%0 Journal Article %1 ullman_evaluation_2000 %A Ullman, David S. %A Cornillon, Peter C. %D 2000 %J Journal of Atmospheric and Oceanic Technology %K Temperature fronts, sea, %N 12 %P 1667--1675 %R 10.1175/1520-0426(2000)017<1667:EOFDMF>2.0.CO;2 %T Evaluation of front detection methods for satellite-derived SST data using in situ observations %U http://journals.ametsoc.org/doi/full/10.1175/1520-0426%282000%29017%3C1667%3AEOFDMF%3E2.0.CO%3B2 %V 17 %X 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 (\textless10 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.

@article{ullman_evaluation_2000, 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 ({\textless}10 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.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Ullman, David S. and Cornillon, Peter C.}, biburl = {https://www.bibsonomy.org/bibtex/291c038d659049854ace83621b28f177e/yourwelcome}, doi = {10.1175/1520-0426(2000)017<1667:EOFDMF>2.0.CO;2}, interhash = {06d8f87fe4d4def5de9b34172adca84f}, intrahash = {91c038d659049854ace83621b28f177e}, issn = {0739-0572, 1520-0426}, journal = {Journal of Atmospheric and Oceanic Technology}, keywords = {Temperature fronts, sea,}, month = dec, number = 12, pages = {1667--1675}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Evaluation of front detection methods for satellite-derived {SST} data using in situ observations}, url = {http://journals.ametsoc.org/doi/full/10.1175/1520-0426%282000%29017%3C1667%3AEOFDMF%3E2.0.CO%3B2}, urldate = {2012-09-17}, volume = 17, year = 2000 }