Assessment of variability of sea surface salinity using integrated all-weather satellite data in a tropical coast (Nigerian coastal zone)

Abstract

Abstract The tropical coasts, particularly the Nigerian coastal zone has been traditionally undersampled, and understudied using appropriate remote sensing technique. In spite of the disparity in the spatial scales of accessible all-weather satellite sea surface salinity (SSS) datasets, their integrated applications for baseline, and SSS variability studies coupled with the implications in such coastal zone at local scale are crucial for supporting relevant decisions. We utilized integrated SSS datasets from Aquarius/Satélite de Aplicaciones Científicas (SAC)-D (Aquarius) and Soil Moisture Active Passive mission (SMAP) satellite products in this study. We determine their accuracy. We assess the interannual and seasonal variability of the monthly SSS (Jan., 2012-Dec., 2021); and determine their potential implications for changes in the freshwater flux (FWF) and tidal rivers discharge. We show RMSD of 0.1100 psu and 0.1236 psu for Aquarius and SMAP respectively. We show Coefficient of Variation (CV) of 0.66% and 2.96% for the interannual SSS variability (iSSSv) and the seasonal SSS variability (sSSSv) respectively. We show that the negative average annual percentage change (NAAPC, -0.06%) and the negative average seasonal percentage change (NASPC, -0.21%) imply the predominance of net positive FWF, and of relatively high freshwater discharge into the coastal zone. The results suggest relatively stable iSSSv; and low risk of upstream seawater intrusion from the Nigerian coastal zone. Despite the difference in spatial resolution of the two datasets, the results further suggest a relatively accurate integrated dataset for assessing SSS variability; and for monitoring SSS for the risk of upstream seawater intrusion in the tropics.