Generating A Monthly Variability of Sea Surface Salinity Based on Source Tracing of Salt Concentration and The Estimated SEBAL-Evaporation Mochamad Firman Ghazali*1,3, Asep Saepuloh2,3, Ketut Wikantika3,4
1. Earth Sciences, Faculty of Earth Sciences and Technology, ITB, Bandung-Indonesia
2. Geological Engineering, Faculty of Earth Sciences and Technology, ITB, Bandung-Indonesia
3. Center for remote sensing (CRS-ITB) Bandung-Indonesia
4. Geodesy and Geomatics Engineering, Faculty of Earth Sciences and Technology, ITB, Bandung-Indonesia
Abstract
The variation and spatial distribution of sea surface salinity (SSS) depend on the geographic condition of the water surfaces and the temporal variation of atmospheric conditions. The SSS might differ in a local coastal area compared to similar situations in global and regional oceans. The SSS values have been estimated based on spatial regression of extracted water-salt concentration as a source tracing of salt against corrected Landsat 8 satellite data during the drought season of April 2023. This result, paired with the evaporation-derived surface energy balance algorithm for land (SEBAL) algorithm, explains a monthly SSS variability after the validation using pre-defined resampled regional SSS and evaporation data. The result shows variations in estimated SSS values along with fluctuated SEBAL evaporation, describing monthly variability and the relationship between SSS and evaporation in a local coastal area limited to the condition of a drought season. The fluctuated pattern is applied for both parameters. However, the validation shows the root means square error (RMSE) values range satisfied only for the monthly variability pattern of SSS and evaporation followed by reasonable accuracy.
