Variability of sea surface salinity in the tropical Indian Ocean as inferred from Aquarius and in situ data sets

Abstract

Sea surface salinity (SSS) is one of the key components of the Earth's global water cycle. Reliable information on SSS is very important for ocean modelling, data assimilation, and ocean and climate research applications. In this study, SSS variability in the tropical Indian Ocean (TIO) was analysed using the Aquarius instrument on board the SAC-D satellite and in situ observations from the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) buoys and Array for Real-Time Geostrophic Oceanography (ARGO) data sets for the period 2012-2013. Comparison of two recent versions (V2 and V3) of Aquarius-based SSS estimates to nine RAMA buoys on a daily timescale showed excellent mutual agreement. The systematic underestimation of SSS by satellite-based V2 products over the TIO shows a clear advantage for the new version product (V3). A larger root-meansquare error of the order of 0.50 psu in the satellite-based SSS was observed over the highly variable (larger standard deviation) Bay of Bengal region as compared with ARGO data sets. In the eastern equatorial Indian Ocean region, satellite-based SSS overestimated SSS below 34 psu and underestimated SSS of 34-35 psu as compared with ARGO data. However, the V3 SSS from Aquarius showed marginal improvement over V2 SSS. Monthly variation and fast Fourier analysis of the satellite-based SSS estimates are in reasonably good agreement with in situ observations which suggest that Aquarius is able to capture SSS variability in the TIO. The Aquarius-based V3 SSS showed a temporal autocorrelation of 0.6 over most parts of the TIO up to day 10, and decreased gradually with time. Overall analysis suggests that Aquarius-derived V3 SSS can detect variability in SSS satisfactorily in the TIO and is in reasonably good agreement with in situ observations.

Observed Variability of Near-Surface Salinity Field on Seasonal and Interannual Time Scales and Its Impact on the Evolution of Sea Surface Temperature of the Tropical Indian Ocean

“…The numerical models have also reached reasonable level of maturity to reproduce the observed salinity fields in the tropical Indian Ocean with good accuracy , Howden and Murtugudde, 2001, Sharma et al, 2010, Parekh et al, 2015. In addition, the efforts on remote sensing of sea surface salinity (SSS) with SMOS and Aquarius are also progressing to map the global ocean surface salinity fields (Durand et al, 2013, Momin et al, 2015. So in the light of the availability of these recent measurements and numerical model outputs it is now possible to characterise and explain the nature of the observed near-surface salinity field both on intraseasonal and interannual time scales with greater confidence level.…”

“…Satya Prakash et al (2012) have studied the observed relationship between surface freshwater flux and salinity in the north Indian Ocean. Momin et al ( 2015) have studied the observed variability of sea surface salinity in the tropical Indian Ocean as inferred from Aquarius and in situ data sets. Recently Zweng et al (2013) have updated the earlier climatologies to provide a comprehensive description on the salinity field of the global ocean.…”

Revisiting the Global Patterns of Seasonal Cycle in Sea Surface Salinity

“…The STD of the monthly mean SSS values is used as a measure of SSS seasonal variability (Figure 4). Argo shows that large STDs (>0.4 pss) dominates the following areas: the pan-tropical low salinity zone under the ITCZ and SPCZ, the near coastal areas affected by the Amazon plume in the western tropical Atlantic (Fournier, Vandemark, et al, 2017;Grodsky et al, 2014) and the Congo and Niger rivers in the eastern equatorial Atlantic (Chao et al, 2015;Reul et al, 2014), the northwestern Atlantic shelf region particularly south of the St. George's and Newfoundland banks (Grodsky et al, 2017), the northern Gulf of Mexico bordering the Mississippi (da Silva & Castelao, 2018), the vicinity of the western South Atlantic near 35°S, 55°W under the influence of the Rio de la Plata (Piola et al, 2005), the Bay of Bengal impacted by monsoon and the Ganges/Brahmaputra river (Momin et al, 2015;Fournier, Vialard, et al, 2017), and the southeastern Arabian Sea centered at 8°N, 75°E, known as the Laccadive Sea region (also called the Lakshadweep Sea) (Bruce et al, 1994;Schott & McCreary, 2001). All of these high STD regions are in direct response to the freshwater sources from rainfall and/or river discharge, except for the high STD in the Laccadive Sea of the Arabian Sea.…”

Spatiotemporal variability of sea surface salinity and its covariation with freshwater flux in the Indo-Pacific Warm Pool region

“…The anomalously high and low SSS in the subtropical and tropical mostly coincide with sea surface freshwater flux (F) [3] . Hence, having better knowledge of the spatiotemporal variability of SSS and its covariation patterns with F is of great importance to well understanding the various processes in the coupled ocean-atmosphere dynamic [4] .…”