About Me:
Chuck received his B.S. in Atmospheric Sciences in 2012 at the University of Illinois – Urbana Champaign. He continued his education at the University of Wisconsin – Madison where he obtained his M.S. in Atmospheric and Oceanic Sciences in 2016. His M.S. thesis was centered around the creation of long-term satellite records of lake-surface temperatures from the several-decade long AVHRR record with specific foci on orbital drift corrections, diel LST variability, spatio-temporal coherence, and upwelling identification. Chuck continued his PhD at UW-Madison and shifted his focus to studying applications of machine learning methods to cloud property estimation from passive satellite imagers, and considerations for their use in cloud climate records.
Chuck joined CIRA as a postdoc in March 2022 and is continuing work on several applications of ML to cloud property estimation including cloud detection, cloud-top pressure, and vertical distributions of cloud water content from passive imager data. His other areas of interest include satellite climate record development, super-resolution of remote sensing imagery, and atmospheric radiative transfer.
- MetSat
- CIRA Machine Learning (ML)