Their new technique using symmetric filters is described in their new article in the July 2019 issue of the Journal of Atmospheric and Oceanic Technology. During each ATMS scanning cycle, the antenna first scans the Earth scene, then cold space, and finally the blackbody warm target to record the measured scene counts, warm counts, and cold counts when these three segments are completed.
The new approach removes the high-frequency striping without altering the low-frequency weather signals and outperforms the current operational “boxcar” filters for ATMS.
A Fellow of the American Meteorological Society, Zou has research interests in atmospheric data assimilation, hurricanes, and climate changes. Her research has expanded over the past five years to include satellite data calibration, as well as validation and assimilation for both numerical weather prediction (NWP) and climate trend study.
To read their paper, click here: “Mitigation of Striping Noise in ATMS Calibration Counts by Symmetric Filters”.