Global-scale surface salinity change since the 1870s.Implications for the global hydrological cycle

2021 ◽  
Author(s):  
W John Gould ◽  
Stuart Cunningham
Keyword(s):  
Hydrological Cycle ◽  
Surface Air Temperature ◽  
Global Scale ◽  
Rate Of Change ◽  
Sea Surface ◽  
Salinity Change ◽  
Surface Salinity ◽  
Global Hydrological Cycle ◽  
Global Surface ◽  
Scale Surface

<p>Based on the first ever combined analysis of observations from the round-the-world voyages of HMS Challenger and SMS Gazelle in the 1870s, early in the industrial era, this paper shows that the amplification of the global surface salinity signal (saline areas becoming saltier and fresh areas fresher) has increased by 63±5% since the 1950s compared to the period 1870s to 1950s. Other analyses of regional salinity change between the mid-20<sup>th</sup> century and present day have linked this amplification to anthropogenically-driven strengthening of the global hydrological cycle in line with increasing global temperatures. Our results show that the rate of change has indeed accelerated but more closely in line with changes in sea surface temperature than with surface air temperature over almost 150 years. This is the first global-scale analysis of salinities from these two expeditions in the 1870s and the first observational evidence of changes in the global hydrological cycle since the late 19<sup>th</sup> century.</p>

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 Global air temperature variability independent of sea-surface temperature influences

2012 ◽  
Vol 37 (1) ◽  
pp. 29-35
Author(s):  
Andrew C. Comrie ◽  
Gregory J. McCabe
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Recent Literature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Sea Surface ◽  
Sst Variability ◽  
Global Surface

Mean global surface air temperature (SAT) and sea surface temperature (SST) display substantial variability on timescales ranging from annual to multi-decadal. We review the key recent literature on connections between global SAT and SST variability. Although individual ocean influences on SAT have been recognized, the combined contributions of worldwide SST variability on the global SAT signal have not been clearly identified in observed data. We analyze these relations using principal components of detrended SST, and find that removing the underlying combined annual, decadal, and multi-decadal SST variability from the SAT time series reveals a nearly monotonic global warming trend in SAT since about 1900.

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 Nine years of SMOS Sea Surface Salinity global maps at the Barcelona Expert Center

2020 ◽  
Author(s):  
Estrella Olmedo ◽  
Cristina González-Haro ◽  
Nina Hoareau ◽  
Marta Umbert ◽  
Verónica González-Gambau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Quality Assessment ◽  
Global Scale ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Low Resolution ◽  
Surface Salinity ◽  
Resolution Level ◽  
Level 3 ◽  
Expert Center

Abstract. After more than 10 years in orbit, the Soil Moisture and Ocean Salinity (SMOS) European mission is still a unique, highquality instrument for providing Soil Moisture over land and Sea Surface Salinity (SSS) over the oceans. At the Barcelona Expert Center (BEC), a new reprocessing of 9 years (2011–2019) of global SMOS SSS maps has been generated. This work presents the algorithms used in the generation of BEC global SMOS SSS product v2.0, as well as an extensive quality assessment. Three SMOS SSS fields are distributed: a high-resolution level 3 product (with https://doi.org/10.20350/digitalCSIC/12601 (Olmedo et al., 2020a)) consisting of a binned SSS in 9-day maps at 0.25 × 0.25°; a low-resolution level 3 SSS computed from the binned salinity by applying a smoothening spatial window of 50-km radius; and a level 4 SSS (with https://doi.org/10.20350/digitalCSIC/12600 (Olmedo et al., 2020b)) consisting of daily, 0.05 × 0.05° maps that are computed by multifractal fusion with Sea Surface Temperature maps. For the validation of BEC SSS products, we have applied a battery of tests aiming at the assessment of quality of the products both in value and in structure. First, we have compared BEC SSS products with near-to-surface salinity measurements provided by Argo floats. Secondly, we have assessed the geophysical consistency of the products characterized by singularity analysis, and also the effective spatial resolutions are estimated by means of Power Density Spectra and Singularity Density Spectra. Finally, we have calculated full maps of SSS errors by using Correlated Triple Collocation. We have compared the performance of BEC SMOS product with other satellite SSS and reanalysis products. The main outcomes of this quality assessment are: i) the bias between BEC SMOS and Argo salinity is lower than 0.02 psu at global scale, while the standard deviation of their difference is lower than 0.34 and 0.27 psu for the high and low resolution level 3 fields (respectively) and 0.24 psu for the level 4 salinity; ii) the effective spatial resolution is around 40 km for all SSS products and regions; and iii) BEC SMOS level 4 product is globally the one with the lowest salinity error, while BEC SMOS low-resolution level 3 more accurate in regions strongly affected by rainfall and continental freshwater discharges.

scholarly journals An assessment of climate state reconstructions obtained using particle filtering methods

2013 ◽  
Vol 9 (1) ◽  
pp. 43-74
Author(s):  
S. Dubinkina ◽  
H. Goosse
Keyword(s):  
Data Assimilation ◽  
Particle Filter ◽  
Air Temperature ◽  
Particle Filtering ◽  
Climate Model ◽  
Initial Conditions ◽  
Surface Air Temperature ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

Abstract. In an idealized framework, we assess reconstructions of the climate state of the Southern Hemisphere during the past 150 yr using the climate model of intermediate complexity LOVECLIM and three data-assimilation methods: a nudging, a particle filter with sequential importance resampling, and an extremely efficient particle filter. The methods constrain the model by pseudo-observations of surface air temperature anomalies obtained from a twin experiment using the same model but different initial conditions. The net of the pseudo-observations is chosen to be either dense (when the pseudo-observations are given at every grid cell of the model) or sparse (when the pseudo-observations are given at the same locations as the dataset of instrumental surface temperature records HADCRUT3). All three data-assimilation methods provide with good estimations of surface air temperature and of sea ice concentration, with the extremely efficient particle filter having the best performance. When reconstructing variables that are not directly linked to the pseudo-observations of surface air temperature as atmospheric circulation and sea surface salinity, the performance of the particle filters is weaker but still satisfactory for many applications. Sea surface salinity reconstructed by the nudging, however, exhibits a patterns opposite to the pseudo-observations, which is due to a spurious impact of the nudging on the ocean mixing.

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 Fifty-Year Trends in Global Ocean Salinities and Their Relationship to Broad-Scale Warming

2010 ◽  
Vol 23 (16) ◽  
pp. 4342-4362 ◽  
Author(s):  
Paul J. Durack ◽  
Susan E. Wijffels
Keyword(s):  
Hydrological Cycle ◽  
Southern Oscillation ◽  
Global Ocean ◽  
Mean Flow ◽  
Salinity Field ◽  
Surface Warming ◽  
Salinity Changes ◽  
Global Hydrological Cycle ◽  
Scale Surface ◽  
Broad Scale

Abstract Using over 1.6 million profiles of salinity, potential temperature, and neutral density from historical archives and the international Argo Program, this study develops the three-dimensional field of multidecadal linear change for ocean-state properties. The period of analysis extends from 1950 to 2008, taking care to minimize the aliasing associated with the seasonal and major global El Niño–Southern Oscillation modes. Large, robust, and spatially coherent multidecadal linear trends in salinity to 2000-dbar depth are found. Salinity increases at the sea surface are found in evaporation-dominated regions and freshening in precipitation-dominated regions, with the spatial pattern of change strongly resembling that of the mean salinity field, consistent with an amplification of the global hydrological cycle. Subsurface salinity changes on pressure surfaces are attributable to both isopycnal heave and real water-mass modification of the temperature–salinity relationship. Subduction and circulation by the ocean’s mean flow of surface salinity and temperature anomalies appear to account for most regional subsurface salinity changes on isopycnals. Broad-scale surface warming and the associated poleward migration of isopycnal outcrops drive a clear and repeating pattern of subsurface isopycnal salinity change in each independent ocean basin. Qualitatively, the observed global multidecadal salinity changes are thus consonant with both broad-scale surface warming and the amplification of the global hydrological cycle.

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 An assessment of particle filtering methods and nudging for climate state reconstructions

2013 ◽  
Vol 9 (3) ◽  
pp. 1141-1152 ◽  
Author(s):  
S. Dubinkina ◽  
H. Goosse
Keyword(s):  
Data Assimilation ◽  
Particle Filter ◽  
Air Temperature ◽  
Particle Filtering ◽  
Climate Model ◽  
Initial Conditions ◽  
Surface Air Temperature ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

Abstract. Using the climate model of intermediate complexity LOVECLIM in an idealised framework, we assess three data-assimilation methods for reconstructing the climate state. The methods are a nudging, a particle filter with sequential importance resampling, and a nudging proposal particle filter and the test case corresponds to the climate of the high latitudes of the Southern Hemisphere during the past 150 yr. The data-assimilation methods constrain the model by pseudo-observations of surface air temperature anomalies obtained from the same model, but different initial conditions. All three data-assimilation methods provide with good estimations of surface air temperature and of sea ice concentration, with the nudging proposal particle filter obtaining the highest correlations with the pseudo-observations. When reconstructing variables that are not directly linked to the pseudo-observations such as atmospheric circulation and sea surface salinity, the particle filters have equivalent performance and their correlations are smaller than for surface air temperature reconstructions but still satisfactory for many applications. The nudging, on the contrary, obtains sea surface salinity patterns that are opposite to the pseudo-observations, which is due to a spurious impact of the nudging on vertical exchanges in the ocean.

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