How Salty Is the Global Ocean: Weighting It All or Tasting It a Sip at a Time?

2020 ◽  
Author(s):  
Rui Ponte ◽  
Qiang Sun ◽  
Chao Liu ◽  
Xinfeng Liang
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Hydrological Cycle ◽  
Global Ocean ◽  
Data Quality Control ◽  
Argo Data ◽  
Terrestrial Water ◽  
Control Procedures ◽  
Global Mean Sea Level

<div class="page" title="Page 1"> <div class="section"> <div class="layoutArea"> <div class="column"> <p>Global ocean mean salinity <em>S </em>is a key indicator of the Earth's hydrological cycle and the exchanges of freshwater between the terrestrial water and ice reservoirs and the ocean. We explore two different ways of determining how salty the ocean is: (1) use in situ salinity measurements to taste the ocean a sip at a time and obtain a sample average; (2) use space gravimetry to weigh the whole ocean including sea-ice, and then separate sea-ice effects to infer changes in liquid freshwater content and thus <em>S</em>. Focusing on the 2005-2019 period, we assess monthly series of <em>S </em>derived from five different in situ gridded products, based mostly but not exclusively on Argo data, versus a series obtained from GRACE and GRACE Follow-On data and available sea ice mass estimates.</p> <p>There is little consistency in <em>S </em>series from the two methods for all time scales examined (seasonal, interannual, long-term trend). In situ series show larger variability, particularly at the longest scales, and are somewhat incoherent with the GRACE-derived series. In addition, there are wide spread differences among all the in situ <em>S </em>series, which denote their considerable sensitivity to choice of data, quality control procedures, and mapping methods. Results also suggest that in situ <em>S </em>values are prone to systematic biases, with most series showing increases after around 2014 that are equivalent to a drop in barystatic sea level of tens of centimeters! Estimates derived from GRACE are much smaller in magnitude and consistent with contributions of freshwater to the global mean sea level budgets, and they are thus more reliable than in situ-based <em>S </em>estimates. The existence of GRACE-derived estimates can serve as a consistency check on in situ measurements, revealing potential unknown biases and providing a way to cross-calibrate the latter data.</p> </div> </div> </div> </div>

The Copernicus global 1/12° oceanic and sea ice reanalysis

2021 ◽  
Author(s):  
Jean-Michel Lellouche ◽  
Romain Bourdalle-Badie ◽  
Eric Greiner ◽  
Gilles Garric ◽  
Angelique Melet ◽  
...  
Keyword(s):  
Sea Ice ◽  
Real Time ◽  
Sea Level ◽  
Observation System ◽  
Small Scale ◽  
Free Access ◽  
In Situ Observation ◽  
Seasonal Forecasts ◽  
Concentration Data

<p>The GLORYS12V1 system is a global eddy-resolving physical ocean and sea ice reanalysis at 1/12° resolution covering the 1993-present altimetry period, designed and implemented in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). All the essential ocean physical variables from this reanalysis are available with free access through the CMEMS data portal.</p><p>The GLORYS12V1 reanalysis is based on the current CMEMS global real-time forecasting system, apart from a few specificities that are detailed in this manuscript. The model component is the NEMO platform driven at the surface by atmospheric conditions from the ECMWF ERA-Interim reanalysis. Ocean observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter sea level anomaly, satellite sea surface temperature and sea ice concentration data and in situ temperature and salinity (T/S) vertical profiles are jointly assimilated. A 3D-VAR scheme provides an additional correction for the slowly-evolving large-scale biases in temperature and salinity.</p><p>The performance of the reanalysis is first addressed in the space of the assimilated observations and shows a clear dependency on the time-dependent in situ observation system, which is intrinsic to most reanalyses. The general assessment of GLORYS12V1 highlights a level of performance at the state-of-the-art and the reliability of the system to correctly capture the main expected climatic interannual variability signals for ocean and sea ice, the general circulation and the inter-basins exchanges. In terms of trends, GLORYS12V1 shows a higher than observed  warming trend together with a lower than observed global mean sea level rise.</p><p>Comparisons made with an experiment carried out on the same platform without assimilation show the benefit of data assimilation in controlling water masses properties and their low frequency variability. Examination of the deep signals below 2000 m depth shows that the reanalysis does not suffer from artificial signals even in the pre-Argo period.</p><p>Moreover, GLORYS12V1 represents particularly well the small-scale variability of surface dynamics and compares well with independent (non-assimilated) data. Comparisons made with a twin experiment carried out at ¼° resolution allows characterizing and quantifying the strengthened contribution of the 1/12° resolution onto the downscaled dynamics.</p><p>In conclusion, GLORYS12V1 provides a reliable physical ocean state for climate variability and supports applications such as seasonal forecasts. In addition, this reanalysis has strong assets to serve regional applications and should provide relevant physical conditions for applications such as marine biogeochemistry. In a near future, GLORYS12V1 will be maintained to be as close as possible to real time and could therefore provide a relevant reference statistical framework for many operational applications.</p>

scholarly journals The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 779-808 ◽  
Author(s):  
Hao Zuo ◽  
Magdalena Alonso Balmaseda ◽  
Steffen Tietsche ◽  
Kristian Mogensen ◽  
Michael Mayer
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Global Ocean ◽  
Full Description ◽  
Data Sets ◽  
Observation Data ◽  
Perturbation Scheme ◽  
Ensemble Spread ◽  
System Components ◽  
Analysis Error

Abstract. The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This paper gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors, ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions and a generic perturbation scheme for observations and forcing fields. Other upgrades include revisions to the a priori bias correction scheme, observation quality control and assimilation method for sea-level anomalies. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes five ensemble members and covers the period from 1979 onwards. Updated versions of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 through sensitivity experiments suggests that all system components contribute to an improved fit to observation in reanalyses, with the most prominent contribution from direct assimilation of ocean in situ observations. Results of observing system experiments further suggest that the Argo float is the most influential observation type in our data assimilation system. Assessment of ORAS5 has also been carried out for several key ocean state variables and verified against reference climate data sets from the ESA CCI (European Space Agency Climate Change Initiative) project. With respect to ORAS4, ORAS5 has improved ocean climate state and variability in terms of SST and sea level, mostly due to increased model resolution and updates in assimilated observation data sets. In spite of the improvements, ORAS5 still underestimates the temporal variance of sea level and continues exhibiting large SST biases in the Gulf Stream and its extension regions which are possibly associated with misrepresentation of front positions. Overall, the SST and sea-ice uncertainties estimated using five ORAS5 ensemble members have spatial patterns consistent with those of analysis error. The ensemble spread of sea ice is commensurable with the sea-ice analysis error. On the contrary, the ensemble spread is under-dispersive for SST.

scholarly journals Integration of HF Radar Observations for an Enhanced Coastal Mean Dynamic Topography

2020 ◽  
Vol 7 ◽  
Author(s):  
Ainhoa Caballero ◽  
Sandrine Mulet ◽  
Nadia Ayoub ◽  
Ivan Manso-Narvarte ◽  
Xabier Davila ◽  
...  
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Satellite Data ◽  
Coastal Areas ◽  
Hf Radar ◽  
Global Ocean ◽  
Dynamic Topography ◽  
Mean Dynamic Topography ◽  
Radar Measurements

Satellite altimeters provide continuous information of the sea level variability and mesoscale processes for the global ocean. For estimating the sea level above the geoid and monitoring the full ocean dynamics from altimeters measurements, a key reference surface is needed: The Mean Dynamic Topography (MDT). However, in coastal areas, where, in situ measurements are sparse and the typical scales of the motion are generally smaller than in the deep ocean, the global MDT solutions are less accurate than in the open ocean, even if significant improvement has been done in the past years. An opportunity to fill in this gap has arisen with the growing availability of long time-series of high-resolution HF radar surface velocity measurements in some areas, such as the south-eastern Bay of Biscay. The prerequisite for the computation of a coastal MDT, using the newly available data of surface velocities, was to obtain a robust methodology to remove the ageostrophic signal from the HF radar measurements, in coherence with the scales resolved by the altimetry. To that end, we first filtered out the tidal and inertial motions, and then, we developed and tested a method that removed the Ekman component and the remaining divergent part of the flow. A regional high-resolution hindcast simulation was used to assess the method. Then, the processed HF radar geostrophic velocities were used in synergy with additional in situ data, altimetry, and gravimetry to compute a new coastal MDT, which shows significant improvement compared with the global MDT. This study showcases the benefit of combining satellite data with continuous, high-frequency, and synoptic in situ velocity data from coastal radar measurements; taking advantage of the different scales resolved by each of the measuring systems. The integrated analysis of in situ observations, satellite data, and numerical simulations has provided a further step in the understanding of the local ocean processes, and the new MDT a basis for more reliable monitoring of the study area. Recommendations for the replicability of the methodology in other coastal areas are also provided. Finally, the methods developed in this study and the more accurate regional MDT could benefit present and future high-resolution altimetric missions.

scholarly journals Low-Frequency Sea Level Variability and the Inverted Barometer Effect

2006 ◽  
Vol 23 (4) ◽  
pp. 619-629 ◽  
Author(s):  
Rui M. Ponte
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Low Frequency ◽  
Anomalous Behavior ◽  
Global Ocean ◽  
Sea Level Pressure ◽  
Seasonal Signals ◽  
Global Mean Sea Level ◽  
Inverted Barometer ◽  
Linear Trends

Abstract For a dynamical interpretation of sea level records, estimates are needed of the isostatic, or so-called inverted barometer, signals (ηib) associated with the ocean response to atmospheric loading. Seasonal and longer-period ηib signals are evaluated over the global ocean for the period 1958–2000 using monthly sea level pressure fields from two different atmospheric reanalyses. Variability and linear trends in ηib agree well for the two reanalyses in most regions but less so over the Southern Ocean, where uncertainties in ηib seem to be largest. The standard deviation of ηib ranges from <1 cm in equatorial regions to >7 cm in the regions of the Aleutian and Iceland lows and parts of the Southern and Arctic Oceans. When compared to a global tide gauge dataset, both seasonal and interannual ηib signals are found to contribute importantly to the sea level variance in many mid- and high-latitude records, with seasonal signals important as well in tropical records from India and Southeast Asia. For these records, subtracting ηib from the data can lead to changes in variance of 40% or more. Over the period of study, linear trends in ηib are mostly negative at low and midlatitudes and can cause negative biases in tide gauge estimates of global mean sea level rise that are comparable in magnitude to the effects of postglacial rebound. In agreement with previous findings, ηib signals are found to introduce anomalous behavior in local records (e.g., substantially weaker upward trends in the Mediterranean), and their removal can also reduce formal trend uncertainties. Accounting for ηib effects can be even more important when analyzing relatively short (decadal) records, such as those available from satellite altimetry.

scholarly journals How essential are Argo observations to constrain a global ocean data assimilation system?

2015 ◽  
Vol 12 (3) ◽  
pp. 1145-1186 ◽  
Author(s):  
V. Turpin ◽  
E. Remy ◽  
P. Y. Le Traon
Keyword(s):  
Data Assimilation ◽  
Forecast Error ◽  
Global Ocean ◽  
Altimeter Data ◽  
Western Boundary ◽  
Argo Data ◽  
Ocean Data Assimilation ◽  
In Situ Observations ◽  
The Impact

Abstract. Observing System Experiments (OSEs) are carried out over a one-year period to quantify the impact of Argo observations on the Mercator-Ocean 1/4° global ocean analysis and forecasting system. The reference simulation assimilates sea surface temperature (SST), SSALTO/DUACS altimeter data and Argo and other in situ observations from the Coriolis data center. Two other simulations are carried out where all Argo and half of Argo data sets are withheld. Assimilating Argo observations has a significant impact on analyzed and forecast temperature and salinity fields at different depths. Without Argo data assimilation, large errors occur in analyzed fields as estimated from the differences when compared with in situ observations. For example, in the 0–300 m layer RMS differences between analyzed fields and observations reach 0.25 psu and 1.25 °C in the western boundary currents and 0.1 psu and 0.75 °C in the open ocean. The impact of the Argo data in reducing observation-model forecast error is also significant from the surface down to a depth of 2000 m. Differences between independent observations and forecast fields are thus reduced by 20 % in the upper layers and by up to 40 % at a depth of 2000 m when Argo data are assimilated. At depth, the most impacted regions in the global ocean are the Mediterranean outflow and the Labrador Sea. A significant degradation can be observed when only half of the data are assimilated. All Argo observations thus matter, even with a 1/4° model resolution. The main conclusion is that the performance of global data assimilation systems is heavily dependent on the availability of Argo data.

scholarly journals Earth's water reservoirs in a changing climate

2020 ◽  
Vol 476 (2236) ◽  
pp. 20190458 ◽  
Author(s):  
Graeme L. Stephens ◽  
Julia M. Slingo ◽  
Eric Rignot ◽  
John T. Reager ◽  
Maria Z. Hakuba ◽  
...  
Keyword(s):  
Sea Level ◽  
Hydrological Cycle ◽  
Water Cycle ◽  
Water Reservoirs ◽  
Future Evolution ◽  
Quantitative Understanding ◽  
Global Mean Sea Level ◽  
Earth’S Climate ◽  
The Many ◽  
Different Sources

Progress towards achieving a quantitative understanding of the exchanges of water between Earth's main water reservoirs is reviewed with emphasis on advances accrued from the latest advances in Earth Observation from space. These exchanges of water between the reservoirs are a result of processes that are at the core of important physical Earth-system feedbacks, which fundamentally control the response of Earth's climate to the greenhouse gas forcing it is now experiencing, and are therefore vital to understanding the future evolution of Earth's climate. The changing nature of global mean sea level (GMSL) is the context for discussion of these exchanges. Different sources of satellite observations that are used to quantify ice mass loss and water storage over continents, how water can be tracked to its source using water isotope information and how the waters in different reservoirs influence the fluxes of water between reservoirs are described. The profound influence of Earth's hydrological cycle, including human influences on it, on the rate of GMSL rise is emphasized. The many intricate ways water cycle processes influence water exchanges between reservoirs and thus sea-level rise, including disproportionate influences by the tiniest water reservoirs, are emphasized.

scholarly journals Global ocean freshening, ocean mass increase and global mean sea level rise over 2005–2015

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
William Llovel ◽  
S. Purkey ◽  
B. Meyssignac ◽  
A. Blazquez ◽  
N. Kolodziejczyk ◽  
...  
Keyword(s):  
Sea Level ◽  
Global Ocean ◽  
Last Deglaciation ◽  
Mean Sea Level ◽  
Isostatic Adjustment ◽  
Ocean Mass ◽  
Grace Data ◽  
Global Mean Sea Level ◽  
Gravity Recovery ◽  
Global Mean

AbstractGlobal mean sea level has experienced an unabated rise over the 20th century. This observed rise is due to both ocean warming and increasing continental freshwater discharge. We estimate the net ocean mass contribution to sea level by assessing the global ocean salt budget based on the unprecedented amount of in situ data over 2005–2015. We obtain the ocean mass trends of 1.30 ± 1.13 mm · yr−1 (0–2000 m) and 1.55 ± 1.20 mm · yr−1 (full depth). These new ocean mass trends are smaller by 0.63–0.88 mm · yr−1 compared to the ocean mass trend estimated through the sea level budget approach. Our result provides an independent validation of Gravity Recovery And Climate Experiment (GRACE)-based ocean mass trend and, in addition, places an independent constraint on the combined Glacial Isostatic Adjustment – the Earth’s delayed viscoelastic response to the redistribution of mass that accompanied the last deglaciation- and geocenter variations needed to directly infer the ocean mass trend based on GRACE data.

Closing the global mean sea level budget from altimetry, GRACE/GRACE Follow-On and Argo data (2005-present)

2021 ◽  
Author(s):  
Anne Barnoud ◽  
Anny Cazenave ◽  
Julia Pfeffer ◽  
Michaël Ablain ◽  
Adrien Guérou ◽  
...  
Keyword(s):  
Sea Level ◽  
Systematic Bias ◽  
Satellite Mission ◽  
Argo Data ◽  
Steric Sea Level ◽  
Mean Sea Level ◽  
Ocean Mass ◽  
Salinity Data ◽  
Global Mean Sea Level ◽  
Global Mean

<p>Change in the global mean sea level (GMSL) is the sum of changes in the global mean steric sea level and global mean ocean mass. Over the 1993-2016 period, the GMSL budget was found to be closed, as shown by many independent studies. However, non-closure of the sea level budget after 2016 has been recently reported when using altimetry, Argo and GRACE/GRACE Follow-On data (Chen et al., GRL, 2020). This non-closure may result from errors in one or more components of the sea level budget (altimetry-based GMSL, Argo-based steric sea level or GRACE-based ocean mass). In this study, we investigated possible sources of errors affecting atlimetry and Argo data used to assess closure of the GMSL budget. Concerning altimetry data, we compared the wet tropospheric correction (WTC) applied to Jason-3 data (the reference satellite mission used for the GMSL computation since 2016) with that from the SARAL/AltiKa mission, and found no systematic bias between the radiometer measurements from these two missions. Besides, preliminary comparisons of GMSL trends (using the WTC ECMWF model) between different missions do not suggest discrepancies larger than 0.4 mm/yr over 2016-present. While further analyses are still needed, we find unlikely that non-closure of the sea level budget results from errors of the altimetry system. Concerning Argo data, since 2016, salinity data from different processing groups display strong discrepancies, likely due to instrumental problems and data editing issues. Good agreement is found between all available Argo-based thermosteric products. Given that the halosteric component should be negligible in global average, we re-examined the sea level budget since 2016 using only the thermosteric component and found significant improvement in the budget closure, although it is not yet fully closed. This suggests that the observed discrepancies in the Argo-based halosteric component largely contribute to the non-closure of the GMSL budget in the recent years.</p>

scholarly journals El Niño, La Niña, and the global sea level budget

Ocean Science ◽  
2016 ◽  
Vol 12 (6) ◽  
pp. 1165-1177 ◽  
Author(s):  
Christopher G. Piecuch ◽  
Katherine J. Quinn
Keyword(s):  
Sea Level ◽  
El Niño ◽  
Hydrological Cycle ◽  
El Nino ◽  
Southern Oscillation ◽  
Heat Content ◽  
Global Ocean ◽  
Surface Warming ◽  
Enso Events ◽  
The Pacific

Abstract. Previous studies show that nonseasonal variations in global-mean sea level (GMSL) are significantly correlated with El Niño–Southern Oscillation (ENSO). However, it has remained unclear to what extent these ENSO-related GMSL fluctuations correspond to steric (i.e., density) or barystatic (mass) effects. Here we diagnose the GMSL budget for ENSO events observationally using data from profiling floats, satellite gravimetry, and radar altimetry during 2005–2015. Steric and barystatic effects make comparable contributions to the GMSL budget during ENSO, in contrast to previous interpretations based largely on hydrological models, which emphasize the barystatic component. The steric contributions reflect changes in global ocean heat content, centered on the Pacific. Distributions of ocean heat storage in the Pacific arise from a mix of diabatic and adiabatic effects. Results have implications for understanding the surface warming slowdown and demonstrate the usefulness of the Global Ocean Observing System for constraining Earth's hydrological cycle and radiation imbalance.

scholarly journals A Global Ocean Observing System for Measuring Sea Level Atmospheric Pressure: Effects and Impacts on Numerical Weather Prediction

2017 ◽  
Vol 98 (2) ◽  
pp. 231-238 ◽  
Author(s):  
Luca Centurioni ◽  
András Horányi ◽  
Carla Cardinali ◽  
Etienne Charpentier ◽  
Rick Lumpkin
Keyword(s):  
Sea Level ◽  
Surface Pressure ◽  
Numerical Weather Prediction ◽  
Atmospheric Pressure ◽  
Weather Prediction ◽  
Global Ocean ◽  
Numerical Weather ◽  
Observation Impact ◽  
The Impact

Abstract Since 1994 the U.S. Global Drifter Program (GDP) and its international partners cooperating within the Data Buoy Cooperation Panel (DBCP) of the World Meteorological Organization (WMO) and the United Nations Education, Scientific and Cultural Organization (UNESCO) have been deploying drifters equipped with barometers primarily in the extratropical regions of the world’s oceans in support of operational weather forecasting. To date, the impact of the drifter data isolated from other sources has never been studied. This essay quantifies and discusses the effect and the impact of in situ sea level atmospheric pressure (SLP) data from the global drifter array on numerical weather prediction using observing system experiments and forecast sensitivity observation impact studies. The in situ drifter SLP observations are extremely valuable for anchoring the global surface pressure field and significantly contributing to accurate marine weather forecasts, especially in regions where no other in situ observations are available, for example, the Southern Ocean. Furthermore, the forecast sensitivity observation impact analysis indicates that the SLP drifter data are the most valuable per-observation contributor of the Global Observing System (GOS). All these results give evidence that surface pressure observations of drifting buoys are essential ingredients of the GOS and that their quantity, quality, and distribution should be preserved as much as possible in order to avoid any analysis and forecast degradations. The barometer upgrade program offered by the GDP, under which GDP-funded drifters can be equipped with partner-funded accurate air pressure sensors, is a practical example of how the DBCP collaboration is executed. Interested parties are encouraged to contact the GDP to discuss upgrade opportunities.

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