A gridded sea surface salinity data set for the tropical Pacific with sample applications (1950–2008)

We present a gridded data set of Sea Surface Salinity (SSS) for the tropical Pacific (120°E–70°W; 30°N–30°S), with a grid resolution of 1° longitude, 1° latitude and 1 month, from 1950 to 2008. The product, together with its associated error field, is derived from an objective analysis of about 10 million validated SSS records, with most of the data originating from Voluntary Observing Ships, TAO/TRITON moorings and Argo profilers (during the most recent period). We expect this product to benefit studies in oceanography, meteorology and paleoceanography. As examples of applications, we analyse: (a) the seasonal and ENSO (El Niño Southern Oscillation) modes of observed SSS variability, (b) the ability of 23 coupled models used in the Intergovernmental Panel for Climate Change 4th Assessment Report (IPCC AR4) to simulate the mean SSS and these two time varying modes, and (c) the usefulness of the SSS product and of its associated error field in calibrating and validating the paleo-salinity time series. We anticipate improvements and regular updates to our product, as more SSS data become available from in situ networks and from the ongoing and near-future satellite-derived observations by SMOS (Soil Moisture and Ocean Salinity) and Aquarius.     

SMOS reveals the signature of Indian Ocean Dipole events

The tropical Indian Ocean experiences an interannual mode of climatic variability, known as the Indian Ocean Dipole (IOD). The signature of this variability in ocean salinity is hypothesized based on modeling and assimilation studies, on account of scanty observations. Soil Moisture and Ocean Salinity (SMOS) satellite has been designed to take up the challenge of sea surface salinity remote sensing. We show that SMOS data can be used to infer the pattern of salinity variability linked with the IOD events. The core of maximum variability is located in the central tropical basin, south of the equator. This region is anomalously salty during the 2010 negative IOD event, and anomalously fresh during the 2011 positive IOD event. The peak-to-peak anomaly exceeds one salinity unit, between late 2010 and late 2011. In conjunction with other observational datasets, SMOS data allow us to draw the salt budget of the area. It turns out that the horizontal advection is the main driver of salinity anomalies. This finding is confirmed by the analysis of the outputs of a numerical model. This study shows that the advent of SMOS makes it feasible the quantitative assessment of the mechanisms of ocean surface salinity variability in the tropical basins, at interannual timescales.

     

Sea Surface Salinity Observations from Space with the SMOS Satellite: A New Means to Monitor the Marine Branch of the Water Cycle

While it is well known that the ocean is one of the most important component of the climate system, with a heat capacity 1,100 times greater than the atmosphere, the ocean is also the primary reservoir for freshwater transport to the atmosphere and largest component of the global water cycle. Two new satellite sensors, the ESA Soil Moisture and Ocean Salinity (SMOS) and the NASA Aquarius SAC-D missions, are now providing the first space-borne measurements of the sea surface salinity (SSS). In this paper, we present examples demonstrating how SMOS-derived SSS data are being used to better characterize key land–ocean and atmosphere–ocean interaction processes that occur within the marine hydrological cycle. In particular, SMOS with its ocean mapping capability provides observations across the world’s largest tropical ocean fresh pool regions, and we discuss from intraseasonal to interannual precipitation impacts as well as large-scale river runoff from the Amazon–Orinoco and Congo rivers and its offshore advection. Synergistic multi-satellite analyses of these new surface salinity data sets combined with sea surface temperature, dynamical height and currents from altimetry, surface wind, ocean color, rainfall estimates, and in situ observations are shown to yield new freshwater budget insight. Finally, SSS observations from the SMOS and Aquarius/SAC-D sensors are combined to examine the response of the upper ocean to tropical cyclone passage including the potential role that a freshwater-induced upper ocean barrier layer may play in modulating surface cooling and enthalpy flux in tropical cyclone track regions.     

SMOS reveals the signature of Indian Ocean Dipole events

The tropical Indian Ocean experiences an interannual mode of climatic variability, known as the Indian Ocean Dipole (IOD). The signature of this variability in ocean salinity is hypothesized based on modeling and assimilation studies, on account of scanty observations. Soil Moisture and Ocean Salinity (SMOS) satellite has been designed to take up the challenge of sea surface salinity remote sensing. We show that SMOS data can be used to infer the pattern of salinity variability linked with the IOD events. The core of maximum variability is located in the central tropical basin, south of the equator. This region is anomalously salty during the 2010 negative IOD event, and anomalously fresh during the 2011 positive IOD event. The peak-to-peak anomaly exceeds one salinity unit, between late 2010 and late 2011. In conjunction with other observational datasets, SMOS data allow us to draw the salt budget of the area. It turns out that the horizontal advection is the main driver of salinity anomalies. This finding is confirmed by the analysis of the outputs of a numerical model. This study shows that the advent of SMOS makes it feasible the quantitative assessment of the mechanisms of ocean surface salinity variability in the tropical basins, at interannual timescales.     

Validation of a decadal OGCM simulation for the tropical Pacific

An ocean general circulation model is forced with NCEP reanalysis over the 1948–1999 period. The simulated dynamic height and sea level are compared respectively to the dynamic height computed from hydrological data and to the sea level measured by tide gauges in the tropical Pacific. The model is shown to capture important features of the temporal structure of variability in the tide gauge data over the last several decades. However, the comparison reveals a largely artificial trend in the simulation, which consists of a decreasing dynamic height and sea level in the southwest and northwest of the tropical Pacific. Model sensitivity experiments show this trend is controlled by the NCEP surface wind stresses and more precisely by a weakening in the trade winds and a trend in the off-equatorial wind curl, with this trend existing mainly before the mid 1970s. For studies of decadal variability, the simple removal of a linear trend is an inadequate way to solve the problem, due to the inhomogeneities in the data used in reanalysis products and the non-linearity of models.