Putting It All Together: Adding Value to the Global Ocean and Climate Observing Systems With Complete Self-Consistent Ocean State and Parameter Estimates

Heimbach, Patrick; Fukumori, Ichiro; Hill, Christopher N.; Ponte, Rui M.; Stammer, Detlef; Wunsch, Carl; Campin, Jean‐Michel; Cornuelle, Bruce D.; Fenty, Ian; Forget, Gaël; Köhl, Armin; Mazloff, Matthew R.; Menemenlis, Dimitris; Nguyen, Anhco; Piecuch, Christopher G.; Trossman, David S.; Verdy, Ariane; Wang, Ou; Zhang, Hong

doi:10.3389/fmars.2019.00055

Cited by 33 publications

(29 citation statements)

References 98 publications

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“…Reanalyses have shown increasing maturity and reliability over the last decade [48] and are routinely used for ocean state monitoring [2] and climate investigations [49]. Ocean state estimates can be considered a subcategory of ocean reanalyses, which provide a fully consistent four-dimensional picture of the ocean [50] by optimizing the model solution over the entire reanalysis period (long assimilation time windows). Most reanalysis methods rely instead on sequential data assimilation, which can in turn introduce some discontinuity unless they are explicitly considered as budget terms [51].…”

Section: Methods Of Estimation Of Sea Levelmentioning

confidence: 99%

Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales

Storto

Bonaduce

Feng

et al. 2019

Water

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Sea level has risen significantly in the recent decades and is expected to rise further based on recent climate projections. Ocean reanalyses that synthetize information from observing networks, dynamical ocean general circulation models, and atmospheric forcing data offer an attractive way to evaluate sea level trend and variability and partition the causes of such sea level changes at both global and regional scales. Here, we review recent utilization of reanalyses for steric sea level trend investigations. State-of-the-science ocean reanalysis products are then used to further infer steric sea level changes. In particular, we used an ensemble of centennial reanalyses at moderate spatial resolution (between 0.5 × 0.5 and 1 × 1 degree) and an ensemble of eddy-permitting reanalyses to quantify the trends and their uncertainty over the last century and the last two decades, respectively. All the datasets showed good performance in reproducing sea level changes. Centennial reanalyses reveal a 1900–2010 trend of steric sea level equal to 0.47 ± 0.04 mm year−1, in agreement with previous studies, with unprecedented rise since the mid-1990s. During the altimetry era, the latest vintage of reanalyses is shown to outperform the previous ones in terms of skill scores against the independent satellite data. They consistently reproduce global and regional upper ocean steric expansion and the association with climate variability, such as ENSO. However, the mass contribution to the global mean sea level rise is varying with products and its representability needs to be improved, as well as the contribution of deep and abyssal waters to the steric sea level rise. Similarly, high-resolution regional reanalyses for the European seas provide valuable information on sea level trends, their patterns, and their causes.

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Section: Methods Of Estimation Of Sea Levelmentioning

confidence: 99%

Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales

Storto

Bonaduce

Feng

et al. 2019

Water

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“…First, model output is more globally complete than observational data sets in both time and space. Second, ECCO has been validated against independent data sets (Heimbach et al, ). Third, its rerun is guaranteed to maintain consistency in the dynamics and physics of its underlying ocean model, which filter‐based reanalyses cannot do due to their use of analysis increments (Pilo et al, ; Stammer et al, ).…”

Section: Introductionmentioning

confidence: 99%

Predictability of Ocean Heat Content From Electrical Conductance

Trossman

Tyler

2019

JGR Oceans

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Ocean heat content (OHC) is a key climate variable that needs to be monitored to know how Earth's energy imbalance is changing, yet observing OHC remains a challenge. The present study examines whether a depth integral of the ocean's electrical conductivity ("conductance"), which may be inferred from both in situ methods and satellite magnetometers over the global ocean, could help monitor OHC. The ocean's electrical conductivity locally depends on temperature, salinity, and pressure, but it is not as well known how the conductance depends on OHC and ocean salt content. By examining the output of an ocean state estimate shown to agree well with observations that have not been assimilated, this study evaluates the fundamental limitations of using perfectly known ocean conductance to predict OHC, rather than the challenges associated with accounting for observational error. It is found that the ocean's conductance and OHC fields are nonlinearly related but nevertheless highly correlated. A statistical framework tends to predict OHC more accurately than ocean salt content from ocean conductance in regions where conductivity is more sensitive to salinity than temperature. The annually (bidecadally) averaged OHC can be predicted from a combination of conductance and depth-averaged conductivity ocean fields to within nearly 0.1% (1%) error globally and even more accurately in many poorly observed (e.g., ice-covered) regions. Practical application of this statistical framework to monitor OHC requires examination of the effect of uncertainties in the observed bathymetry and ocean conductance, which vary with application.Plain Language Summary Seawater's electrical conductivity describes the ocean's ability to conduct electricity, which has an associated magnetic field. It may be possible to get a conductivity averaged over all depths from a combination of satellite observations and our knowledge of the seafloor. Because conductivity depends upon how warm/cold the ocean is, how salty the ocean is, and how deep you are in the ocean, we investigate whether this depth-averaged conductivity can provide us with information about how much heat is in the ocean over different time period lengths. We develop some frameworks for predicting how much heat is in the ocean from the averaged conductivity and find that there is a trade-off between the accuracy of the predictions and the length of the time period over which changes in the amount of heat can be detected in the ocean. We also note that there will be additional uncertainties added when our frameworks are applied to observations. The electrical conductance (i.e., depth integral of conductivity) can of course be obtained by in situ instruments sampling a depth profile of conductivity, but more practical means are also available. As a simple

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“…Acoustic in situ rainfall and wind speed estimates can improve our observations of air-sea fluxes (Centurioni et al, 2019), particularly in sparely sampled regions such as the Southern Ocean (Swart et al, 2019) and polar regions (Smith et al, 2019) as well as improve our ability to monitor wind/current/wave interactions (Villas Bôas et al, 2019). The direct estimates of ocean state variables from acoustic tomography and acoustically located and navigated autonomous platforms operating in undersampled high-latitude regions will improve ocean state estimation (Heimbach et al, 2019). The rich applications of hydroacoustic monitoring from the CTBTO IMS demonstrate that additional observations from fixed acoustic transceiver nodes, coupled with soundscape maps provided by PAM, are important components of Eulerian observational systems, including tsunami warning (Angove et al, 2019).…”

Section: Discussionmentioning

confidence: 99%