scholarly journals Planktonic foraminiferal spine versus shell carbonate Na incorporation in relation to salinity

2019 ◽  
Vol 16 (6) ◽  
pp. 1147-1165 ◽  
Author(s):  
Eveline M. Mezger ◽  
Lennart J. de Nooijer ◽  
Jacqueline Bertlich ◽  
Jelle Bijma ◽  
Dirk Nürnberg ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Culture Studies ◽  
Global Circulation ◽  
Relative Contribution ◽  
Icp Ms ◽  
Shell Chemistry ◽  
Shell Carbonate ◽  
Micro Analysis

Abstract. Sea surface salinity is one of the most important parameters to reconstruct in paleoclimatology, reflecting amongst other things the hydrological cycle, paleodensity, ice volume, and regional and global circulation of water masses. Recent culture studies and a Red Sea field study revealed a significant positive relation between salinity and Na incorporation within benthic and planktonic foraminiferal shells. However, these studies reported varying partitioning of Na between and within the same species. The latter could be associated with ontogenetic variations, most likely spine loss. Varying Na concentrations were observed in different parts of foraminiferal shells, with spines and regions close to the primary organic sheet being especially enriched in Na. In this study, we unravel the Na composition of different components of the planktonic foraminiferal shell wall using electron probe micro-analysis (EPMA) and solution ICP-MS. A model is presented to interpret EPMA data for spines and spine bases to quantitatively assess differences in composition and contribution to whole-shell Na∕Ca signals. The same model can also be applied to other spatial inhomogeneities observed in foraminiferal shell chemistry, like elemental (e.g., Mg, Na, S) banding and/or hotspots. The relative contribution of shell carbonate, organic linings, spines and spine bases to whole-shell Na chemistry is considered quantitatively. This study shows that whereas the high Na areas may be susceptible to taphonomic alterations, the Na chemistry of the shell itself seems relatively robust. Comparing both shell and spine Na∕Ca values with salinity shows that shell chemistry records salinity, albeit with a very modest slope.

scholarly journals Planktonic foraminiferal spine versus shell carbonate Na incorporation in relation to salinity

2018 ◽  
Author(s):  
Eveline M. Mezger ◽  
Lennart J. de Nooijer ◽  
Jacqueline Bertlich ◽  
Jelle Bijma ◽  
Dirk Nürnberg ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Culture Studies ◽  
Global Circulation ◽  
Relative Contribution ◽  
Icp Ms ◽  
Shell Chemistry ◽  
Shell Carbonate ◽  
Micro Analysis

Abstract. Sea surface salinity is one of the most important parameters to reconstruct in paleoclimatology, reflecting amongst others the hydrological cycle, paleo-density, ice volume, and regional and global circulation of water masses. Recent culture studies and a Red Sea field study revealed a significant positive relation between salinity and Na incorporation within benthic and planktonic foraminiferal shells. However, these studies reported varying partitioning of Na between and within the same species. The latter could be associated with ontogenetic variations, most likely spine loss. Varying Na concentrations were observed in different parts of foraminiferal shells, with especially spines and regions close to the primary organic sheet being enriched in Na. In this study, we unravel the Na composition of different components of the planktonic foraminiferal shell wall using Electron Probe Micro Analysis (EPMA) and solution-ICP-MS. A model is presented to interpret EPMA data for spines and spine bases to quantitatively assess differences in composition and contribution to whole shell Na/Ca signals. The same model can also be applied to other spatial inhomogeneities observed in foraminiferal shell chemistry, like elemental (e.g. Mg, Na, S) banding and/or hotspots. The relative contribution of shell calcite, organic linings, spines and spine bases to whole shell Na chemistry is considered quantitatively. This study shows that whereas the high Na areas may be susceptible to taphonomy, the Na chemistry of the shell itself seems relatively robust. Comparing both shell and spine Na/Ca values with salinity shows that shell chemistry records salinity, albeit with a very modest slope.

scholarly journals Global-scale patterns of observed sea surface salinity intensified since the 1870s

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
W. John Gould ◽  
Stuart A. Cunningham
Keyword(s):  
Hydrological Cycle ◽  
Global Scale ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Salinity Change ◽  
Surface Salinity ◽  
Salinity Changes ◽  
Change Pattern ◽  
The World ◽  
Global Mean

AbstractSea surface salinity patterns have intensified between the mid-20th century and present day, with saline areas becoming saltier and fresher areas fresher. This change has been linked to a human-induced strengthening of the global hydrological cycle as global mean surface temperatures rose. Here we analyse salinity observations from the round-the-world voyages of HMS Challenger and SMS Gazelle in the 1870s, early in the industrial era, to reconstruct surface salinity changes since that decade. We find that the amplification of the salinity change pattern between the 1870s and the 1950s was at a rate that was 54 ± 10% lower than the post-1950s rate. The acceleration in salinity pattern amplification over almost 150 years implies that the hydrological cycle would have similarly accelerated over this period.

scholarly journals Comparison of Distributional Statistics of Aquarius and Argo Sea Surface Salinity Measurements

2016 ◽  
Vol 33 (1) ◽  
pp. 103-118 ◽  
Author(s):  
Elizabeth Mannshardt ◽  
Katarina Sucic ◽  
Montserrat Fuentes ◽  
Frederick M. Bingham
Keyword(s):  
Ocean Circulation ◽  
Hydrological Cycle ◽  
Water Cycle ◽  
Ocean Basin ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Time And Space ◽  
Surface Salinity ◽  
Statistical Validation ◽  
Earth’S Climate

AbstractSalinity is an indicator of the interaction between ocean circulation and the global water cycle, which in turn affects the regulation of the earth’s climate. To thoroughly understand sea surface salinity’s connection to processes that define the hydrological cycle, such as surface forcing and ocean mixing, there is need for proper validation of remotely sensed salinity products with independent measurements, beyond central tendencies, across the entire distribution of salinity. Because of its fine spatial and temporal coverage, Aquarius presents an ideal measurement system for fully characterizing the distribution and properties of sea surface salinity. Using the first 33 months of Aquarius, version 3.0, level 2 sea surface salinity data, both central tendencies and distributional quantile characteristics across time and space are investigated, and a statistical validation of Aquarius measurements with Argo in situ observations is conducted. Several aspects are considered, including regional characteristics and temporal agreement, as well as seasonal differences by ocean basin and hemisphere. Regional studies examine the time and space scales of variability through time series comparisons and an analysis of quantile properties. Results indicate that there are significant differences between the tails of their respective distributions, especially the lower tail. The Aquarius data show longer, fatter lower tails, indicating higher probability to sample low-salinity events. There is also evidence of differences in measurement variation between Aquarius and Argo. These results are seen across seasons, ocean basins, hemispheres, and regions.

scholarly journals Near-Surface Salinity Reveals the Oceanic Sources of Moisture for Australian Precipitation through Atmospheric Moisture Transport

2020 ◽  
Vol 33 (15) ◽  
pp. 6707-6730
Author(s):  
Saurabh Rathore ◽  
Nathaniel L. Bindoff ◽  
Caroline C. Ummenhofer ◽  
Helen E. Phillips ◽  
Ming Feng
Keyword(s):  
El Niño ◽  
Moisture Transport ◽  
Hydrological Cycle ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface Salinity ◽  
Atmospheric Moisture ◽  
Surface Salinity ◽  
Near Surface ◽  
Atmospheric Moisture Transport

AbstractThe long-term trend of sea surface salinity (SSS) reveals an intensification of the global hydrological cycle due to human-induced climate change. This study demonstrates that SSS variability can also be used as a measure of terrestrial precipitation on interseasonal to interannual time scales, and to locate the source of moisture. Seasonal composites during El Niño–Southern Oscillation/Indian Ocean dipole (ENSO/IOD) events are used to understand the variations of moisture transport and precipitation over Australia, and their association with SSS variability. As ENSO/IOD events evolve, patterns of positive or negative SSS anomaly emerge in the Indo-Pacific warm pool region and are accompanied by atmospheric moisture transport anomalies toward Australia. During co-occurring La Niña and negative IOD events, salty anomalies around the Maritime Continent (north of Australia) indicate freshwater export and are associated with a significant moisture transport that converges over Australia to create anomalous wet conditions. In contrast, during co-occurring El Niño and positive IOD events, a moisture transport divergence anomaly over Australia results in anomalous dry conditions. The relationship between SSS and atmospheric moisture transport also holds for pure ENSO/IOD events but varies in magnitude and spatial pattern. The significant pattern correlation between the moisture flux divergence and SSS anomaly during the ENSO/IOD events highlights the associated ocean–atmosphere coupling. A case study of the extreme hydroclimatic events of Australia (e.g., the 2010/11 Brisbane flood) demonstrates that the changes in SSS occur before the peak of ENSO/IOD events. This raises the prospect that tracking of SSS variability could aid the prediction of Australian rainfall.

scholarly journals Regime changes in global sea surface salinity trend

2015 ◽  
Vol 12 (3) ◽  
pp. 983-1011 ◽  
Author(s):  
A. L. Aretxabaleta ◽  
K. W. Smith ◽  
J. Ballabrera-Poy
Keyword(s):  
Hydrological Cycle ◽  
Information Criterion ◽  
Gaussian Mixture ◽  
Optimal Number ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Regime Changes ◽  
Hadley Centre ◽  
The Uk

Abstract. Recent studies have shown significant sea surface salinity (SSS) changes at scales ranging from regional to global. In this study, we estimate global salinity means and trends using historical (1950–2014) SSS data from the UK Met. Office Hadley Centre objectively analyzed monthly fields and recent data from the SMOS satellite (2010–2014). We separate the different components (regimes) of the global surface salinity by fitting a Gaussian Mixture Model to the data and using Expectation–Maximization to distinguish the means and trends of the data. The procedure uses a non-subjective method (Bayesian Information Criterion) to extract the optimal number of means and trends. The results show the presence of three separate regimes: Regime A (1950–1990) is characterized by small trend magnitudes; Regime B (1990–2009) exhibited enhanced trends; and Regime C (2009–2014) with significantly larger trend magnitudes. The salinity differences between regime means were around 0.01. The trend acceleration could be related to an enhanced global hydrological cycle or to a change in the sampling methodology.

scholarly journals Statistical Assessment of Sea-Surface Salinity from SMAP: Arabian Sea, Bay of Bengal and a Promising Red Sea Application

2020 ◽  
Vol 12 (3) ◽  
pp. 447 ◽  
Author(s):  
Viviane V. Menezes
Keyword(s):  
Red Sea ◽  
Ocean Circulation ◽  
Bay Of Bengal ◽  
Arabian Sea ◽  
Hydrological Cycle ◽  
North Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
The North

Sea-surface salinity (SSS) is an essential climate variable connected to Earth’s hydrological cycle and a dynamical component of ocean circulation, but its variability is not well-understood. Thanks to Argo floats, and the first decade of salinity remote sensing, this is changing. While satellites can retrieve salinity with some confidence, accuracy is regionally dependent and challenging within 500–1000 km offshore. The present work assesses the first four years of the National Aeronautics and Space Administration’s Soil Moisture Active Passive (SMAP) satellite in the North Indian Ocean. SMAP’s improved spatial resolution, better mitigation for radio-frequency interference, and land contamination make it particularly attractive to study coastal areas. Here, regions of interest are the Bay of Bengal, the Arabian Sea, and the extremely salty Red Sea (the last of which has not yet received attention). Six SMAP products, which include Levels 2 and 3 data, were statistically evaluated against in situ measurements collected by a variety of instruments. SMAP reproduced SSS well in both the Arabian Sea and the Bay of Bengal, and surprisingly well in the Red Sea. Correlations there were 0.81–0.93, and the root-mean-square difference was 0.38–0.67 for Level 3 data.

scholarly journals Satellite and In Situ Salinity: Understanding Near-Surface Stratification and Subfootprint Variability

2016 ◽  
Vol 97 (8) ◽  
pp. 1391-1407 ◽  
Author(s):  
J. Boutin ◽  
Y. Chao ◽  
W. E. Asher ◽  
T. Delcroix ◽  
R. Drucker ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Ocean Dynamics ◽  
Sea Surface Salinity ◽  
Spatial Average ◽  
Surface Salinity ◽  
Near Surface ◽  
In Situ Data ◽  
Microwave Radiometers ◽  
Vertical Gradients

Abstract Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km2. In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.

scholarly journals Matchup Characteristics of Sea Surface Salinity Using a High-Resolution Ocean Model

2021 ◽  
Vol 13 (15) ◽  
pp. 2995
Author(s):  
Frederick M. Bingham ◽  
Severine Fournier ◽  
Susannah Brodnitz ◽  
Karly Ulfsax ◽  
Hong Zhang
Keyword(s):  
High Resolution ◽  
Time Window ◽  
Single Point ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Argo Floats ◽  
Statistical Measures ◽  
Salinity Difference

Sea surface salinity (SSS) satellite measurements are validated using in situ observations usually made by surfacing Argo floats. Validation statistics are computed using matched values of SSS from satellites and floats. This study explores how the matchup process is done using a high-resolution numerical ocean model, the MITgcm. One year of model output is sampled as if the Aquarius and Soil Moisture Active Passive (SMAP) satellites flew over it and Argo floats popped up into it. Statistical measures of mismatch between satellite and float are computed, RMS difference (RMSD) and bias. The bias is small, less than 0.002 in absolute value, but negative with float values being greater than satellites. RMSD is computed using an “all salinity difference” method that averages level 2 satellite observations within a given time and space window for comparison with Argo floats. RMSD values range from 0.08 to 0.18 depending on the space–time window and the satellite. This range gives an estimate of the representation error inherent in comparing single point Argo floats to area-average satellite values. The study has implications for future SSS satellite missions and the need to specify how errors are computed to gauge the total accuracy of retrieved SSS values.

scholarly journals Sea Surface Salinity Response to Tropical Cyclones Based on Satellite Observations

2021 ◽  
Vol 13 (3) ◽  
pp. 420
Author(s):  
Jingru Sun ◽  
Gabriel Vecchi ◽  
Brian Soden
Keyword(s):  
Tropical Cyclones ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Translation Speed ◽  
Salinity Stratification ◽  
Left Hand ◽  
In Situ Data ◽  
Salinity Response ◽  
The Right

Multi-year records of satellite remote sensing of sea surface salinity (SSS) provide an opportunity to investigate the climatological characteristics of the SSS response to tropical cyclones (TCs). In this study, the influence of TC winds, rainfall and preexisting ocean stratification on SSS evolution is examined with multiple satellite-based and in-situ data. Global storm-centered composites indicate that TCs act to initially freshen the ocean surface (due to precipitation), and subsequently salinify the surface, largely through vertical ocean processes (mixing and upwelling), although regional hydrography can lead to local departure from this behavior. On average, on the day a TC passes, a strong SSS decrease is observed. The fresh anomaly is subsequently replaced by a net surface salinification, which persists for weeks. This salinification is larger on the right (left)-hand side of the storm motion in the Northern (Southern) Hemisphere, consistent with the location of stronger turbulent mixing. The influence of TC intensity and translation speed on the ocean response is also examined. Despite having greater precipitation, stronger TCs tend to produce longer-lasting, stronger and deeper salinification especially on the right-hand side of the storm motion. Faster moving TCs are found to have slightly weaker freshening with larger area coverage during the passage, but comparable salinification after the passage. The ocean haline response in four basins with different climatological salinity stratification reveals a significant impact of vertical stratification on the salinity response during and after the passage of TCs.

scholarly journals Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models

2021 ◽  
Vol 13 (5) ◽  
pp. 831
Author(s):  
Jorge Vazquez-Cuervo ◽  
Chelle Gentemann ◽  
Wenqing Tang ◽  
Dustin Carroll ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Future Research ◽  
Surface Salinity ◽  
Cold Temperatures ◽  
Yukon River ◽  
Arctic Sea ◽  
The Arctic Ocean

The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

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