Evaluation of Front Detection Methods for Satellite-Derived SST Data Using In Situ Observations

Authors

David S. Ullman, University of Rhode IslandFollow
Peter C. Cornillon, University of Rhode IslandFollow

Document Type

Article

Date of Original Version

2000

Department

Oceanography

Abstract

Sea surface temperature (SST) fronts detected in Advanced Very High Resolution Radiometer (AVHRR) data using automated edge-detection algorithms were compared to fronts found in continuous measurements of SST made aboard a ship of opportunity. Two histograms (a single-image and a multi-image method) and one gradient algorithm were tested for the occurrence of two types of errors: (a) the detection of false fronts and (b) the failure to detect fronts observed in the in situ data. False front error rates were lower for the histogram methods (27%–28%) than for the gradient method (45%). Considering only AVHRR fronts for which the SST gradient along the ship track was greater than 0.1°C km⁻¹, error rates drop to 14% for the histogram methods and 29% for the gradient method. Missed front error rates were lower using the gradient method (16%) than the histogram methods (30%). This error rate drops significantly for the histogram methods (5%–10%) if fronts associated with small-scale SST features (km) are omitted from the comparison. These results suggest that frontal climatologies developed from the application of automated edge-detection methods to long time series of AVHRR images provide acceptably accurate statistics on front occurrence.

Citation/Publisher Attribution

Ullman, D.S. and P.C. Cornillon, 2000: Evaluation of Front Detection Methods for Satellite-Derived SST Data Using In Situ Observations. J. Atmos. Oceanic Technol., 17, 1667–1675. doi: 10.1175/1520-0426(2000)0172.0.CO;2.

Available at: https://doi.org/10.1175/1520-0426(2000)0172.0.CO;2