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Monthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1° × 1° grid in the Atlantic Ocean between 30°S and 50°N in the 1970–2016 period in an update of the dataset of Reverdin et al. Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20° and 50°N in 5° × 5° boxes during the 1993–2016 period, both locally and remotely following the displacements of the deep mixed layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about one-half of the boxes, notably in the northeast and southeast, whereas little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, whereas only a first SST reemergence is seen. An oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies. [ABSTRACT FROM AUTHOR]

Ships of opportunity are a frequently used platform in surface ocean carbon observations and estimating the annual ocean carbon sink. For understanding the drivers behind changes in the ocean carbon system, oxygen measurements alongside the carbon dioxide measurements can be a valuable tool. We developed an in‐air calibration system for oxygen optodes in underway systems. The regular measurements of atmospheric oxygen enable us to correct for sensor drift and biofouling. This new system can help to obtain reliable oxygen data from underway applications, especially if the vessel is not easily accessible and a frequent recalibration of the optode is not feasible. [ABSTRACT FROM AUTHOR]

Variability of surface water masses of the Laptev and the East Siberian seas in August–September 2018 is studied using in situ and satellite data. In situ data were collected during the ARKTIKA-2018 expedition and then complemented with satellite-derived sea surface temperature (SST), salinity (SSS), sea surface height, wind speed, and sea ice concentration. The estimation of SSS fields is challenging in high-latitude regions, and the precision of soil moisture and ocean salinity (SMOS) SSS retrieval is improved by applying a threshold on SSS weekly error. For the first time in this region, the validity of DMI (Danish Meteorological Institute) SST and SMOS SSS products is thoroughly studied using ARKTIKA-2018 expedition continuous thermosalinograph measurements and conductivity–temperature–depth (CTD) casts. They are found to be adequate to describe large surface gradients in this region. Surface gradients and mixing of the river and the sea water in the ice-free and ice-covered areas are described with a special attention to the marginal ice zone at a synoptic scale. We suggest that the freshwater is pushed northward, close to the marginal ice zone (MIZ) and under the sea ice, which is confirmed by the oxygen isotope analysis. The SST-SSS diagram based on satellite estimates shows the possibility of investigating the surface water mass transformation at a synoptic scale and reveals the presence of river water on the shelf of the East Siberian Sea. The Ekman transport is calculated to better understand the pathway of surface water displacement on the shelf and beyond. [ABSTRACT FROM AUTHOR]

We present the Copernicus in situ ocean dataset of temperature and salinity (version 5.2). Ocean subsurface sampling varied widely from 1950 to 2017 as a result of changes in instrument technology and the development of in situ observational networks (in particular, tropical moorings for the Argo program). Thus, global ocean temperature data coverage on an annual basis grew from 10 % in 1950 (30 % for the North Atlantic basin) to 25 % in 2000 (60 % for the North Atlantic basin) and reached a plateau exceeding 80 % (95 % for the North Atlantic Ocean) after the deployment of the Argo program. The average depth reached by the profiles also increased from 1950 to 2017. The validation framework is presented, and an objective analysis-based method is developed to assess the quality of the dataset validation process. Objective analyses (OAs) of the ocean variability are calculated without taking into account the data quality flags (raw dataset OA), with the near-real-time quality flags (NRT dataset OA), and with the delayed-time-mode quality flags (CORA dataset OA). The comparison of the objective analysis variability shows that the near-real-time dataset managed to detect and to flag most of the large measurement errors, reducing the analysis error bar compared to the raw dataset error bar. It also shows that the ocean variability of the delayed-time-mode validated dataset is almost exempt from random-error-induced variability. [ABSTRACT FROM AUTHOR]

Understanding what controls the water vapor isotopic composition of the sub-cloud layer (SCL) over tropical oceans (δD0) is a first step towards understanding the water vapor isotopic composition everywhere in the troposphere. We propose an analytical model to predict δD0 motivated by the hypothesis that the altitude from which the free tropospheric air originates (zorig) is an important factor: when the air mixing into the SCL is lower in altitude, it is generally moister, and thus it depletes the SCL more efficiently. We extend previous simple box models of the SCL by prescribing the shape of δD vertical profiles as a function of humidity profiles and by accounting for rain evaporation and horizontal advection effects. The model relies on the assumption that δD profiles are steeper than mixing lines, and that the SCL is at steady state, restricting its applications to timescales longer than daily. In the model, δD0 is expressed as a function of zorig , humidity and temperature profiles, surface conditions, a parameter describing the steepness of the δD vertical gradient, and a few parameters describing rain evaporation and horizontal advection effects. We show that δD0 does not depend on the intensity of entrainment, in contrast to several previous studies that had hoped that δD0 measurements could help estimate this quantity. Based on an isotope-enabled general circulation model simulation, we show that δD0 variations are mainly controlled by mid-tropospheric depletion and rain evaporation in ascending regions and by sea surface temperature and zorig in subsiding regions. In turn, could δD0 measurements help estimate zorig and thus discriminate between different mixing processes? For such isotope-based estimates of zorig to be useful, we would need a precision of a few hundred meters in deep convective regions and smaller than 20 m in stratocumulus regions. To reach this target, we would need daily measurements of δD in the mid-troposphere and accurate measurements of δD0 (accuracy down to 0.1 ‰ in the case of stratocumulus clouds, which is currently difficult to obtain). We would also need information on the horizontal distribution of δD to account for horizontal advection effects, and full δD profiles to quantify the uncertainty associated with the assumed shape for δD profiles. Finally, rain evaporation is an issue in all regimes, even in stratocumulus clouds. Innovative techniques would need to be developed to quantify this effect from observations. [ABSTRACT FROM AUTHOR]

We present a binned annual product (BINS) of sea surface temperature (SST), sea surface salinity (SSS), and sea surface density (SSD) observations for 1896-2015 of the subpolar North Atlantic between 40° N and 70° N, mostly excluding the shelf areas. The product of bin averages over spatial scales on the order of 200 to 500 km, reproducing most of the interannual variability in different time series covering at least the last three decades or of the along-track ship monitoring. Comparisons with other SSS and SST gridded products available since 1950 suggest that BINS captures the large decadal to multidecadal variability. Comparison with the HadSST3 SST product since 1896 also indicates that the decadal and multidecadal variability is usually well-reproduced, with small differences in long-term trends or in areas with marginal data coverage in either of the two products. Outside of the Labrador Sea and Greenland margins, interannual variability is rather similar in different seasons. Variability at periods longer than 15 years is a large part of the total interannual variability, both for SST and SSS, except possibly in the south-western part of the domain. Variability in SST and SSS increases towards the west, with the contribution of salinity variability to density dominating that of temperature in the western Atlantic, except close to the Gulf Stream and North Atlantic Current in the southwest area. Weaker variability and larger relative temperature contributions to density changes are found in the eastern part of the gyre and south of Iceland. [ABSTRACT FROM AUTHOR]

We present a binned product of sea surface temperature, sea surface salinity, and sea surface density data in the North Atlantic subpolar gyre from 1993 to 2017 that resolves seasonal variability along specific ship routes (https://doi.org/10.6096/SSS-BIN-NASG). The characteristics of this product are described and validated through comparisons to other monthly products. Data presented in this work were collected in regions crossed by two predetermined ship transects, between Denmark and western Greenland (AX01) and between Iceland, Newfoundland, and the northeastern USA (AX02). The data were binned along a selected usable transect. The analysis and the strong correlation between successive seasons indicate that in large parts of the subpolar gyre, the binning approach is robust and resolves the seasonal timescales, in particular after 1997 and in regions away from the continental shelf. Prior to 2002, there was no winter sampling over theWest Greenland Shelf. Variability in sea surface salinity increases towards Newfoundland south of 54° N, as well as in the western Iceland Basin along 59° N. Variability in sea surface temperature presents less spatial structure with an increase westward and towards Newfoundland. The contribution of temperature variability to density dominates in the eastern part of the gyre, whereas the contribution of salinity variability dominates in the southwestern part along AX02. [ABSTRACT FROM AUTHOR]

We present a binned product of sea surface temperature, sea surface salinity and sea surface density data in the North Atlantic subpolar gyre for the 1993-2017 that resolves seasonal variability along specific ship routes (doi:10.6096/SSS-BIN-NASG). The characteristics of this product are described and validated through comparisons to other monthly products. Data presented in this work was collected in regions crossed by two predetermined ship transects, between Denmark and western Greenland (AX01) and between Iceland, Newfoundland, and the northeastern USA (AX02). The analysis and the strong correlation between successive seasons indicate that in large parts of the subpolar gyre, the binning approach is robust and resolves the seasonal time scales, in particular after 1997 and in regions away from the continental shelf. Prior to 2002, there was no winter sampling over the west Greenland shelf. Variability in sea surface salinity increases towards Newfoundland south of 54°N, as well as in the western Iceland Basin along 59°N. Variability in sea surface temperature presents less spatial structure with an increase westward and towards Newfoundland. The contribution of temperature variability to density dominates in the eastern part of the gyre, whereas the contribution of salinity variability dominates in the southwestern part along AX02. [ABSTRACT FROM AUTHOR]

Detailed observations of the diurnal jet, a surface intensification of the wind-driven current associated with the diurnal cycle of sea surface temperature (SST), were obtained during August and September 2012 in the subtropical Atlantic. A diurnal increase in SST of 0.2° to 0.5°C was observed, which corresponded to a diurnal jet of 0.15 m s−1. The increase in near-surface stratification limits the vertical diffusion of the wind stress, which in turn increases the near-surface shear. While the stratification decreased the turbulent dissipation rate ε below the depth of the diurnal jet, there was an observed increase in ε within the diurnal jet. The diurnal jet was observed to increase the near-surface shear by a factor of 5, which coincided with enhanced values of ε. The diurnal evolution of the Richardson number, which is an indicator of shear instability, is less than 1, suggesting that shear instability may contribute to near-surface turbulence. While the increased stratification due to the diurnal heating limits the depth of the momentum flux due to the wind, shear instability provides an additional source of turbulence that interacts with the enhanced shear of the diurnal jet to increase ε within this shallow layer. [ABSTRACT FROM AUTHOR]

The frontal activity in coastal regions remains a research field where a large number of open questions needs to be addressed to quantify the potential impact of these processes on dependent systems (e.g. biogeochemical activity). Spatial and seasonal distributions of Sea Surface Temperature (SST) fronts (∼1–100 km) in the vicinity of main French rivers, Gironde and Loire, are explored over the continental shelf North of 45°N in the Bay of Biscay. A high resolution (1 km spatial and daily temporal resolutions) dataset of 11 years' (2003–2013) remotely sensed SST by MODIS sensor onboard Aqua and Terra satellites has been investigated and compared with coastal numerical model experiments. The detection and characterization fronts with fluctuating amplitudes is achieved through the Singularity Analysis (i.e. the process of calculating the degree of regularity or irregularity of a function at each point in a domain). Seasonality of frontal activity in the Bay of Biscay is then described based on the long-term satellite SST archive and coastal operational model simulations. The identified hot spots of higher frontal occurrences correspond on one hand to previously observed features (e.g. tidal fronts) but also reveal new features. These are investigated to identify fine-scale dynamical drivers. In winter, density fronts are prominent in a coastal strip where freshwater influence is important. In spring, this strip diminishes as plumes detach from the coast, while tidal fronts become apparent in other regions. In summer, tidal fronts in Ushant region and internal wave activity along the shelf break dominate. In autumn, coastal density fronts due to freshwater inputs reappear as these inputs increase, and reduced stratification causes a weakening of the Ushant and shelf break fronts. Additional information and an effort to dynamically interpret these fronts, based on a systematic investigation of the whole seasonal cycle and including modeling insights from coastal operational oceanography, complement the description of frontal activity in the Bay of Biscay. [ABSTRACT FROM AUTHOR]

Sea Surface Salinity (SSS) acquired by the Soil Moisture and Ocean Salinity (SMOS) satellite mission are subject to systematic errors originating from various non-geophysical contaminations such as land contamination. These systematic errors reach more than 2 pss in some regions close to the land with very strong spatial gradients according to the coast orientation and the across-track position within the satellite swath. An empirical method to estimate and correct the time independent systematic errors from resampled quasi L2 SMOS SSS is presented. The method is based on self-consistency hypothesis of long term (July 2010–June 2014) variability of SMOS SSS among SMOS dwell-lines and orbit orientation (ascending and descending). The bias correction is performed by first adjusting SSS relative variations among dwell-lines and orbits orientation and then by determining a mean correction over four years. A reference time series of SSS and the associated relative systematic error for each dwell-line and orbit orientation is estimated using a least square approach. Then, the 4-year mean value of corrected SMOS SSS is adjusted relative to a 4-year mean in situ data climatology. Four years of salinity maps mitigated from systematic errors are presented. Independent validation using in situ thermosalinograph SSS from ships of opportunity is presented. The new SMOS bias corrected SSS over the global ocean shows an improvement of 32% of the RMSD. [ABSTRACT FROM AUTHOR]

Since 2010, the Soil Moisture and Ocean Salinity (SMOS) satellite mission monitors the earth emission at L-Band. It provides the longest time series of Sea Surface Salinity (SSS) from space over the global ocean. However, the SSS retrieval at high latitudes is a challenge because of the low sensitivity L-Band radiometric measurements to SSS in cold waters and to the contamination of SMOS measurements by the vicinity of continents, of sea ice and of Radio Frequency Interferences. In this paper, we assess the quality of weekly SSS fields derived from swath-ordered instantaneous SMOS SSS (so called Level 2) distributed by the European Space Agency. These products are filtered according to new criteria. We use the pseudo-dielectric constant retrieved from SMOS brightness temperatures to filter SSS pixels polluted by sea ice. We identify that the dielectric constant model and the sea surface temperature auxiliary parameter used as prior information in the SMOS SSS retrieval induce significant systematic errors at low temperatures. We propose a novel empirical correction to mitigate those sources of errors at high latitudes. Comparisons with in-situ measurements ranging from 1 to 11 m depths spotlight huge vertical stratification in fresh regions. This emphasizes the need to consider in-situ salinity as close as possible to the sea surface when validating L-band radiometric SSS which are representative of the first top centimeter. SSS Standard deviation of differences (STDD) between weekly SMOS SSS and in-situ near surface salinity significantly decrease after applying the SSS correction, from 1.46 pss to 1.28 pss. The correlation between new SMOS SSS and in-situ near surface salinity reaches 0.94. SMOS estimates better capture SSS variability in the Arctic Ocean in comparison to TOPAZ reanalysis (STDD between TOPAZ and in-situ SSS = 1.86 pss), particularly in river plumes with very large SSS spatial gradients. Unlabelled Image • Large signal to noise ratio of SMOS salinity in fresh and variable Arctic Seas. • Near surface vertical stratification critical for SMOS salinity validation. • Improved sea ice filtering using SMOS pseudo dielectric constant. • Improved SMOS salinity considering SST and dielectric constant uncertainties. [ABSTRACT FROM AUTHOR]