GOES ABI Detection of Thin Cirrus over Land
Abstract
This study develops a new thin cirrus detection algorithm applicable to overland scenes. The methodology builds from a previously developed overwater algorithm, which makes use of the Geostationary Operational Environmental Satellite 16 (GOES-16) Advanced Baseline Imager (ABI) channel 4 radiance (1.378-μm “cirrus” band). Calibration of this algorithm is based on coincident Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud profiles. Emphasis is placed on rejection of false detections that are more common in overland scenes. Clear-sky false alarm rates over land are examined as a function of precipitable water vapor (PWV), showing that nearly all pixels having a PWV of H removes significant land surface and low-/midlevel cloud false alarms from the overall sample while preserving over 80% of valid cirrus pixels. Additionally, the use of an aggressive PWV layer threshold preferentially removes noncirrus pixels such that the remaining sample is composed of nearly 70% cirrus pixels, at the cost of a much-reduced overall sample size. This study shows that lower-tropospheric clouds are a much more significant source of uncertainty in cirrus detection than the land surface.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 01, 2022
- Source ID
- 10.1175/jtech-d-21-0160.1
Entities
People
- Anne Garnier
- Arunas P. Kuciauskas
- David A. Peterson
- Erica K. Dolinar
- James R. Campbell
- Jared W. Marquis
- Melinda L. Surratt
- Simone Lolli
- Steven D. Miller
- Theodore M. McHardy
- Xiquan Dong
Organizations
- American Society for Engineering Education
- Colorado State University
- Office of Naval Research
- United States Naval Research Laboratory
- University of Arizona
- University of North Dakota