The cira team developed the enterprise cloud base height (CBH)/cloud geometric thickness (CGT) algorithm that was initially established using viirs data and was followed by a version of the…

The cira team developed the enterprise cloud base height (CBH)/cloud geometric thickness (CGT) algorithm that was initially established using viirs data and was followed by a version of the algorithm using goes-r series advanced baseline imager (ABI) data. This product is a key component required to provide satellite-based 3D cloud information. Tied to the NOAA jpss pgrr research project at cira, we introduced a cloud vertical cross-section algorithm (CVC) along flight paths over alaska and extended this effort to CONUS using goes-16 ABI data, focusing on the needs of aviation users. More recently, cira started incorporating hrrr smoke model data as requested by users for improved visibility information. As part of this project, cira will provide user-selectable CVC products by combining goes-16/18 ABI data over an expanded domain including all of north america. The algorithms can be applied to all ABI sensors onboard the goes-r series, and the fundamental framework will also be applicable to noaas future geostationary extended observations (geoxo) satellite system. This project directly addresses noaas weather-ready nation objectives. The products and user documents will be available on-line for the general public and will help noaas mission to provide enhanced satellite data for aviation applications.