The Cloud Masking Task Team has set as its first priority the reduction of false flagging in regions of high sea surface temperature gradient. False flagging arises when spatial coherence tests are used: such tests are effective in discriminating clouds from sea areas in brightness temperature imagery for most of the ocean, but for frontal areas, cloud features and sea features on such metrics overlap and a compromise between failure to detect and false alarms is inevitable. However, systematic over-flagging of frontal areas is unsatisfactory for applications that explore ocean dynamics that generate fronts as a signature and quantifier of dynamical processes.

OBJECTIVES

Sharing good practices on cloud masking in GHRSST products, reduction of false flagging in regions of high sea surface temperature gradient.

ACTIVITIES

Priority areas:

  • Options in development for reducing false flagging include alternative metrics of spatial coherence, multi-temporal techniques, and (for contemporary sensors) use of additional (non-retrieval) channels.
  • Coastal zone cloud detection.

Achievements

• Steinar Eastwood: Sci4MaST, using cloud lidar & SynObsto test masks
• Claire Bulgin: improved used of thermal and reflectance imagery for SLSTR, reducing overflagging from thermal texture
• MingkunLiu: physics-aware machine learning, focused on cloud edges

LAST REPORT TO THE SCIENCE TEAM

TASK TEAM MEMBERS

Chair: Mingkun Liu

Co-Chair: This team is looking for a co-chair!

Members: Peter Cornillon, Mingkun Liu, Claire Bulgin, Owen Embury, Mike Chin, Steinar Eastwood, Andy Harris, Boris Petrenko, Stephane Saux-Picart, Yukio Kurihara.

TOOLS

Slack: https://ghrsstworkspace.slack.com/archives/C024XK9GT98

INTERESTED IN CONTRIBUTING?

Please contact the chair directly: Mingkun Liu,  liumingkun@ouc.edu.cn