Quality assessment of spaceborne sea surface salinity observations over the northern North Atlantic

Abstract

SMOS SSS fields show a temperature-dependent negative SSS bias of up to 22 g/kg for temperatures <5 C. Removing this bias significantly reduces the differences to independent ship-based thermosalinograph data but potentially corrects simultaneously also other effects not related to temperature, such as land contamination or radio frequency interference (RFI). The resulting time-mean bias, averaged over the study area, amounts to 0.1 g/kg. A respective correction applied previously by the Jet Propulsion Laboratory to the Aquarius data is shown here to have successfully removed an SST-related bias in our study area. For both missions, resulting spatial structures of SSS variability agree very well with those available from an eddy-resolving numerical simulation and from Argo data and, additionally they also show substantial salinity changes on monthly and seasonal time scales. Some fraction of the root-mean-square difference between in situ, and SMOS and Aquarius data (approximately 0.9 g/kg) can be attributed to short time scale ocean processes, notably at the Greenland shelf, and could represent associated sampling errors there.

Pacific Ocean surface freshwater variability underneath the double ITCZ as seen by satellite sea surface salinity retrievals

“…In contrast, Köhler et al . [] investigated the quality of SMOS and Aquarius data over cold water in the North Atlantic to assess their data quality under a worst case scenario.…”

Mechanisms of Mixed‐Layer Salinity Seasonal Variability in the Indian Ocean

“…Various studies (e.g., Banks et al, ; Köhler et al, ; Tong et al, ) showed that satellite‐retrieved SSS is corrupted by systematic errors coming from ice and land contamination (Font et al, ; Gabarro et al, ; Oliva et al, ), radio frequency interference (RFI; Oliva et al, ), seasonal biases, or latitudinal biases mainly due to thermal drift of the instrument (e.g., Boutin et al, ; Gourrion et al, ; Reul et al, ). Those biases are difficult to characterize and several institutions provide satellite‐retrieved SSS products based on different correction methods (e.g., Kolodziejczyk et al, ).…”

Regime Changes in Global Sea Surface Salinity Trend

“…The recently available SMOS (Soil Moisture and Ocean Salinity) satellite [25,26] provides sea surface salinity data with sufficient spatial resolution (1/4 • ) to characterize global [27] and regional (e.g., Amazon: [28]; North Atlantic SSS maximum: [29,30]; Gulf Stream: [31]; northern North Atlantic: [32]) features. Recently, SMOS data have been used to study salinity variability in the Atlantic [33], the signature of La Niña in the tropical Pacific Ocean [34] and even create surface temperature/salinity (T/S) diagrams [35].…”

“…The SMOS satellite data exhibited deficiencies near coastal areas and in high latitudes [29,32,37,38]. To prevent the introduction of bogus features, those data were removed from the analysis.…”