applications. They are based on newly-processed 3D cloud data that combines multiple satellite cloud products obtained from the NOAA Enterprise Cloud Algorithm Suite and additional environmental datasets. Leveraging these research efforts and being mindful of the current and future states of global cloud data development activities, this work is now expanded to generate global 3D cloud fields by applying cloud retrieval algorithms to multiple Low Earth Orbit (LEO) and Geostationary (GEO) satellite sensors. We also incorporate enhanced cloud properties into the global framework by adopting Artificial intelligence (AI)/Machine Learning (ML) approaches. This paper presents our current accomplishments and continuing efforts for further improved satellite cloud data.