Other algorithm studies
Read our other algorithm studies for current, future and multi-missions.
30 May 2022
03 August 2020
The purpose of this project is to improve cloud detection in coastal regions for sea surface temperature (SST) products from the Copernicus Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) instrument. Although coastal zones comprise a small fraction of the global oceans, they are of significant interest to users of SST, and play an important role in livelihoods and local economies. This project addresses a user requirement to improve the quality of cloud masking in coastal zones, maximising the near-coastal SST data coverage.
The main objective of this project is to test evolutions to the SLSTR cloud detection algorithm in coastal regions. A survey of user requirements has identified the following key issues that need to be addressed:
This project seeks to improve the existing Bayesian cloud detection system applied operationally to SLSTR SST data production in coastal zones. Coastal zones are typically characterised by more turbulent water and increased volume scattering from the entrainment of sediment and phytoplankton, which affects ocean colour. Upwelling is also common in coastal regions, resulting in locally cool waters and strong thermal gradients. These differences between coastal waters and open oceans mean that adaptations to the cloud detection algorithm are required to obtain performance comparable to that over the open ocean. Using unmodified open-ocean approaches, coastal margins are frequently incorrectly flagged as cloud (Figure 1). The following evolutions of the Bayesian cloud detection will be considered in this project: