Detection of surface temperature anomaly of the Sea of Marmara

Monitoring sea surface temperature (SST) over a long-term and detecting the anomalies highly contribute to understanding the pre-vailing water quality of the sea. Earth observation satellite images are the key data sources that offer the long-term SST detection in cost and time effective way. Since the Sea of Marmara in Tu center dot rkiye is surrounded by the highly populated provinces, the water quality of the sea has gained importance for scientific and public communities over the years. This article emphasizes on the significance of detect-ing SST trend and corresponding anomalies of the Sea of Marmara over the past 32 years. To address the SST variations of the Sea of Marmara in time, a comprehensive set of both field and satellite data regarding SSTs were obtained within the context of this study. The SST trend and its anomalies between the years 1990 and 2021 were detected by applying Seasonal-Trend decomposition procedure based on LOESS (STL) method to NOAA OISST V2 data. On the other hand, spatial SST distribution was detected with Landsat-8, Sentinel-3 and NOAA OISST V2 satellite data. SST results were verified with the in-situ data within the scope of accuracy assessment. The results showed that SST time-series data performed an increasing trend and had anomalies mostly during the spring months in the recent years. (c) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

Automated summary

Monitoring sea surface temperature (SST) over a long-term and detecting the anomalies are important for understanding the water quality of the sea. Earth observation satellite images provide cost and time effective data for long-term SST detection. This article emphasizes on the significance of detecting SST trend and anomalies of the Sea of Marmara over the past 32 years, and presents the results of increasing SST trend and anomalies mostly during the spring months.