Persistent upwelling in the Mid-Atlantic Bight detected using gap-filled, high-resolution satellite SST

• Published in: Remote sensing of environment Vol. 262; p. 112487
• Main Authors: Murphy, Sarah C., Nazzaro, Laura J., Simkins, James, Oliver, Matthew J., Kohut, Josh, Crowley, Michael, Miles, Travis N.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01-09-2021; Elsevier BV
• Subjects: Atmospheric models; Atmospheric processes; Cloud removal; Clouds; Coastal zone; Cold pool; Environmental impact; GOES-16; High-resolution; Identification methods; Mid-Atlantic Bight; Ocean models; Oceans; Satellite; Sea surface temperature; Spikes; Surface temperature; Temperature fields; Upwelling; GOES-16; Cold pool; High-resolution; Satellite; Upwelling; Cloud removal; Sea surface temperature; Mid-Atlantic Bight
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2021.112487

This study applied a Spike-Filter (SF) method to identify and remove rapidly moving clouds over the coastal ocean in GOES-16 satellite sea surface temperature fields (SST). These images were then gap-filled to capture upwelling in the Mid Atlantic Bight (MAB), a critical process that impacts ecosystems and atmospheric processes in the region and is important to coastal regions around the world. During the 2019 upwelling season, the default Quality Filter (QF) provided to identify and remove clouds from GOES SST consistently removed upwelling pixels, resulting in ~15% MAB coastal SST coverage. The Spike Filter (SF) method increased MAB coastal SST coverage to 30% and maintained overall accuracy. GOES SF DINEOF SST approximately doubled the number of detected upwelling days compared to MUR SST. The longest upwelling event detected in GOES SF DINEOF persisted for over 17 days, which is longer than upwelling events previously observed in the MAB (Glenn et al., 2004).This suggests that the MAB can have persistent, rather than episodic upwelling as previously thought. Clear detection of the timing and duration of upwelling events is important as it provides estimates for ecological and physical responses in the MAB and coastal regions around the world. GOES-16 SST has the potential to improve upwelling detection and should be further studied for application in ocean and atmospheric modeling.
•GOES SST is valuable for the detection of coastal upwelling.•The MAB can have persistent, rather than episodic upwelling as previously thought.•GOES SF DINEOF detected double the number of upwelling days compared to MUR.•The GOES-16 NOAA Quality Filter removes coastal upwelling features in the MAB•The Spike Filter effectively removed clouds from GOES SST and retained upwelling pixels