Spatial and temporal scales of variability in Tropical Atlantic sea surface salinity from the SMOS and Aquarius satellite missions

摘要

Taking advantage of the spatially dense, multi-year time series of global Sea Surface Salinity (SSS) from two concurrent satellite missions, the spatial and temporal decorrelation scales of SSS in the Tropical Atlantic 30 degrees N-30 degrees S are quantified for the first time from SMOS and Aquarius observations. Given the dominance of the seasonal cycle in SSS variability in the region, the length scales are calculated both for the mean and anomaly (i.e. seasonal cycle removed) SSS fields. Different 7-10 days composite SSS products from the two missions are examined to explore the possible effects of varying resolution, bias corrections and averaging characteristics. With the seasonal cycle retained, the SSS field is characterized by strongly anisotropic spatial variability. Homogeneous SSS variations in the Tropics have the longest zonal scales of over similar to 2000 km and long temporal scales of up to similar to 70-80 days, as shown by both SMOS and Aquarius. The longest meridional scales, reaching over similar to 1000 km, are seen in the South Atlantic between similar to 10 degrees-25 degrees S, most discernible in Aquarius data. The longest temporal scales of SSS variability are reported by both satellites to occur in the North-West Atlantic region 15 degrees-30 degrees N, at the Southern end of the Sargasso Sea, with SSS persisting for up to 150-200 days. The removal of the seasonal cycle results in a noticeable decrease in the spatio-temporal decorrelation scales over most of the basin. Overall, with the exception of the differences in the South Atlantic, there is general agreement between the spatial and temporal scales of SSS from the two satellites and different products, despite differences in individual product calibration and resolution characteristics. These new estimates of spatio-temporal decorrelation scales of SSS improve our knowledge of the processes and mechanisms controlling the Tropical Atlantic SSS variability, and provide valuable information for a wide range of oceanographic and modelling applications. (C) 2016 The Authors. Published by Elsevier Inc.