Revised estimates of the ocean energy cycle and the key role of the western boundary in the APE to KE conversion due to high latitude cooling

NASA Astrophysics Data System (ADS)

Tailleux, Remi

2014-05-01

The ocean energy cycle is a key aspect of the ocean circulation, and has been traditionally framed in terms of Lorenz (1955) theory of available potential energy. However, the latest available observational estimate of the ocean energy cycle is due to Oort and Peixoto (1994) and is now very dated. Moreover, the latter estimate relies on the so-called Lorenz quasi-geostrophic approximation, which is known to be very inaccurate. Oort and Peixoto also neglected the internal energy contribution to the total available potential energy, which is now understood to be far from negligible, and to account for up to 40 percent of the total APE. The purpose of this work is to revisit observational estimates of the ocean energy cycle by taking advantage of a newly developed APE framework, as well as of the many new available observational products for temperature, salinity and surface buoyancy fluxes. In contrast to previous frameworks, our APE framework (Tailleux, 2013) relies on a physically well defined local APE definition, which is valid for a binary Boussinesq or fully compressible fluid with an arbitrary nonlinear equation of state. As part of our approach, we also developed a new fast and accurate way to construct Lorenz reference state of minimum potential energy, based on using the joint probability distribution function for temperature and salinity. Results will be presented for a variety of observational products, as well as for the ECCO2 ocean state estimate. The role of the deep western boundary as the place where the APE created by high latitude is converted into kinetic energy (KE) as part of driving the Atlantic meridional overturning circulation will be emphasized. References: Tailleux, R., 2013: Available potential energy density for a multicomponent Boussinesq fluid with arbitrary nonlinear equation of state.J. Fluid Mech., 735,499-518. Sijp, W., J.M.Gregory, R. Tailleux, P. Spence, 2012: The key role of the western boundary in linking the AMOC strength to the North South pressure gradient. J. Phys. Oceanogr., 42, 628-643.

Sequential estimation and satellite data assimilation in meteorology and oceanography

NASA Technical Reports Server (NTRS)

Ghil, M.

1986-01-01

The central theme of this review article is the role that dynamics plays in estimating the state of the atmosphere and of the ocean from incomplete and noisy data. Objective analysis and inverse methods represent an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Four-dimensional data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric or oceanic model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and oceanic sciences, namely, mesoscale meteorology, medium and long-range forecasting, and upper-ocean dynamics.

The Use of the Data Assimilation Research Testbed for Initializing and Evaluating IPCC Decadal Forecasts

NASA Astrophysics Data System (ADS)

Raeder, K.; Anderson, J. L.; Lauritzen, P. H.; Hoar, T. J.; Collins, N.

2010-12-01

DART (www.image.ucar.edu/DAReS/DART) is a general purpose, freely available, ensemble Kalman filter, data assimilation system, which is being used to generate state-of-the-art, partially coupled, ocean-atmosphere re-analyses in support of the decadal predictions planned for the next IPCC report. The resulting gridded product is directly comparable to the state variables output by POP and CAM (oceanic and atmospheric components of NCAR's Community Earth System Model climate model) because those are the assimilating models. Other models could also benefit from comparison against these reanalyses, since the ocean analyses are at the leading edge of ocean state estimation, and the atmospheric analyses are competitive with operational centers'. Such comparisons can reveal model biases and predictability characteristics, and do so in a quantitative way, since the ensemble nature of the analyses provides an objective estimate of the analysis error. The analyses will also be used as initial conditions for the decadal forecasts because they are the most realistic available. The generation of such analyses has revealed errors in model formulation for several versions of the finite volume core CAM, which has led to model improvements in each case. New models can be incorporated into DART in a matter of weeks, allowing them to be compared directly against available observations. The observations currently used in the assimilations include, for the ocean; temperature and salinity from the World Ocean Database (floats, drifters, moorings, autonomous pinipeds, and others), and for the atmosphere; temperature and winds from radiosondes, satellite drift winds, ACARS and aircraft. Observations of ocean currents and atmospheric moisture and pressure are also available. Global Positioning System profiles of atmospheric temperature and moisture are available for recent years. All that is required to add new observations to the suite is the forward operator, which generates an estimate of the observation from the model state. In summary, DART provides a flexible, convenient, rigorous environment for evaluating models in the context of real observations.

Two Techniques for Estimating Deglacial Mean-Ocean δ13 C Change from the Same Set of 493 Benthic δ13C Records

NASA Astrophysics Data System (ADS)

Peterson, C. D.; Lisiecki, L. E.; Gebbie, G.

2013-12-01

The crux of carbon redistribution over the deglaciation centers on the ocean, where the isotopic signature of terrestrial carbon (δ13C terrestrial carbon = -25‰) is observed as a 0.3-0.7‰ shift in benthic foraminiferal δ13C. Deglacial mean-ocean δ13C estimates vary due to different subsets of benthic δ13C data and different methods of weighting the mean δ13C by volume. Here, we present a detailed 1-to-1 comparison of two methods of calculating mean δ13C change and uncertainty estimates using the same set of 493 benthic Cibicidoides spp. δ13C measurements for the LGM and Late Holocene. The first method divides the ocean into 8 regions, and uses simple line fits to describe the distribution of δ13C data for each timeslice over 0.5-5 km depth. With these line fits, we estimate the δ13C value at 100-meter intervals and weight those estimates by the regional volume at each depth slice. The mean-ocean δ13C is the sum of these volume-weighted regional δ13C estimates and the uncertainty of these mean-ocean δ13C estimates is computed using Monte Carlo simulations. The whole-ocean δ13C change is estimated using extrapolated surface- and deep-ocean δ13C estimates, and an assumed δ13C value for the Southern Ocean. This method yields an estimated LGM-to-Holocene change of 0.38×0.07‰ for 0.5-5km and 0.35×0.16‰ for the whole ocean (Peterson et al., 2013, submitted to Paleoceanography). The second method reconstructs glacial and modern δ13C by combining the same data compilation as above with a steady-state ocean circulation model (Gebbie, 2013, submitted to Paleoceanography). The result is a tracer distribution on a 4-by-4 degree horizontal resolution grid with 23 vertical levels, and an estimate of the distribution's uncertainty that accounts for the distinct modern and glacial water-mass geometries. From both methods, we compare the regional δ13C estimates (0.5-5 km), surface δ13C estimates (0-0.5 km), deep δ13C estimates (>5 km), Southern Ocean δ13C estimates, and finally whole-ocean δ13C estimates. Additionally, we explore the sensitivity of our mean δ13C estimates to our region and depth boundaries. Such a detailed comparison broadens our understanding of the limitations of sparse geologic data sets and deepens our understanding of deglacial δ13C changes.

Vertical eddy diffusivity as a control parameter in the tropical Pacific

NASA Astrophysics Data System (ADS)

Martinez Avellaneda, N.; Cornuelle, B.

2011-12-01

Ocean models suffer from errors in the treatment of turbulent sub-grid-scale motions responsible for mixing and energy dissipation. Unrealistic small-scale physics in models can have large-scale consequences, such as biases in the upper ocean temperature, a symptom of poorly-simulated upwelling, currents and air-sea interactions. This is of special importance in the tropical Pacific Ocean (TP), which is home to energetic air-sea interactions that affect global climate. It has been shown in a number of studies that the simulated ENSO variability is highly dependent on the state of the ocean (e.g.: background mixing). Moreover, the magnitude of the vertical numerical diffusion is of primary importance in properly reproducing the Pacific equatorial thermocline. This work is part of a NASA-funded project to estimate the space- and time-varying ocean mixing coefficients in an eddy-permitting (1/3dgr) model of the TP to obtain an improved estimate of its time-varying circulation and its underlying dynamics. While an estimation procedure for the TP (26dgr S - 30dgr N) in underway using the MIT general circulation model, complementary adjoint-based sensitivity studies have been carried out for the starting ocean state from Forget (2010). This analysis aids the interpretation of the estimated mixing coefficients and possible error compensation. The focus of the sensitivity tests is the Equatorial Undercurrent and sub-thermocline jets (i.e., Tsuchiya Jets), which have been thought to have strong dependence on vertical diffusivity and should provide checks on the estimated mixing parameters. In order to build intuition for the vertical diffusivity adjoint results in the TP, adjoint and forward perturbed simulations were carried out for an idealized sharp thermocline in a rectangular domain.

Quantifying How Observations Inform a Numerical Reanalysis of Hawaii

NASA Astrophysics Data System (ADS)

Powell, B. S.

2017-11-01

When assimilating observations into a model via state-estimation, it is possible to quantify how each observation changes the modeled estimate of a chosen oceanic metric. Using an existing 2 year reanalysis of Hawaii that includes more than 31 million observations from satellites, ships, SeaGliders, and autonomous floats, I assess which observations most improve the estimates of the transport and eddy kinetic energy. When the SeaGliders were in the water, they comprised less than 2.5% of the data, but accounted for 23% of the transport adjustment. Because the model physics constrains advanced state-estimation, the prescribed covariances are propagated in time to identify observation-model covariance. I find that observations that constrain the isopycnal tilt across the transport section provide the greatest impact in the analysis. In the case of eddy kinetic energy, observations that constrain the surface-driven upper ocean have more impact. This information can help to identify optimal sampling strategies to improve both state-estimates and forecasts.

Estimating the distribution of colored dissolved organic matter during the Southern Ocean Gas Exchange Experiment using four-dimensional variational data assimilation

NASA Astrophysics Data System (ADS)

Del Castillo, C. E.; Dwivedi, S.; Haine, T. W. N.; Ho, D. T.

2017-03-01

We diagnosed the effect of various physical processes on the distribution of mixed-layer colored dissolved organic matter (CDOM) and a sulfur hexafluoride (SF6) tracer during the Southern Ocean Gas Exchange Experiment (SO GasEx). The biochemical upper ocean state estimate uses in situ and satellite biochemical and physical data in the study region, including CDOM (absorption coefficient and spectral slope), SF6, hydrography, and sea level anomaly. Modules for photobleaching of CDOM and surface transport of SF6 were coupled with an ocean circulation model for this purpose. The observed spatial and temporal variations in CDOM were captured by the state estimate without including any new biological source term for CDOM, assuming it to be negligible over the 26 days of the state estimate. Thermocline entrainment and photobleaching acted to diminish the mixed-layer CDOM with time scales of 18 and 16 days, respectively. Lateral advection of CDOM played a dominant role and increased the mixed-layer CDOM with a time scale of 12 days, whereas lateral diffusion of CDOM was negligible. A Lagrangian view on the CDOM variability was demonstrated by using the SF6 as a weighting function to integrate the CDOM fields. This and similar data assimilation methods can be used to provide reasonable estimates of optical properties, and other physical parameters over the short-term duration of a research cruise, and help in the tracking of tracer releases in large-scale oceanographic experiments, and in oceanographic process studies.

Estimating the Distribution of Colored Dissolved Organic Matter During the Southern Ocean Gas Exchange Experiment Using Four-Dimensional Variational Data Assimilation

NASA Technical Reports Server (NTRS)

Del Castillo, C. E.; Dwivedi, S.; Haine, T. W. N.; Ho, D. T.

2017-01-01

We diagnosed the effect of various physical processes on the distribution of mixed-layer colored dissolved organic matter (CDOM) and a sulfur hexauoride (SF6) tracer during the Southern Ocean Gas Exchange Experiment (SO GasEx). The biochemical upper ocean state estimate uses in situ and satellite biochemical and physical data in the study region, including CDOM (absorption coefcient and spectral slope), SF6, hydrography, and sea level anomaly. Modules for photobleaching of CDOM and surface transport of SF6 were coupled with an ocean circulation model for this purpose. The observed spatial and temporal variations in CDOM were captured by the state estimate without including any new biological source term for CDOM, assuming it to be negligible over the 26 days of the state estimate. Thermocline entrainment and photobleaching acted to diminish the mixed-layer CDOM with time scales of 18 and 16 days, respectively. Lateral advection of CDOM played a dominant role and increased the mixed-layer CDOM with a time scale of 12 days, whereas lateral diffusion of CDOM was negligible. A Lagrangian view on the CDOM variability was demonstrated by using the SF6 as a weighting function to integrate the CDOM elds. This and similar data assimilation methods can be used to provide reasonable estimates of optical properties, and other physical parameters over the short-term duration of a research cruise, and help in the tracking of tracer releases in large-scale oceanographic experiments, and in oceanographic process studies.

Modern Estimates of Global Water Cycle Fluxes

NASA Astrophysics Data System (ADS)

Rodell, M.; Beaudoing, H. K.; L'Ecuyer, T. S.; Olson, W. S.

2014-12-01

The goal of the first phase of the NASA Energy and Water Cycle Study (NEWS) Water and Energy Cycle Climatology project was to develop "state of the global water cycle" and "state of the global energy cycle" assessments based on data from modern ground and space based observing systems and data integrating models. Here we describe results of the water cycle assessment, including mean annual and monthly fluxes over continents and ocean basins during the first decade of the millennium. To the extent possible, the water flux estimates are based on (1) satellite measurements and (2) data-integrating models. A careful accounting of uncertainty in each flux was applied within a routine that enforced multiple water and energy budget constraints simultaneously in a variational framework, in order to produce objectively-determined, optimized estimates. Simultaneous closure of the water and energy budgets caused the ocean evaporation and precipitation terms to increase by about 10% and 5% relative to the original estimates, mainly because the energy budget required turbulent heat fluxes to be substantially larger in order to balance net radiation. In the majority of cases, the observed annual, surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are a non-issue. Fluxes are poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian Islands, leading to reliance on atmospheric analysis estimates. Other details of the study and future directions will be discussed.

Calibration of Ocean Forcing with satellite Flux Estimates (COFFEE)

NASA Astrophysics Data System (ADS)

Barron, Charlie; Jan, Dastugue; Jackie, May; Rowley, Clark; Smith, Scott; Spence, Peter; Gremes-Cordero, Silvia

2016-04-01

Predicting the evolution of ocean temperature in regional ocean models depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. Within the COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates, real-time satellite observations are used to estimate shortwave, longwave, sensible, and latent air-sea heat flux corrections to a background estimate from the prior day's regional or global model forecast. These satellite-corrected fluxes are used to prepare a corrected ocean hindcast and to estimate flux error covariances to project the heat flux corrections for a 3-5 day forecast. In this way, satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. While traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle, COFFEE endeavors to appropriately partition and reduce among various surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using operational global or regional atmospheric forcing. Experiment cases combine different levels of flux calibration with assimilation alternatives. The cases use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is equally applicable to other regions. These approaches within a 3DVAR application are anticipated to be useful for global and larger regional domains where a full 4DVAR methodology may be cost-prohibitive.

Ocean Current Estimation Using a Multi-Model Ensemble Kalman Filter During the Grand Lagrangian Deployment Experiment (GLAD)

DTIC Science & Technology

2014-12-27

oil spill plumes). Results can be used for operational applications or to derive enhanced background fields for other data assimilation systems, thus...with the ocean state and for which a forward model exists (e.g. oil spill plumes). The MEKF assumes that a prior system is running with several forecast...the ocean state and for which a forward model exists (e.g. oil spill images). The results discussed in this paper can be viewed as part of a framework

Horizontal mixing in the Southern Ocean from Argo float trajectories

NASA Astrophysics Data System (ADS)

Roach, Christopher J.; Balwada, Dhruv; Speer, Kevin

2016-08-01

We provide the first observational estimate of the circumpolar distribution of cross-stream eddy diffusivity at 1000 m in the Southern Ocean using Argo float trajectories. We show that Argo float trajectories, from the float surfacing positions, can be used to estimate lateral eddy diffusivities in the ocean and that these estimates are comparable to those obtained from RAFOS floats, where they overlap. Using the Southern Ocean State Estimate (SOSE) velocity fields to advect synthetic particles with imposed behavior that is "Argo-like" and "RAFOS-like" diffusivity estimates from both sets of synthetic particles agreed closely at the three dynamically very different test sites, the Kerguelen Island region, the Southeast Pacific Ocean, and the Scotia Sea, and support our approach. Observed cross-stream diffusivities at 1000 m, calculated from Argo float trajectories, ranged between 300 and 2500 m2 s-1, with peaks corresponding to topographic features associated with the Scotia Sea, the Kerguelen Plateau, the Campbell Plateau, and the Southeast Pacific Ridge. These observational estimates agree with previous regional estimates from the Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean (DIMES) near the Drake Passage, and other estimates from natural tracers (helium), inverse modeling studies, and current meter measurements. These estimates are also compared to the suppressed eddy diffusivity in the presence of mean flows. The comparison suggests that away from regions of strong topographic steering suppression explains both the structure and magnitude of eddy diffusivity but that eddy diffusivities in the regions of topographic steering are greater than what would be theoretically expected and the ACC experiences localized enhanced cross-stream mixing in these regions.

Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

NASA Astrophysics Data System (ADS)

El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

2016-02-01

Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate different biological parameters of phytoplanktons and zooplanktons. We analyze the performance of the filters in terms of complexity and accuracy of the state and parameters estimates.

On the assimilation of absolute geodetic dynamic topography in a global ocean model: impact on the deep ocean state

NASA Astrophysics Data System (ADS)

Androsov, Alexey; Nerger, Lars; Schnur, Reiner; Schröter, Jens; Albertella, Alberta; Rummel, Reiner; Savcenko, Roman; Bosch, Wolfgang; Skachko, Sergey; Danilov, Sergey

2018-05-01

General ocean circulation models are not perfect. Forced with observed atmospheric fluxes they gradually drift away from measured distributions of temperature and salinity. We suggest data assimilation of absolute dynamical ocean topography (DOT) observed from space geodetic missions as an option to reduce these differences. Sea surface information of DOT is transferred into the deep ocean by defining the analysed ocean state as a weighted average of an ensemble of fully consistent model solutions using an error-subspace ensemble Kalman filter technique. Success of the technique is demonstrated by assimilation into a global configuration of the ocean circulation model FESOM over 1 year. The dynamic ocean topography data are obtained from a combination of multi-satellite altimetry and geoid measurements. The assimilation result is assessed using independent temperature and salinity analysis derived from profiling buoys of the AGRO float data set. The largest impact of the assimilation occurs at the first few analysis steps where both the model ocean topography and the steric height (i.e. temperature and salinity) are improved. The continued data assimilation over 1 year further improves the model state gradually. Deep ocean fields quickly adjust in a sustained manner: A model forecast initialized from the model state estimated by the data assimilation after only 1 month shows that improvements induced by the data assimilation remain in the model state for a long time. Even after 11 months, the modelled ocean topography and temperature fields show smaller errors than the model forecast without any data assimilation.

Multivariate Error Covariance Estimates by Monte-Carlo Simulation for Assimilation Studies in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Borovikov, Anna; Rienecker, Michele M.; Keppenne, Christian; Johnson, Gregory C.

2004-01-01

One of the most difficult aspects of ocean state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model-observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross-covariances between different model variables used. Here a comparison is made between a univariate Optimal Interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature. In the UOI case only temperature is updated using a Gaussian covariance function and in the MvOI salinity, zonal and meridional velocities as well as temperature, are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimation of the model error statistics is made by Monte-Carlo techniques from an ensemble of model integrations. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross-covariances between the fields of different physical variables constituting the model state vector, at the same time incorporating the model's dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere-Ocean array have been assimilated in this study. In order to investigate the efficacy of the multivariate scheme two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity and temperature. For reference, a third control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the UOI and MvOI is similar with respect to the temperature field, the salinity and velocity fields are greatly improved when multivariate correction is used, as evident from the analyses of the rms differences of these fields and independent observations. The MvOI assimilation is found to improve upon the control run in generating the water masses with properties close to the observed, while the UOI failed to maintain the temperature and salinity structure.

Estimate of carbonyl sulfide tropical oceanic surface fluxes using Aura Tropospheric Emission Spectrometer observations

NASA Astrophysics Data System (ADS)

Kuai, Le; Worden, John R.; Campbell, J. Elliott; Kulawik, Susan S.; Li, King-Fai; Lee, Meemong; Weidner, Richard J.; Montzka, Stephen A.; Moore, Fred L.; Berry, Joe A.; Baker, Ian; Denning, A. Scott; Bian, Huisheng; Bowman, Kevin W.; Liu, Junjie; Yung, Yuk L.

2015-10-01

Quantifying the carbonyl sulfide (OCS) land/ocean fluxes contributes to the understanding of both the sulfur and carbon cycles. The primary sources and sinks of OCS are very likely in a steady state because there is no significant observed trend or interannual variability in atmospheric OCS measurements. However, the magnitude and spatial distribution of the dominant ocean source are highly uncertain due to the lack of observations. In particular, estimates of the oceanic fluxes range from approximately 280 Gg S yr-1 to greater than 800 Gg S yr-1, with the larger flux needed to balance a similarly sized terrestrial sink that is inferred from NOAA continental sites. Here we estimate summer tropical oceanic fluxes of OCS in 2006 using a linear flux inversion algorithm and new OCS data acquired by the Aura Tropospheric Emissions Spectrometer (TES). Modeled OCS concentrations based on these updated fluxes are consistent with HIAPER Pole-to-Pole Observations during 4th airborne campaign and improve significantly over the a priori model concentrations. The TES tropical ocean estimate of 70 ± 16 Gg S in June, when extrapolated over the whole year (about 840 ± 192 Gg S yr-1 ), supports the hypothesis proposed by Berry et al. (2013) that the ocean flux is in the higher range of approximately 800 Gg S yr-1.

Ensemble Kalman filter inference of spatially-varying Manning's n coefficients in the coastal ocean

NASA Astrophysics Data System (ADS)

Siripatana, Adil; Mayo, Talea; Knio, Omar; Dawson, Clint; Maître, Olivier Le; Hoteit, Ibrahim

2018-07-01

Ensemble Kalman (EnKF) filtering is an established framework for large scale state estimation problems. EnKFs can also be used for state-parameter estimation, using the so-called "Joint-EnKF" approach. The idea is simply to augment the state vector with the parameters to be estimated and assign invariant dynamics for the time evolution of the parameters. In this contribution, we investigate the efficiency of the Joint-EnKF for estimating spatially-varying Manning's n coefficients used to define the bottom roughness in the Shallow Water Equations (SWEs) of a coastal ocean model. Observation System Simulation Experiments (OSSEs) are conducted using the ADvanced CIRCulation (ADCIRC) model, which solves a modified form of the Shallow Water Equations. A deterministic EnKF, the Singular Evolutive Interpolated Kalman (SEIK) filter, is used to estimate a vector of Manning's n coefficients defined at the model nodal points by assimilating synthetic water elevation data. It is found that with reasonable ensemble size (O (10)) , the filter's estimate converges to the reference Manning's field. To enhance performance, we have further reduced the dimension of the parameter search space through a Karhunen-Loéve (KL) expansion. We have also iterated on the filter update step to better account for the nonlinearity of the parameter estimation problem. We study the sensitivity of the system to the ensemble size, localization scale, dimension of retained KL modes, and number of iterations. The performance of the proposed framework in term of estimation accuracy suggests that a well-tuned Joint-EnKF provides a promising robust approach to infer spatially varying seabed roughness parameters in the context of coastal ocean modeling.

Physics-based coastal current tomographic tracking using a Kalman filter.

PubMed

Wang, Tongchen; Zhang, Ying; Yang, T C; Chen, Huifang; Xu, Wen

2018-05-01

Ocean acoustic tomography can be used based on measurements of two-way travel-time differences between the nodes deployed on the perimeter of the surveying area to invert/map the ocean current inside the area. Data at different times can be related using a Kalman filter, and given an ocean circulation model, one can in principle now cast and even forecast current distribution given an initial distribution and/or the travel-time difference data on the boundary. However, an ocean circulation model requires many inputs (many of them often not available) and is unpractical for estimation of the current field. A simplified form of the discretized Navier-Stokes equation is used to show that the future velocity state is just a weighted spatial average of the current state. These weights could be obtained from an ocean circulation model, but here in a data driven approach, auto-regressive methods are used to obtain the time and space dependent weights from the data. It is shown, based on simulated data, that the current field tracked using a Kalman filter (with an arbitrary initial condition) is more accurate than that estimated by the standard methods where data at different times are treated independently. Real data are also examined.

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.; Balmaseda, Magdalena; Awaji, Toshiyuki; Barnier, Bernard; Behringer, David; Bell, Mike; Bourassa, Mark; Brasseur, Pierre; Breivik, Lars-Anders; Carton, James;

Regional Ocean Data Assimilation

NASA Astrophysics Data System (ADS)

Edwards, Christopher A.; Moore, Andrew M.; Hoteit, Ibrahim; Cornuelle, Bruce D.

2015-01-01

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal regions. As in weather prediction, the accurate representation of physical, chemical, and/or biological properties in the ocean is challenging. Models and observations alone provide imperfect representations of the ocean state, but together they can offer improved estimates. Variational and sequential methods are among the most widely used in regional ocean systems, and there have been exciting recent advances in ensemble and four-dimensional variational approaches. These techniques are increasingly being tested and adapted for biogeochemical applications.

Regional ocean data assimilation.

PubMed

Edwards, Christopher A; Moore, Andrew M; Hoteit, Ibrahim; Cornuelle, Bruce D

2015-01-01

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal regions. As in weather prediction, the accurate representation of physical, chemical, and/or biological properties in the ocean is challenging. Models and observations alone provide imperfect representations of the ocean state, but together they can offer improved estimates. Variational and sequential methods are among the most widely used in regional ocean systems, and there have been exciting recent advances in ensemble and four-dimensional variational approaches. These techniques are increasingly being tested and adapted for biogeochemical applications.

Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

NASA Technical Reports Server (NTRS)

Adler, Robert; Gu, Guojun; Huffman, George

2012-01-01

A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet's mean precipitation.

Practical global oceanic state estimation

NASA Astrophysics Data System (ADS)

Wunsch, Carl; Heimbach, Patrick

2007-06-01

The problem of oceanographic state estimation, by means of an ocean general circulation model (GCM) and a multitude of observations, is described and contrasted with the meteorological process of data assimilation. In practice, all such methods reduce, on the computer, to forms of least-squares. The global oceanographic problem is at the present time focussed primarily on smoothing, rather than forecasting, and the data types are unlike meteorological ones. As formulated in the consortium Estimating the Circulation and Climate of the Ocean (ECCO), an automatic differentiation tool is used to calculate the so-called adjoint code of the GCM, and the method of Lagrange multipliers used to render the problem one of unconstrained least-squares minimization. Major problems today lie less with the numerical algorithms (least-squares problems can be solved by many means) than with the issues of data and model error. Results of ongoing calculations covering the period of the World Ocean Circulation Experiment, and including among other data, satellite altimetry from TOPEX/POSEIDON, Jason-1, ERS- 1/2, ENVISAT, and GFO, a global array of profiling floats from the Argo program, and satellite gravity data from the GRACE mission, suggest that the solutions are now useful for scientific purposes. Both methodology and applications are developing in a number of different directions.

Mechanisms Controlling Global Mean Sea Surface Temperature Determined From a State Estimate

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Piecuch, C. G.

2018-04-01

Global mean sea surface temperature (T¯) is a variable of primary interest in studies of climate variability and change. The temporal evolution of T¯ can be influenced by surface heat fluxes (F¯) and by diffusion (D¯) and advection (A¯) processes internal to the ocean, but quantifying the contribution of these different factors from data alone is prone to substantial uncertainties. Here we derive a closed T¯ budget for the period 1993-2015 based on a global ocean state estimate, which is an exact solution of a general circulation model constrained to most extant ocean observations through advanced optimization methods. The estimated average temperature of the top (10-m thick) level in the model, taken to represent T¯, shows relatively small variability at most time scales compared to F¯, D¯, or A¯, reflecting the tendency for largely balancing effects from all the latter terms. The seasonal cycle in T¯ is mostly determined by small imbalances between F¯ and D¯, with negligible contributions from A¯. While D¯ seems to simply damp F¯ at the annual period, a different dynamical role for D¯ at semiannual period is suggested by it being larger than F¯. At periods longer than annual, A¯ contributes importantly to T¯ variability, pointing to the direct influence of the variable ocean circulation on T¯ and mean surface climate.

Experiences in multiyear combined state-parameter estimation with an ecosystem model of the North Atlantic and Arctic Oceans using the Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Simon, Ehouarn; Samuelsen, Annette; Bertino, Laurent; Mouysset, Sandrine

2015-12-01

A sequence of one-year combined state-parameter estimation experiments has been conducted in a North Atlantic and Arctic Ocean configuration of the coupled physical-biogeochemical model HYCOM-NORWECOM over the period 2007-2010. The aim is to evaluate the ability of an ensemble-based data assimilation method to calibrate ecosystem model parameters in a pre-operational setting, namely the production of the MyOcean pilot reanalysis of the Arctic biology. For that purpose, four biological parameters (two phyto- and two zooplankton mortality rates) are estimated by assimilating weekly data such as, satellite-derived Sea Surface Temperature, along-track Sea Level Anomalies, ice concentrations and chlorophyll-a concentrations with an Ensemble Kalman Filter. The set of optimized parameters locally exhibits seasonal variations suggesting that time-dependent parameters should be used in ocean ecosystem models. A clustering analysis of the optimized parameters is performed in order to identify consistent ecosystem regions. In the north part of the domain, where the ecosystem model is the most reliable, most of them can be associated with Longhurst provinces and new provinces emerge in the Arctic Ocean. However, the clusters do not coincide anymore with the Longhurst provinces in the Tropics due to large model errors. Regarding the ecosystem state variables, the assimilation of satellite-derived chlorophyll concentration leads to significant reduction of the RMS errors in the observed variables during the first year, i.e. 2008, compared to a free run simulation. However, local filter divergences of the parameter component occur in 2009 and result in an increase in the RMS error at the time of the spring bloom.

Deep Water Ocean Acoustics (DWOA): The Philippine Sea, OBSANP, and THAAW Experiments

DTIC Science & Technology

2015-09-30

the travel times. 4 The ocean state estimates were then re-computed to fit the acoustic travel times as integrals of the sound speed, and...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Deep Water Ocean Acoustics (DWOA): The Philippine Sea...deep-water acoustic propagation and ambient noise has been collected in a wide variety of environments over the last few years with ONR support

Satellite-based Calibration of Heat Flux at the Ocean Surface

NASA Astrophysics Data System (ADS)

Barron, C. N.; Dastugue, J. M.; May, J. C.; Rowley, C. D.; Smith, S. R.; Spence, P. L.; Gremes-Cordero, S.

2016-02-01

Model forecasts of upper ocean heat content and variability on diurnal to daily scales are highly dependent on estimates of heat flux through the air-sea interface. Satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. Traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle. Subsequent evolution depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. The COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates) endeavors to correct ocean forecast bias through a responsive error partition among surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using Navy operational global or regional atmospheric forcing. COFFEE addresses satellite-calibration of surface fluxes to estimate surface error covariances and links these to the ocean interior. Experiment cases combine different levels of flux calibration with different assimilation alternatives. The cases may use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is equally applicable to other regions. These approaches within a 3DVAR application are anticipated to be useful for global and larger regional domains where a full 4DVAR methodology may be cost-prohibitive.

THE ECOLOGICAL CONDITION OF ESTUARIES: A FOCUS ON THE ATLANTIC OCEAN AND GULF OF MEXICO COASTS OF THE UNITED STATES

EPA Science Inventory

Monitoring the estuaries of the Atlantic Ocean and Gulf of Mexico coastlines was performed annually from 1990 to 1997 to assess ecological conditions on a regional basis for four biogeographic provinces. These province estimates - Virginian, Carolinian, West Indian, and Louisiani...

Mechanisms underlying recent decadal changes in subpolar North Atlantic Ocean heat content

NASA Astrophysics Data System (ADS)

Piecuch, Christopher G.; Ponte, Rui M.; Little, Christopher M.; Buckley, Martha W.; Fukumori, Ichiro

2017-09-01

The subpolar North Atlantic (SPNA) is subject to strong decadal variability, with implications for surface climate and its predictability. In 2004-2005, SPNA decadal upper ocean and sea-surface temperature trends reversed from warming during 1994-2004 to cooling over 2005-2015. This recent decadal trend reversal in SPNA ocean heat content (OHC) is studied using a physically consistent, observationally constrained global ocean state estimate covering 1992-2015. The estimate's physical consistency facilitates quantitative causal attribution of ocean variations. Closed heat budget diagnostics reveal that the SPNA OHC trend reversal is the result of heat advection by midlatitude ocean circulation. Kinematic decompositions reveal that changes in the deep and intermediate vertical overturning circulation cannot account for the trend reversal, but rather ocean heat transports by horizontal gyre circulations render the primary contributions. The shift in horizontal gyre advection reflects anomalous circulation acting on the mean temperature gradients. Maximum covariance analysis (MCA) reveals strong covariation between the anomalous horizontal gyre circulation and variations in the local wind stress curl, suggestive of a Sverdrup response. Results have implications for decadal predictability.

Effectiveness and Sensitivity of the Arctic Observing Network in a Coupled Ocean-Sea Ice State Estimation Framework

NASA Astrophysics Data System (ADS)

Nguyen, A. T.; Heimbach, P.; Garg, V.; Ocana, V.

2016-12-01

Over the last few decades, various agencies have invested heavily in the development and deployment of Arctic ocean and sea ice observing platforms, especially moorings, profilers, gliders, and satellite-based instruments. These observational assets are heterogeneous in terms of variables sampled and spatio-temporal coverage, which calls for a dynamical synthesis framework of the diverse data streams. Here we introduce an adjoint-based Arctic Subpolar gyre sTate estimate (ASTE), a medium resolution model-data synthesis that leverages all the possible observational assets. Through an established formal state and parameter estimation framework, the ASTE framework produces a 2002-present ocean-sea ice state that can be used to address Arctic System science questions. It is dynamically and kinematically consistent with known equations of motion and consistent with observations. Four key aspects of ASTE will be discussed: (1) How well is ASTE constrained by the existing observations; (2) which data most effectively constrain the system, and what impact on the solution does spatial and temporal coverage have; (3) how much information does one set of observation (e.g. Fram Strait heat transport) carry about a remote, but dynamically linked component (e.g. heat content in the Beaufort Gyre); and (4) how can the framework be used to assess the value of hypothetical observations in constraining poorly observed parts of the Arctic Ocean and the implied mechanisms responsible for the changes occurring in the Arctic. We will discuss the suggested geographic distribution of new observations to maximize the impact on improving our understanding of the general circulation, water mass distribution and hydrographic changes in the Arctic.

An investigation of the observability of ocean-surface parameters using GEOS-3 backscatter data

NASA Technical Reports Server (NTRS)

Miller, L. S.; Priester, R. W.

1978-01-01

The degree to which ocean surface roughness can be synoptically observed through use of the information extracted from the GEOS-3 backscattered waveform data was evaluated. Algorithms are given for use in estimating the radar sensed waveheight distribution or ocean-surface impulse response. Other factors discussed include comparisons between theoretical and experimental radar cross section values, sea state bias effects, spatial variability of significant waveheight data, and sensor-related considerations.

Assessment of Energy Production Potential from Ocean Currents along the United States Coastline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haas, Kevin

Increasing energy consumption and depleting reserves of fossil fuels have resulted in growing interest in alternative renewable energy from the ocean. Ocean currents are an alternative source of clean energy due to their inherent reliability, persistence and sustainability. General ocean circulations exist in the form of large rotating ocean gyres, and feature extremely rapid current flow in the western boundaries due to the Coriolis Effect. The Gulf Stream system is formed by the western boundary current of the North Atlantic Ocean that flows along the east coastline of the United States, and therefore is of particular interest as a potentialmore » energy resource for the United States. This project created a national database of ocean current energy resources to help advance awareness and market penetration in ocean current energy resource assessment. The database, consisting of joint velocity magnitude and direction probability histograms, was created from data created by seven years of numerical model simulations. The accuracy of the database was evaluated by ORNL?s independent validation effort documented in a separate report. Estimates of the total theoretical power resource contained in the ocean currents were calculated utilizing two separate approaches. Firstly, the theoretical energy balance in the Gulf Stream system was examined using the two-dimensional ocean circulation equations based on the assumptions of the Stommel model for subtropical gyres with the quasi-geostrophic balance between pressure gradient, Coriolis force, wind stress and friction driving the circulation. Parameters including water depth, natural dissipation rate and wind stress are calibrated in the model so that the model can reproduce reasonable flow properties including volume flux and energy flux. To represent flow dissipation due to turbines additional turbine drag coefficient is formulated and included in the model. Secondly, to determine the reasonableness of the total power estimates from the Stommel model and to help determine the size and capacity of arrays necessary to extract the maximum theoretical power, further estimates of the available power based on the distribution of the kinetic power density in the undisturbed flow was completed. This used estimates of the device spacing and scaling to sum up the total power that the devices would produce. The analysis has shown that considering extraction over a region comprised of the Florida Current portion of the Gulf Stream system, the average power dissipated ranges between 4-6 GW with a mean around 5.1 GW. This corresponds to an average of approximately 45 TWh/yr. However, if the extraction area comprises the entire portion of the Gulf Stream within 200 miles of the US coastline from Florida to North Carolina, the average power dissipated becomes 18.6 GW or 163 TWh/yr. A web based GIS interface, http://www.oceancurrentpower.gatech.edu/, was developed for dissemination of the data. The website includes GIS layers of monthly and yearly mean ocean current velocity and power density for ocean currents along the entire coastline of the United States, as well as joint and marginal probability histograms for current velocities at a horizontal resolution of 4-7 km with 10-25 bins over depth. Various tools are provided for viewing, identifying, filtering and downloading the data.« less

Estimating ocean production from satellite-derived chlorophyll - Insights from the EASTROPAC data set

NASA Technical Reports Server (NTRS)

Eppley, R. W.; Stewart, E.; Abbott, M. R.; Owen, R. W.

1985-01-01

The EASTROPAC expedition took place in 1967-68 in the eastern tropical Pacific Ocean. Primary production was related to near-surface chlorophyll in these data. Much of the variability in the relation was due to the light-history of the phytoplankton and its photoadaptive state. This was due to changes in the depth of mixing of the surface waters more than changes in insolation. Accurate estimates of production from satellite chlorophyll measurements may require knowledge of the temporal and spatial variation in mixing of this region.

Completing the Feedback Loop: The Impact of Chlorophyll Data Assimilation on the Ocean State

NASA Technical Reports Server (NTRS)

Borovikov, Anna; Keppenne, Christian; Kovach, Robin

2015-01-01

In anticipation of the integration of a full biochemical model into the next generation GMAO coupled system, an intermediate solution has been implemented to estimate the penetration depth (1Kd_PAR) of ocean radiation based on the chlorophyll concentration. The chlorophyll is modeled as a tracer with sources-sinks coming from the assimilation of MODIS chlorophyll data. Two experiments were conducted with the coupled ocean-atmosphere model. In the first, climatological values of Kpar were used. In the second, retrieved daily chlorophyll concentrations were assimilated and Kd_PAR was derived according to Morel et al (2007). No other data was assimilated to isolate the effects of the time-evolving chlorophyll field. The daily MODIS Kd_PAR product was used to validate the skill of the penetration depth estimation and the MERRA-OCEAN re-analysis was used as a benchmark to study the sensitivity of the upper ocean heat content and vertical temperature distribution to the chlorophyll input. In the experiment with daily chlorophyll data assimilation, the penetration depth was estimated more accurately, especially in the tropics. As a result, the temperature bias of the model was reduced. A notably robust albeit small (2-5 percent) improvement was found across the equatorial Pacific ocean, which is a critical region for seasonal to inter-annual prediction.

Identifying meaningful trends in Atlantic water temperature from sparse in situ hydrographic observations from the periphery of the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Fenty, I. G.; Willis, J. K.; Rignot, E. J.

2016-12-01

Motivated by the need to understand the connection between the warming North Atlantic Ocean and increasing ice mass loss from the Greenland Ice Sheet, in 2015 we initiated "Oceans Melting Greenland" (OMG), a 5-year NASA sub-orbital mission. One component of OMG is a once-yearly sampling of full-depth vertical profiles of ocean temperature and salinity around Greenland's continental shelf at 250 locations. These measurements have the potential to provide an unprecedented view of ocean properties around Greenland, especially the warm, salty subsurface Atlantic Waters that have been implicated in tidewater glacier retreat, acceleration, and thinning. However, OMG'S ocean measurements are essentially large-scale synoptic snapshots of an ocean state whose characteristic scales of temporal and spatial variability around Greenland are largely unknown. In this talk we discuss how high-resolution numerical ocean modelling is being employed to quantitatively estimate the region's natural hydrographic variability for the dual purposes of (1) informing our pan-Greenland ocean sampling strategy and (2) informing our interpretation of temperature trends in the data. OMG hydrographic shelf data collected in ship-based CTDs (2015, 2016) and Airborne eXpendable CTDs (2016) will be examined in the context of this estimated ocean variability.

Estimation of sum-to-one constrained parameters with non-Gaussian extensions of ensemble-based Kalman filters: application to a 1D ocean biogeochemical model

NASA Astrophysics Data System (ADS)

Simon, E.; Bertino, L.; Samuelsen, A.

2011-12-01

Combined state-parameter estimation in ocean biogeochemical models with ensemble-based Kalman filters is a challenging task due to the non-linearity of the models, the constraints of positiveness that apply to the variables and parameters, and the non-Gaussian distribution of the variables in which they result. Furthermore, these models are sensitive to numerous parameters that are poorly known. Previous works [1] demonstrated that the Gaussian anamorphosis extensions of ensemble-based Kalman filters were relevant tools to perform combined state-parameter estimation in such non-Gaussian framework. In this study, we focus on the estimation of the grazing preferences parameters of zooplankton species. These parameters are introduced to model the diet of zooplankton species among phytoplankton species and detritus. They are positive values and their sum is equal to one. Because the sum-to-one constraint cannot be handled by ensemble-based Kalman filters, a reformulation of the parameterization is proposed. We investigate two types of changes of variables for the estimation of sum-to-one constrained parameters. The first one is based on Gelman [2] and leads to the estimation of normal distributed parameters. The second one is based on the representation of the unit sphere in spherical coordinates and leads to the estimation of parameters with bounded distributions (triangular or uniform). These formulations are illustrated and discussed in the framework of twin experiments realized in the 1D coupled model GOTM-NORWECOM with Gaussian anamorphosis extensions of the deterministic ensemble Kalman filter (DEnKF). [1] Simon E., Bertino L. : Gaussian anamorphosis extension of the DEnKF for combined state and parameter estimation : application to a 1D ocean ecosystem model. Journal of Marine Systems, 2011. doi :10.1016/j.jmarsys.2011.07.007 [2] Gelman A. : Method of Moments Using Monte Carlo Simulation. Journal of Computational and Graphical Statistics, 4, 1, 36-54, 1995.

An Implementation of Icebergs in CICE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Comeau, Darin S.

2012-06-25

There is an estimated global iceberg calving flux of {approx} 2300 Gt yr{sup -1}, about 90% of which occurs in the Antarctic. Icebergs provide an important vehicle for freshwater injection into the polar oceans, an estimated 60-80% of net freshwater flux from land ice to oceans in the Antarctic. Icebergs interact dynamically with surrounding sea ice, potentially affecting marine eco systems. Icebergs lose mass primarily through three mechanisms, described by empirical relations: (1) Basal melting - turbulence due to differences in oceanic and iceberg motion (also function of difference in temperature between ocean and iceberg); (2) Lateral melting - buoyantmore » convection along sidewalls of iceberg (function of ocean temperature); and (3) Erosion due to waves (function of sea state and ocean temperature). We have incorporated an iceberg parameterization into the CICE model where sea ice responds to the icebergs, rather than being a static forcing term. Icebergs produce highly localized anomalies in sea ice concentration, thickness, and strength. Summer sea ice meltback limits these effects. Icebergs shed freshwater as they move, transporting freshwater away from the coast.« less

Antarctic icebergs melt over the Southern Ocean : Climatology and impact on sea ice

NASA Astrophysics Data System (ADS)

Merino, Nacho; Le Sommer, Julien; Durand, Gael; Jourdain, Nicolas C.; Madec, Gurvan; Mathiot, Pierre; Tournadre, Jean

2016-08-01

Recent increase in Antarctic freshwater release to the Southern Ocean is suggested to contribute to change in water masses and sea ice. However, climate models differ in their representation of the freshwater sources. Recent improvements in altimetry-based detection of small icebergs and in estimates of the mass loss of Antarctica may help better constrain the values of Antarctic freshwater releases. We propose a model-based seasonal climatology of iceberg melt over the Southern Ocean using state-of-the-art observed glaciological estimates of the Antarctic mass loss. An improved version of a Lagrangian iceberg model is coupled with a global, eddy-permitting ocean/sea ice model and compared to small icebergs observations. Iceberg melt increases sea ice cover, about 10% in annual mean sea ice volume, and decreases sea surface temperature over most of the Southern Ocean, but with distinctive regional patterns. Our results underline the importance of improving the representation of Antarctic freshwater sources. This can be achieved by forcing ocean/sea ice models with a climatological iceberg fresh-water flux.

Closing the Seasonal Ocean Surface Temperature Balance in the Eastern Tropical Oceans from Remote Sensing and Model Reanalyses

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Clayson, Carol A.

2012-01-01

The Eastern tropical ocean basins are regions of significant atmosphere-ocean interaction and are important to variability across subseasonal to decadal time scales. The numerous physical processes at play in these areas strain the abilities of coupled general circulation models to accurately reproduce observed upper ocean variability. Furthermore, limitations in the observing system of important terms in the surface temperature balance (e.g., turbulent and radiative heat fluxes, advection) introduce uncertainty into the analyses of processes controlling sea surface temperature variability. This study presents recent efforts to close the surface temperature balance through estimation of the terms in the mixed layer temperature budget using state-of-the-art remotely sensed and model-reanalysis derived products. A set of twelve net heat flux estimates constructed using combinations of radiative and turbulent heat flux products - including GEWEX-SRB, ISCCP-SRF, OAFlux, SeaFlux, among several others - are used with estimates of oceanic advection, entrainment, and mixed layer depth variability to investigate the seasonal variability of ocean surface temperatures. Particular emphasis is placed on how well the upper ocean temperature balance is, or is not, closed on these scales using the current generation of observational and model reanalysis products. That is, the magnitudes and spatial variability of residual imbalances are addressed. These residuals are placed into context within the current uncertainties of the surface net heat fluxes and the role of the mixed layer depth variability in scaling the impact of those uncertainties, particularly in the shallow mixed layers of the Eastern tropical ocean basins.

The Buoyancy Budget With a Nonlinear Equation of State

NASA Astrophysics Data System (ADS)

Hieronymus, M. H.; Nycander, J.

2012-12-01

There has been a number of studies focusing on different aspects of having a nonlinear equation of state for seawater. Amongst other things it has been shown that the nonlinear equation of state has implications for the oceanic energy budget and that nonlinear processes can be a significant source of dense water production. This presentation will focus on the oceanic buoyancy budget. The nonlinear equation of state of seawater can introduce a sink or source of buoyancy when water parcels of unequal salinities and temperatures are mixed. A common example is the process known as cabbeling, which is responsible for forming a water mass that is denser than the original constituents in a mixture of two water masses with equal densities but different salinities and temperatures. This presentation will contain quantitative estimates of these nonlinear effects on the buoyancy budget of the global ocean. Because of these nonlinear effects there is a net sink of buoyancy in the oceans interior and the size of this sink can be determined from the buoyancy fluxes at the ocean boundaries. These boundary buoyancy fluxes are calculated using two surface heat flux climatologies one based on in situ measurements, the other on a reanalysis and in both cases using a nonlinear equation of state. The presentation also treats the buoyancy budget in the State of the art ocean model Nucleus for European Modelling of the Ocean (NEMO) and the results from NEMO are seen to be in good agreement with the buoyancy budgets based on the heat flux climatologies. Using the ocean model is a good complement to the surface flux climatologies, because in NEMO the buoyancy fluxes can be evaluated at all vertical model levels. This means that the vertical distribution of the buoyancy sink can be looked into. The results from NEMO shows that in large parts of the ocean the nonlinear buoyancy sink is the largest contribution to the buoyancy budget.

Vertical Redistribution of Ocean Salt Content

NASA Astrophysics Data System (ADS)

Liang, X.; Liu, C.; Ponte, R. M.; Piecuch, C. G.

2017-12-01

Ocean salinity is an important proxy for change and variability in the global water cycle. Multi-decadal trends have been observed in both surface and subsurface salinity in the past decades, and are usually attributed to the change in air-sea freshwater flux. Although air-sea freshwater flux, a major component of the global water cycle, certainly contributes to the change in surface and upper ocean salinity, the salt redistribution inside the ocean can affect the surface and upper ocean salinity as well. Also, the mechanisms controlling the surface and upper ocean salinity changes likely depend on timescales. Here we examined the ocean salinity changes as well as the contribution of the vertical redistribution of salt with a 20-year dynamically consistent and data-constrained ocean state estimate (ECCO: Estimating Circulation and Climate of the Ocean). A decrease in the spatial mean upper ocean salinity and an upward salt flux inside the ocean were observed. These findings indicate that over 1992-2011, surface freshwater fluxes contribute to the decrease in spatial mean upper ocean salinity and are partly compensated by the vertical redistribution of salt inside the ocean. Between advection and diffusion, the two major processes determining the vertical exchange of salt, the advective term at different depths shows a downward transport, while the diffusive term is the dominant upward transport contributor. These results suggest that the salt transport in the ocean interior should be considered in interpreting the observed surface and upper ocean salinity changes, as well as inferring information about the changes in the global water cycle.

Theoretical Advances in Sequential Data Assimilation for the Atmosphere and Oceans

NASA Astrophysics Data System (ADS)

Ghil, M.

2007-05-01

We concentrate here on two aspects of advanced Kalman--filter-related methods: (i) the stability of the forecast- assimilation cycle, and (ii) parameter estimation for the coupled ocean-atmosphere system. The nonlinear stability of a prediction-assimilation system guarantees the uniqueness of the sequentially estimated solutions in the presence of partial and inaccurate observations, distributed in space and time; this stability is shown to be a necessary condition for the convergence of the state estimates to the true evolution of the turbulent flow. The stability properties of the governing nonlinear equations and of several data assimilation systems are studied by computing the spectrum of the associated Lyapunov exponents. These ideas are applied to a simple and an intermediate model of atmospheric variability and we show that the degree of stabilization depends on the type and distribution of the observations, as well as on the data assimilation method. These results represent joint work with A. Carrassi, A. Trevisan and F. Uboldi. Much is known by now about the main physical mechanisms that give rise to and modulate the El-Nino/Southern- Oscillation (ENSO), but the values of several parameters that enter these mechanisms are an important unknown. We apply Extended Kalman Filtering (EKF) for both model state and parameter estimation in an intermediate, nonlinear, coupled ocean-atmosphere model of ENSO. Model behavior is very sensitive to two key parameters: (a) "mu", the ocean-atmosphere coupling coefficient between the sea-surface temperature (SST) and wind stress anomalies; and (b) "delta-s", the surface-layer coefficient. Previous work has shown that "delta- s" determines the period of the model's self-sustained oscillation, while "mu' measures the degree of nonlinearity. Depending on the values of these parameters, the spatio-temporal pattern of model solutions is either that of a delayed oscillator or of a westward propagating mode. Assimilation of SST data from the NCEP- NCAR Reanalysis-2 shows that the parameters can vary on fairly short time scales and switch between values that approximate the two distinct modes of ENSO behavior. Rapid adjustments of these parameters occur, in particular, during strong ENSO events. Ways to apply EKF parameter estimation efficiently to state-of-the-art coupled ocean-atmosphere GCMs will be discussed. These results arise from joint work with D. Kondrashov and C.-j. Sun.

Atmospheric Models for Over-Ocean Propagation Loss

DTIC Science & Technology

2015-05-15

Atmospheric Models For Over-Ocean Propagation Loss Bruce McGuffin1 MIT Lincoln Laboratory Introduction Air -to-surface radio links differ from...from radiosonde profiles collected along the Atlantic coast of the United States, in order to accurately estimate high-reliability SHF/EHF air -to...predict required link performance to achieve high reliability at different locations and times of year. Data Acquisition Radiosonde balloons are

Isotopic Techniques for Assessment of Groundwater Discharge to the Coastal Ocean

DTIC Science & Technology

2002-09-30

of the groundwater tracer. This may then be divided by the estimated groundwater Ra concentration to derive a water flux. 3...residence times of coastal waters . If one assumes that the source of short-lived radium isotopes is groundwater with a constant isotopic composition...Isotopic Techniques for Assessment of Groundwater Discharge to the Coastal Ocean William C. Burnett Department of Oceanography Florida State

Inverse-model estimates of the ocean's coupled phosphorus, silicon, and iron cycles

NASA Astrophysics Data System (ADS)

Pasquier, Benoît; Holzer, Mark

2017-09-01

The ocean's nutrient cycles are important for the carbon balance of the climate system and for shaping the ocean's distribution of dissolved elements. Dissolved iron (dFe) is a key limiting micronutrient, but iron scavenging is observationally poorly constrained, leading to large uncertainties in the external sources of iron and hence in the state of the marine iron cycle. Here we build a steady-state model of the ocean's coupled phosphorus, silicon, and iron cycles embedded in a data-assimilated steady-state global ocean circulation. The model includes the redissolution of scavenged iron, parameterization of subgrid topography, and small, large, and diatom phytoplankton functional classes. Phytoplankton concentrations are implicitly represented in the parameterization of biological nutrient utilization through an equilibrium logistic model. Our formulation thus has only three coupled nutrient tracers, the three-dimensional distributions of which are found using a Newton solver. The very efficient numerics allow us to use the model in inverse mode to objectively constrain many biogeochemical parameters by minimizing the mismatch between modeled and observed nutrient and phytoplankton concentrations. Iron source and sink parameters cannot jointly be optimized because of local compensation between regeneration, recycling, and scavenging. We therefore consider a family of possible state estimates corresponding to a wide range of external iron source strengths. All state estimates have a similar mismatch with the observed nutrient concentrations and very similar large-scale dFe distributions. However, the relative contributions of aeolian, sedimentary, and hydrothermal iron to the total dFe concentration differ widely depending on the sources. Both the magnitude and pattern of the phosphorus and opal exports are well constrained, with global values of 8. 1 ± 0. 3 Tmol P yr-1 (or, in carbon units, 10. 3 ± 0. 4 Pg C yr-1) and 171. ± 3. Tmol Si yr-1. We diagnose the phosphorus and opal exports supported by aeolian, sedimentary, and hydrothermal iron. The geographic patterns of the export supported by each iron type are well constrained across the family of state estimates. Sedimentary-iron-supported export is important in shelf and large-scale upwelling regions, while hydrothermal iron contributes to export mostly in the Southern Ocean. The fraction of the global export supported by a given iron type varies systematically with its fractional contribution to the total iron source. Aeolian iron is most efficient in supporting export in the sense that its fractional contribution to export exceeds its fractional contribution to the total source. Per source-injected molecule, aeolian iron supports 3. 1 ± 0. 8 times more phosphorus export and 2. 0 ± 0. 5 times more opal export than the other iron types. Conversely, per injected molecule, sedimentary and hydrothermal iron support 2. 3 ± 0. 6 and 4. ± 2. times less phosphorus export, and 1. 9 ± 0. 5 and 2. ± 1. times less opal export than the other iron types.

Estimation of mean sea surfaces in the North Atlantic, the Pacific and the Indian Ocean using GEOS-3 altimeter data

NASA Technical Reports Server (NTRS)

Marsh, J. G.; Martin, T. V.; Mccarthy, J. J.; Chovitz, P. J.

1979-01-01

The sea surface heights above the reference ellipsoid were determined for several regions of the world's ocean using data from the radar altimeter on board the GEOS-3 satellite in conjunction with precise orbital position information derived from laser data. The resolution of the estimated sea surfaces varied from 0.25 degrees off the east coast of the United States to about 2 degrees in the Indian Ocean near Australia. The rms crossover discrepancy after adjustment varied from 30 cm to 70 cm depending on geographic location. Comparison of the altimeter derived mean sea surface in the North Atlantic with the 5 x 5 ft GEM-8 detailed gravimetric geoid indicated a relative consistency of better than one meter.

Vertical Eddy Diffusivity as a Control Parameter in the Tropical Pacific Ocean

NASA Astrophysics Data System (ADS)

Martinez Avellaneda, N.; Cornuelle, B.; Mazloff, M. R.; Stammer, D.

2012-12-01

Ocean models suffer from errors in the treatment of turbulent sub-grid scale motions causing mixing and energy dissipation. Unrealistic small-scale features in models can have large-scale consequences, such as biases in the upper ocean temperature, a symptom of poorly-simulated upwelling, currents and air-sea interactions. This is of special importance in the tropical Pacific Ocean, which is home to energetic air-sea interactions that affect global climate. It has been shown in a number of studies that the simulated ENSO variability is highly dependent on the state of the ocean (e.g.: background mixing). Moreover, the magnitude of the vertical numerical diffusion is of primary importance in properly reproducing the Pacific equatorial thermocline. Yet, it is a common practice to use spatially uniform mixing parameters in ocean simulations. This work is part of a NASA-funded project to estimate the space-varying ocean mixing coefficients in an eddy-permitting model of the tropical Pacific. The usefulness of assimilation techniques in estimating mixing parameters has been previously explored (e.g.: Stammer, 2005, Ferreira et al., 2005). The authors also demonstrated that the spatial structure of the Equatorial Undercurrent (EUC) could be improved by adjusting wind-stress and surface buoyancy flux within their error bounds. In our work, we address the important question of whether adjusting mixing parameterizations can bring about similar improvements. To that end, an eddy-permitting state estimate for the tropical Pacific is developed using the MIT general circulation model and its adjoint where the vertical diffusivity is set as a control parameter. Complementary adjoint-based sensitivity results show strong sensitivities of the Tropical Pacific thermocline (thickness and location) and the EUC transport to the vertical diffusivity in the tropics. Argo, CTD, XBT and mooring in-situ data, as well as TMI SST and altimetry observations are assimilated in order to reduce the misfit between the model simulations and the ocean observations. Model domain topography of 1/3dgr of spatial resolution interpolated from ETOPO 2. The first and the last color levels represent regions shallower than 100m and deeper than 5000m, respectively

Streamflow from the United States into the Atlantic Ocean during 1931-1960

USGS Publications Warehouse

Bue, Conrad D.

1970-01-01

Streamflow from the United States into the Atlantic Ocean, between the international stream St. Croix River, inclusive, and Cape Sable, Fla., averaged about 355,000 cfs (cubic feet per second) during the 30-year period 1931-60, or roughly 20 percent of the water that, on the average flows out of the conterminous United States. The area drained by streams flowing into the Atlantic Ocean is about 288,000 square miles, including the Canadian part of the St. Croix and Connecticut River basins, or a little less than 10 percent of the area of the conterminous United States. Hence, the average streamflow into the Atlantic Ocean, in terms of cubic feet per second per square mile, is about twice the national average of the flow that leaves the conterminous United States. Flow from about three-fourths of the area draining into the Atlantic Ocean is gaged at streamflow measuring stations of the U.S. Geological Survey. The remaining one-fourth of the drainage area consists mostly of low-lying coastal areas from which the flow was estimated, largely on the basis of nearby gaging stations. Streamflow, in terms of cubic feet per second per square mile, decreases rather progressively from north to south. It averages nearly 2 cfs along the Maine coast, about 1 cfs along the North Carolina coast, and about 0.9 cfs along the Florida coast.

Global Electric Circuit Implications of Total Current Measurements over Electrified Clouds

NASA Technical Reports Server (NTRS)

Mach, Douglas M.; Blakeslee, Richard J.; Bateman, Monte G.

2009-01-01

We determined total conduction (Wilson) currents and flash rates for 850 overflights of electrified clouds spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, with and without lightning, and with positive and negative Wilson currents. We combined these individual storm overflight statistics with global diurnal lightning variation data from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to estimate the thunderstorm and electrified shower cloud contributions to the diurnal variation in the global electric circuit. The contributions to the global electric circuit from lightning producing clouds are estimated by taking the mean current per flash derived from the overflight data for land and ocean overflights and combining it with the global lightning rates (for land and ocean) and their diurnal variation derived from the LIS/OTD data. We estimate the contribution of non-lightning producing electrified clouds by assuming several different diurnal variations and total non-electrified storm counts to produce estimates of the total storm currents (lightning and non-lightning producing storms). The storm counts and diurnal variations are constrained so that the resultant total current diurnal variation equals the diurnal variation in the fair weather electric field (+/-15%). These assumptions, combined with the airborne and satellite data, suggest that the total mean current in the global electric circuit ranges from 2.0 to 2.7 kA, which is greater than estimates made by others using other methods.

Improving Global Net Surface Heat Flux with Ocean Reanalysis

NASA Astrophysics Data System (ADS)

Carton, J.; Chepurin, G. A.; Chen, L.; Grodsky, S.

2017-12-01

This project addresses the current level of uncertainty in surface heat flux estimates. Time mean surface heat flux estimates provided by atmospheric reanalyses differ by 10-30W/m2. They are generally unbalanced globally, and have been shown by ocean simulation studies to be incompatible with ocean temperature and velocity measurements. Here a method is presented 1) to identify the spatial and temporal structure of the underlying errors and 2) to reduce them by exploiting hydrographic observations and the analysis increments produced by an ocean reanalysis using sequential data assimilation. The method is applied to fluxes computed from daily state variables obtained from three widely used reanalyses: MERRA2, ERA-Interim, and JRA-55, during an eight year period 2007-2014. For each of these seasonal heat flux errors/corrections are obtained. In a second set of experiments the heat fluxes are corrected and the ocean reanalysis experiments are repeated. This second round of experiments shows that the time mean error in the corrected fluxes is reduced to within ±5W/m2 over the interior subtropical and midlatitude oceans, with the most significant changes occuring over the Southern Ocean. The global heat flux imbalance of each reanalysis is reduced to within a few W/m2 with this single correction. Encouragingly, the corrected forms of the three sets of fluxes are also shown to converge. In the final discussion we present experiments beginning with a modified form of the ERA-Int reanalysis, produced by the DAKKAR program, in which state variables have been individually corrected based on independent measurements. Finally, we discuss the separation of flux error from model error.

Ocean N2O Emissions : Recent Global Estimates and Anthropogenically Influenced Changes

NASA Astrophysics Data System (ADS)

Suntharalingam, P.; Buithenuis, E.; Andrews, O.; Le Quere, C.

2016-12-01

Oceanic N2O is produced by microbial activity during organic matter cycling in the subsurface ocean; its production mechanisms display sensitivity to ambient oxygen level. In the oxic ocean, N2O is produced as a byproduct during the oxidation of ammonia to nitrate, mediated by ammonia oxidizing bacteria and archea. N2O is also produced and consumed in sub-oxic and anoxic waters through the action of marine denitrifiers during the multi-step reduction of nitrate to gaseous nitrogen. The oceanic N2O distribution therefore displays significant heterogeneity with background levels of 10-20 nmol/l in the well-oxygenated ocean basins, high concentrations (> 40 nmol/l) in hypoxic waters, and N2O depletion in the core of ocean oxygen minimum zones (OMZs). Oceanic N2O emissions are estimated to account for up to a third of the pre-industrial N2O fluxes to the atmosphere, however the natural cycle of ocean N2O has been perturbed in recent decades by inputs of anthropogenically derived nutrient, and by the impacts of climate change. Anthropogenic nitrogen inputs (e.g., NOx and NHy from fossil fuel combustion and agricultural fertilizer) enter the ocean via atmospheric deposition and riverine fluxes, influencing oceanic N2O production via their impact on the marine organic matter cycle. In addition, climate variations associated with surface ocean warming affect oceanic circulation and nutrient transport pathways, influencing marine productivity and the ventilation of oxygen minimum zones. Recent studies have suggested that possible expansion of oceanic OMZs in a warming climate could lead to significant changes in N2O production and fluxes from these regions. We will summarise the current state of knowledge on the ocean N2O budget and net flux to the atmosphere. Recently reported estimates have been based on (i) empirical relationships derived from ocean tracer data (e.g., involving excess N2O and Apparent Oxygen Utilization (AOU) correlations), (ii) ocean biogeochemical models, and (iii) air-sea flux calculations which combine surface ocean N2O measurements with gas-exchange relationships. We will also present results from ongoing ocean biogeochemistry model analyses evaluating the separate influences of climate variation and anthropogenic nutrient inputs on ocean N2O emissions for recent decades.

Developing priority variables ("ecosystem Essential Ocean Variables" - eEOVs) for observing dynamics and change in Southern Ocean ecosystems

NASA Astrophysics Data System (ADS)

Constable, Andrew J.; Costa, Daniel P.; Schofield, Oscar; Newman, Louise; Urban, Edward R.; Fulton, Elizabeth A.; Melbourne-Thomas, Jessica; Ballerini, Tosca; Boyd, Philip W.; Brandt, Angelika; de la Mare, Willaim K.; Edwards, Martin; Eléaume, Marc; Emmerson, Louise; Fennel, Katja; Fielding, Sophie; Griffiths, Huw; Gutt, Julian; Hindell, Mark A.; Hofmann, Eileen E.; Jennings, Simon; La, Hyoung Sul; McCurdy, Andrea; Mitchell, B. Greg; Moltmann, Tim; Muelbert, Monica; Murphy, Eugene; Press, Anthony J.; Raymond, Ben; Reid, Keith; Reiss, Christian; Rice, Jake; Salter, Ian; Smith, David C.; Song, Sun; Southwell, Colin; Swadling, Kerrie M.; Van de Putte, Anton; Willis, Zdenka

2016-09-01

Reliable statements about variability and change in marine ecosystems and their underlying causes are needed to report on their status and to guide management. Here we use the Framework on Ocean Observing (FOO) to begin developing ecosystem Essential Ocean Variables (eEOVs) for the Southern Ocean Observing System (SOOS). An eEOV is a defined biological or ecological quantity, which is derived from field observations, and which contributes significantly to assessments of Southern Ocean ecosystems. Here, assessments are concerned with estimating status and trends in ecosystem properties, attribution of trends to causes, and predicting future trajectories. eEOVs should be feasible to collect at appropriate spatial and temporal scales and are useful to the extent that they contribute to direct estimation of trends and/or attribution, and/or development of ecological (statistical or simulation) models to support assessments. In this paper we outline the rationale, including establishing a set of criteria, for selecting eEOVs for the SOOS and develop a list of candidate eEOVs for further evaluation. Other than habitat variables, nine types of eEOVs for Southern Ocean taxa are identified within three classes: state (magnitude, genetic/species, size spectrum), predator-prey (diet, foraging range), and autecology (phenology, reproductive rate, individual growth rate, detritus). Most candidates for the suite of Southern Ocean taxa relate to state or diet. Candidate autecological eEOVs have not been developed other than for marine mammals and birds. We consider some of the spatial and temporal issues that will influence the adoption and use of eEOVs in an observing system in the Southern Ocean, noting that existing operations and platforms potentially provide coverage of the four main sectors of the region - the East and West Pacific, Atlantic and Indian. Lastly, we discuss the importance of simulation modelling in helping with the design of the observing system in the long term. Regional boundary: south of 30°S.

Comparison of MERRA-2 and ECCO-v4 ocean surface heat fluxes: Consequences of different forcing feedbacks on ocean circulation and implications for climate data assimilation.

NASA Astrophysics Data System (ADS)

Strobach, E.; Molod, A.; Menemenlis, D.; Forget, G.; Hill, C. N.; Campin, J. M.; Heimbach, P.

2017-12-01

Forcing ocean models with reanalysis data is a common practice in ocean modeling. As part of this practice, prescribed atmospheric state variables and interactive ocean SST are used to calculate fluxes between the ocean and the atmosphere. When forcing an ocean model with reanalysis fields, errors in the reanalysis data, errors in the ocean model and errors in the forcing formulation will generate a different solution compared to other ocean reanalysis solutions (which also have their own errors). As a first step towards a consistent coupled ocean-atmosphere reanalysis, we compare surface heat fluxes from a state-of-the-art atmospheric reanalysis, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), to heat fluxes from a state-of-the-art oceanic reanalysis, the Estimating the Circulation and Climate of the Ocean Version 4, Release 2 (ECCO-v4). Then, we investigate the errors associated with the MITgcm ocean model in its ECCO-v4 ocean reanalysis configuration (1992-2011) when it is forced with MERRA-2 atmospheric reanalysis fields instead of with the ECCO-v4 adjoint optimized ERA-interim state variables. This is done by forcing ECCO-v4 ocean with and without feedbacks from MERRA-2 related to turbulent fluxes of heat and moisture and the outgoing long wave radiation. In addition, we introduce an intermediate forcing method that includes only the feedback from the interactive outgoing long wave radiation. The resulting ocean circulation is compared with ECCO-v4 reanalysis and in-situ observations. We show that, without feedbacks, imbalances in the energy and the hydrological cycles of MERRA-2 (which are directly related to the fact it was created without interactive ocean) result in considerable SST drifts and a large reduction in sea level. The bulk formulae and interactive outgoing long wave radiation, although providing air-sea feedbacks and reducing model-data misfit, strongly relax the ocean to observed SST and may result in unwanted features such as large change in the water budget. These features have implications in on desired forcing recipe to be used. The results strongly and unambiguously argue for next generation data assimilation climate studies to involve fully coupled systems.

Reconciliation of the carbon budget in the ocean's twilight zone.

PubMed

Giering, Sarah L C; Sanders, Richard; Lampitt, Richard S; Anderson, Thomas R; Tamburini, Christian; Boutrif, Mehdi; Zubkov, Mikhail V; Marsay, Chris M; Henson, Stephanie A; Saw, Kevin; Cook, Kathryn; Mayor, Daniel J

2014-03-27

Photosynthesis in the surface ocean produces approximately 100 gigatonnes of organic carbon per year, of which 5 to 15 per cent is exported to the deep ocean. The rate at which the sinking carbon is converted into carbon dioxide by heterotrophic organisms at depth is important in controlling oceanic carbon storage. It remains uncertain, however, to what extent surface ocean carbon supply meets the demand of water-column biota; the discrepancy between known carbon sources and sinks is as much as two orders of magnitude. Here we present field measurements, respiration rate estimates and a steady-state model that allow us to balance carbon sources and sinks to within observational uncertainties at the Porcupine Abyssal Plain site in the eastern North Atlantic Ocean. We find that prokaryotes are responsible for 70 to 92 per cent of the estimated remineralization in the twilight zone (depths of 50 to 1,000 metres) despite the fact that much of the organic carbon is exported in the form of large, fast-sinking particles accessible to larger zooplankton. We suggest that this occurs because zooplankton fragment and ingest half of the fast-sinking particles, of which more than 30 per cent may be released as suspended and slowly sinking matter, stimulating the deep-ocean microbial loop. The synergy between microbes and zooplankton in the twilight zone is important to our understanding of the processes controlling the oceanic carbon sink.

An approximate Kalman filter for ocean data assimilation: An example with an idealized Gulf Stream model

NASA Technical Reports Server (NTRS)

Fukumori, Ichiro; Malanotte-Rizzoli, Paola

1995-01-01

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter based on approximation of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudomeasurements are examined, including velocity, density, and volume transport at localized arrays and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform an empirical nudging scheme used in a previous study. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

An approximate Kalman filter for ocean data assimilation: An example with an idealized Gulf Stream model

NASA Astrophysics Data System (ADS)

Fukumori, Ichiro; Malanotte-Rizzoli, Paola

1995-04-01

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kaiman filter based on approximations of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudomeasurements are examined, including velocity, density, and volume transport at localized arrays and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform an empirical nudging scheme used in a previous study. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

Offshore remote sensing of the ocean by stereo vision systems

NASA Astrophysics Data System (ADS)

Gallego, Guillermo; Shih, Ping-Chang; Benetazzo, Alvise; Yezzi, Anthony; Fedele, Francesco

2014-05-01

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting oberved waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss furure lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage. Multiresolution and short-time approaches would improve efficiency and scalability of the techniques so that wave displacements are obtained in feasible times.

A reanalysis dataset of the South China Sea.

PubMed

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992-2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability.

A reanalysis dataset of the South China Sea

PubMed Central

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

Toward the assimilation of biogeochemical data in the CMEMS BIOMER coupled physical-biogeochemical operational system

NASA Astrophysics Data System (ADS)

Lamouroux, Julien; Testut, Charles-Emmanuel; Lellouche, Jean-Michel; Perruche, Coralie; Paul, Julien

2017-04-01

The operational production of data-assimilated biogeochemical state of the ocean is one of the challenging core projects of the Copernicus Marine Environment Monitoring Service. In that framework - and with the April 2018 CMEMS V4 release as a target - Mercator Ocean is in charge of improving the realism of its global ¼° BIOMER coupled physical-biogeochemical (NEMO/PISCES) simulations, analyses and re-analyses, and to develop an effective capacity to routinely estimate the biogeochemical state of the ocean, through the implementation of biogeochemical data assimilation. Primary objectives are to enhance the time representation of the seasonal cycle in the real time and reanalysis systems, and to provide a better control of the production in the equatorial regions. The assimilation of BGC data will rely on a simplified version of the SEEK filter, where the error statistics do not evolve with the model dynamics. The associated forecast error covariances are based on the statistics of a collection of 3D ocean state anomalies. The anomalies are computed from a multi-year numerical experiment (free run without assimilation) with respect to a running mean in order to estimate the 7-day scale error on the ocean state at a given period of the year. These forecast error covariances rely thus on a fixed-basis seasonally variable ensemble of anomalies. This methodology, which is currently implemented in the "blue" component of the CMEMS operational forecast system, is now under adaptation to be applied to the biogeochemical part of the operational system. Regarding observations - and as a first step - the system shall rely on the CMEMS GlobColour Global Ocean surface chlorophyll concentration products, delivered in NRT. The objective of this poster is to provide a detailed overview of the implementation of the aforementioned data assimilation methodology in the CMEMS BIOMER forecasting system. Focus shall be put on (1) the assessment of the capabilities of this data assimilation methodology to provide satisfying statistics of the model variability errors (through space-time analysis of dedicated representers of satellite surface Chla observations), (2) the dedicated features of the data assimilation configuration that have been implemented so far (e.g. log-transformation of the analysis state, multivariate Chlorophyll-Nutrient control vector, etc.) and (3) the assessment of the performances of this future operational data assimilation configuration.

75 FR 39523 - Notice of Intent: Designation of an Ocean Dredged Material Disposal Site (ODMDS) Off the Mouth of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-09

..., capacity computer modeling results, and estimates of future proposed projects. Alternatives: The following... federal, state, and local governments, industry, non-governmental organizations, and the general public on...

The contribution of NOAA/CMDL ground-based measurements to understanding long-term stratospheric changes

NASA Astrophysics Data System (ADS)

Montzka, S. A.; Butler, J. H.; Dutton, G.; Thompson, T. M.; Hall, B.; Mondeel, D. J.; Elkins, J. W.

2005-05-01

The El-Nino/Southern-Oscillation (ENSO) dominates interannual climate variability and plays, therefore, a key role in seasonal-to-interannual prediction. Much is known by now about the main physical mechanisms that give rise to and modulate ENSO, but the values of several parameters that enter these mechanisms are an important unknown. We apply Extended Kalman Filtering (EKF) for both model state and parameter estimation in an intermediate, nonlinear, coupled ocean--atmosphere model of ENSO. The coupled model consists of an upper-ocean, reduced-gravity model of the Tropical Pacific and a steady-state atmospheric response to the sea surface temperature (SST). The model errors are assumed to be mainly in the atmospheric wind stress, and assimilated data are equatorial Pacific SSTs. Model behavior is very sensitive to two key parameters: (i) μ, the ocean-atmosphere coupling coefficient between SST and wind stress anomalies; and (ii) δs, the surface-layer coefficient. Previous work has shown that δs determines the period of the model's self-sustained oscillation, while μ measures the degree of nonlinearity. Depending on the values of these parameters, the spatio-temporal pattern of model solutions is either that of a delayed oscillator or of a westward propagating mode. Estimation of these parameters is tested first on synthetic data and allows us to recover the delayed-oscillator mode starting from model parameter values that correspond to the westward-propagating case. Assimilation of SST data from the NCEP-NCAR Reanalysis-2 shows that the parameters can vary on fairly short time scales and switch between values that approximate the two distinct modes of ENSO behavior. Rapid adjustments of these parameters occur, in particular, during strong ENSO events. Ways to apply EKF parameter estimation efficiently to state-of-the-art coupled ocean--atmosphere GCMs will be discussed.

Bayesian Inference of High-Dimensional Dynamical Ocean Models

NASA Astrophysics Data System (ADS)

Lin, J.; Lermusiaux, P. F. J.; Lolla, S. V. T.; Gupta, A.; Haley, P. J., Jr.

2015-12-01

This presentation addresses a holistic set of challenges in high-dimension ocean Bayesian nonlinear estimation: i) predict the probability distribution functions (pdfs) of large nonlinear dynamical systems using stochastic partial differential equations (PDEs); ii) assimilate data using Bayes' law with these pdfs; iii) predict the future data that optimally reduce uncertainties; and (iv) rank the known and learn the new model formulations themselves. Overall, we allow the joint inference of the state, equations, geometry, boundary conditions and initial conditions of dynamical models. Examples are provided for time-dependent fluid and ocean flows, including cavity, double-gyre and Strait flows with jets and eddies. The Bayesian model inference, based on limited observations, is illustrated first by the estimation of obstacle shapes and positions in fluid flows. Next, the Bayesian inference of biogeochemical reaction equations and of their states and parameters is presented, illustrating how PDE-based machine learning can rigorously guide the selection and discovery of complex ecosystem models. Finally, the inference of multiscale bottom gravity current dynamics is illustrated, motivated in part by classic overflows and dense water formation sites and their relevance to climate monitoring and dynamics. This is joint work with our MSEAS group at MIT.

Challenges for present and future estimates of anthropogenic carbon in the Indian Ocean

NASA Astrophysics Data System (ADS)

Goyet, C.; Touratier, F.

One of the main challenges we face today is to determine the evolution of the penetration of anthropogenic CO2 into the Indian Ocean and its impacts on marine and human life. Anthropogenic CO2 reaches the ocean via air-sea interactions as well as riverine inputs. It is then stored in the ocean and follows the oceanic circulation. As the carbon dioxide from the atmosphere penetrates into the sea, it reacts with water and acidifies the ocean. Consequently, the whole marine ecosystem is perturbed, thus potentially affecting the food web, which has, in turn, a direct impact on seafood supply for humans. Naturally, this will mainly affect the growing number of people living in coastal areas. Although anthropogenic CO2 in the ocean is identical with natural CO2 and therefore cannot be detected alone, many approaches are available today to estimate it. Since most of the results of these methods are globally in agreement, here we chose one of these methods, the tracer using oxygen, total inorganic carbon, and total alkalinity (TrOCA) approach, to compute the 3-D distribution of the anthropogenic CO2 concentrations throughout the Indian Ocean. The results of this distribution clearly illustrate the contrast between the Arabian Sea and the Bay of Bengal. They further show the importance of the southern part of this ocean that carries some anthropogenic CO2 at great depths. In order to determine the future anthropogenic impacts on the Indian Ocean, it is urgent and necessary to understand the present state. As the seawater temperature increases, how and how fast will the ocean circulation change? What will the impacts on seawater properties be? Many people are living on the bordering coasts, how will they be affected?

The ECCO Family of State Estimates: An Overview

NASA Astrophysics Data System (ADS)

Wunsch, C.

2008-12-01

The idea of ECCO (Estimating the Circulation and Climate of the Ocean)originated in the middle 1980s, when it became apparent that a global oceanographic observing system for the general circulation would become a reality as it did through the World Ocean Circulation Experiment. Observational design involved extremely diverse technologies and oceanic flow regimes. To be physically interpretable, these diverse data and physical processes would need to be combined into a useful, coherent, whole. Such a synthesis can only be done with a skillful GCM having useful resolution. ECCO originated as an experiment to demonstrate the technical feasibility of such a synthesis and to determine if any of several possible methods was preferable. In contrast to a number of other superficially similar efforts, mainly derived from weather forecasting methods, the ECCO goal was to estimate the long-term circulation mean and its variability on climate (decadal and longer) time scales in a form exactly satisfying known equations of motion. ECCO was made feasible with the simultaneous construction of a new GCM (MIT) along with the development of an automatic differentiation (AD) software tool(now called TAF) which rendered practical the method of Lagrange multipliers (called the adjoint method in oceanography). Parallel developments of simplified sequential methods (smoothers) provided an alternative, also practical, methodology. One can now use the existing (publicly available) machinery to discuss the ocean circulation and its variability. The huge variety of issues connected with the global circulation has meant that an entire family of estimates has grown up, each having different emphases (primarily global; but some primarily regional---the tropics, the Southern Ocean); some focussed on physics---the role of eddies or sea ice). The methodology leads, usefully, to intense scrutiny of data and model errors and spatio-temporal coverage. As with any estimation problem, no uniquely 'correct' solution is now or ever going to be possible-- -only evolving best estimates. Further development of these and similar methodologies appears to be a necessary, inevitable, and growing component of oceanography and climate.

[Review of estimation on oceanic primary productivity by using remote sensing methods.

PubMed

Xu, Hong Yun; Zhou, Wei Feng; Ji, Shi Jian

2016-09-01

Accuracy estimation of oceanic primary productivity is of great significance in the assessment and management of fisheries resources, marine ecology systems, global change and other fields. The traditional measurement and estimation of oceanic primary productivity has to rely on in situ sample data by vessels. Satellite remote sensing has advantages of providing dynamic and eco-environmental parameters of ocean surface at large scale in real time. Thus, satellite remote sensing has increasingly become an important means for oceanic primary productivity estimation on large spatio-temporal scale. Combining with the development of ocean color sensors, the models to estimate the oceanic primary productivity by satellite remote sensing have been developed that could be mainly summarized as chlorophyll-based, carbon-based and phytoplankton absorption-based approach. The flexibility and complexity of the three kinds of models were presented in the paper. On this basis, the current research status for global estimation of oceanic primary productivity was analyzed and evaluated. In view of these, four research fields needed to be strengthened in further stu-dy: 1) Global oceanic primary productivity estimation should be segmented and studied, 2) to dee-pen the research on absorption coefficient of phytoplankton, 3) to enhance the technology of ocea-nic remote sensing, 4) to improve the in situ measurement of primary productivity.

Development and evaluation of a high-resolution reanalysis of the East Australian Current region using the Regional Ocean Modelling System (ROMS 3.4) and Incremental Strong-Constraint 4-Dimensional Variational (IS4D-Var) data assimilation

NASA Astrophysics Data System (ADS)

Kerry, Colette; Powell, Brian; Roughan, Moninya; Oke, Peter

2016-10-01

As with other Western Boundary Currents globally, the East Australian Current (EAC) is highly variable making it a challenge to model and predict. For the EAC region, we combine a high-resolution state-of-the-art numerical ocean model with a variety of traditional and newly available observations using an advanced variational data assimilation scheme. The numerical model is configured using the Regional Ocean Modelling System (ROMS 3.4) and takes boundary forcing from the BlueLink ReANalysis (BRAN3). For the data assimilation, we use an Incremental Strong-Constraint 4-Dimensional Variational (IS4D-Var) scheme, which uses the model dynamics to perturb the initial conditions, atmospheric forcing, and boundary conditions, such that the modelled ocean state better fits and is in balance with the observations. This paper describes the data assimilative model configuration that achieves a significant reduction of the difference between the modelled solution and the observations to give a dynamically consistent "best estimate" of the ocean state over a 2-year period. The reanalysis is shown to represent both assimilated and non-assimilated observations well. It achieves mean spatially averaged root mean squared (rms) residuals with the observations of 7.6 cm for sea surface height (SSH) and 0.4 °C for sea surface temperature (SST) over the assimilation period. The time-mean rms residual for subsurface temperature measured by Argo floats is a maximum of 0.9 °C between water depths of 100 and 300 m and smaller throughout the rest of the water column. Velocities at several offshore and continental shelf moorings are well represented in the reanalysis with complex correlations between 0.8 and 1 for all observations in the upper 500 m. Surface radial velocities from a high-frequency radar array are assimilated and the reanalysis provides surface velocity estimates with complex correlations with observed velocities of 0.8-1 across the radar footprint. A comparison with independent (non-assimilated) shipboard conductivity temperature depth (CTD) cast observations shows a marked improvement in the representation of the subsurface ocean in the reanalysis, with the rms residual in potential density reduced to about half of the residual with the free-running model in the upper eddy-influenced part of the water column. This shows that information is successfully propagated from observed variables to unobserved regions as the assimilation system uses the model dynamics to adjust the model state estimate. This is the first study to generate a reanalysis of the region at such a high resolution, making use of an unprecedented observational data set and using an assimilation method that uses the time-evolving model physics to adjust the model in a dynamically consistent way. As such, the reanalysis potentially represents a marked improvement in our ability to capture important circulation dynamics in the EAC. The reanalysis is being used to study EAC dynamics, observation impact in state-estimation, and as forcing for a variety of downscaling studies.

Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence

NASA Astrophysics Data System (ADS)

Risser, Mark D.; Stone, Dáithí A.; Paciorek, Christopher J.; Wehner, Michael F.; Angélil, Oliver

2017-11-01

In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed "event attribution." Limitations in the observational record and in computational resources motivate the use of uncoupled, atmosphere/land-only climate models with prescribed ocean conditions run over a short period, leading up to and including an event of interest. In this approach, large ensembles of high-resolution simulations can be generated under factual observed conditions and counterfactual conditions that might have been observed in the absence of human interference; these can be used to estimate the change in probability of the given event due to anthropogenic influence. However, using a prescribed ocean state ignores the possibility that estimates of attributable risk might be a function of the ocean state. Thus, the uncertainty in attributable risk is likely underestimated, implying an over-confidence in anthropogenic influence. In this work, we estimate the year-to-year variability in calculations of the anthropogenic contribution to extreme weather based on large ensembles of atmospheric model simulations. Our results both quantify the magnitude of year-to-year variability and categorize the degree to which conclusions of attributable risk are qualitatively affected. The methodology is illustrated by exploring extreme temperature and precipitation events for the northwest coast of South America and northern-central Siberia; we also provides results for regions around the globe. While it remains preferable to perform a full multi-year analysis, the results presented here can serve as an indication of where and when attribution researchers should be concerned about the use of atmosphere-only simulations.

Seismicity and Structure of the Incoming Pacific Plate Subducting into the Japan Trench off Miyagi

NASA Astrophysics Data System (ADS)

Obana, K.; Fujie, G.; Kodaira, S.; Takahashi, T.; Yamamoto, Y.; Sato, T.; Yamashita, M.; Nakamura, Y.; Miura, S.

2015-12-01

Stresses within the oceanic plate in trench axis and outer-rise region have been characterized by shallow extension and deep compression due to the bending of the plate subducting into the trench. The stress state within the incoming/subducting oceanic plate is an important factor not only for the occurrence of shallow intraplate normal-faulting earthquakes in the trench-outer rise region but also the hydration of the oceanic plate through the shallow normal faults cutting the oceanic lithosphere. We investigate seismic velocity structure and stress state within the incoming/subducting Pacific Plate in the Japan Trench based on the OBS aftershock observations for the December 2012 intraplate doublet, which consists of a deep reverse faulting (Mw 7.2) and a shallow normal faulting (Mw 7.2) earthquake, in the Japan Trench off Miyagi. Hypocenter locations and seismic velocity structures were estimated from the arrival time data of about 3000 earthquakes by using double-difference tomography method (Zhang and Thurber, 2003). Also, focal mechanisms were estimated from first motion polarities by using the program HASH by Hardebeck and Shearer (2002). The results show that the earthquakes occurred mainly within the oceanic crust and the uppermost mantle. The deepest event was located at a depth of about 60 km. Focal mechanisms of the earthquakes shallower than a depth of 40 km indicate normal-faulting with T-axis normal to the trench. On the other hand, first motion polarities of the events at depths between 50 and 60 km can be explained a reverse faulting. The results suggest that the neutral plane of the stress between shallow extension and deep compression locates at 40 to 50 km deep. Seismic velocity structures indicate velocity decrease in the oceanic mantle toward the trench. Although the velocity decrease varies with locations, the results suggest the bending-related structure change could extend to at least about 15 km below the oceanic Moho in some locations.

Uncertainty Modeling and Possibilistic Approach to Parameter Estimation.

DTIC Science & Technology

1982-01-01

University Las Cruces, New Mexico 88003 0 SONSOP.!NG ’MONITORING AGENCY NAME(S) AND AOORE SS(ES) 10 SPONSOFlIT!.S1.’NITOR7JG, Naval Ocean Systems...Naval Ocean Systems Center, San Diego, CALIF. 92152 •* Department of Mathematical Sciences, New Mexico State University , Las Cruces, N. MEX. 88003...represents some relationship such as "if xj is in A then xjis in B ", x;varyiVg over the universe of discourse X , and where A and B are fuzzy sets

Sea surface temperature predictions using a multi-ocean analysis ensemble scheme

NASA Astrophysics Data System (ADS)

Zhang, Ying; Zhu, Jieshun; Li, Zhongxian; Chen, Haishan; Zeng, Gang

2017-08-01

This study examined the global sea surface temperature (SST) predictions by a so-called multiple-ocean analysis ensemble (MAE) initialization method which was applied in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2). Different from most operational climate prediction practices which are initialized by a specific ocean analysis system, the MAE method is based on multiple ocean analyses. In the paper, the MAE method was first justified by analyzing the ocean temperature variability in four ocean analyses which all are/were applied for operational climate predictions either at the European Centre for Medium-range Weather Forecasts or at NCEP. It was found that these systems exhibit substantial uncertainties in estimating the ocean states, especially at the deep layers. Further, a set of MAE hindcasts was conducted based on the four ocean analyses with CFSv2, starting from each April during 1982-2007. The MAE hindcasts were verified against a subset of hindcasts from the NCEP CFS Reanalysis and Reforecast (CFSRR) Project. Comparisons suggested that MAE shows better SST predictions than CFSRR over most regions where ocean dynamics plays a vital role in SST evolutions, such as the El Niño and Atlantic Niño regions. Furthermore, significant improvements were also found in summer precipitation predictions over the equatorial eastern Pacific and Atlantic oceans, for which the local SST prediction improvements should be responsible. The prediction improvements by MAE imply a problem for most current climate predictions which are based on a specific ocean analysis system. That is, their predictions would drift towards states biased by errors inherent in their ocean initialization system, and thus have large prediction errors. In contrast, MAE arguably has an advantage by sampling such structural uncertainties, and could efficiently cancel these errors out in their predictions.

The Observed State of the Water Cycle in the Early Twenty-First Century

NASA Technical Reports Server (NTRS)

Rodell, M.; Beaudoing, H. K.; L'Ecuyer, T. S.; Olson, W. S.; Famiglietti, J. S.; Houser, P. R.; Adler, R.; Bosilovich, M. G.; Clayson, C. A.; Chambers, D.;

Impact of the new equation of state of seawater (TEOS-10) on the estimates of water mass mixture and meridional transport in the Atlantic Ocean

NASA Astrophysics Data System (ADS)

Almeida, Lucas; de Azevedo, José Luiz Lima; Kerr, Rodrigo; Araujo, Moacyr; Mata, Mauricio M.

2018-03-01

The equation of state of seawater (EOS) provides a simple way to link the properties of seawater that are the most important for ocean dynamics and the ocean-atmosphere climate system. In 2010, the set of equations used to derive all thermodynamic properties of seawater were updated using a thermodynamic approach. The new approach, named TEOS-10, results in better estimates of seawater properties, such as salinity and temperature, when compared to the previous EOS version (EOS-80). Since several physical processes in the oceans are driven by these properties, improvements in the EOS performance are expected to lead to a better and more realistic representation of the ocean. This work focuses on assessing the main differences of the: (i) contribution of water masses to a total mixture, (ii) baroclinic velocity, and (iii) volume and heat transport, as calculated by the EOS-80 and by the TEOS-10, along four zonal transects at 26.5°N, 10°N, 11°S, and 34.5°S in the Atlantic Ocean. The density differences (always between TEOS-10 and EOS-80) increase with depth and hence the results indicate that the most significant difference in the water mass contributions was found for Antarctic Bottom Water. Within that layer, the differences reach up to 10% on its fraction of the mixture when calculated by the TEOS-10, although the difference in the North Atlantic Deep Water contribution was not negligible either. The estimated baroclinic velocities showed considerable differences in all studied areas, being more significant over boundary current systems. The Gulf Stream presented lower velocity, while the Brazil Current presented increasing velocity when using TEOS-10. The comparison between values computed for volume transported by the Atlantic Meridional Overturning Circulation showed a total difference of about +6%, which cannot be neglected when considering the space and time variability involved. The heat transport showed significant differences in the study areas at the mid latitudes, where large variations in the total flow were observed.

Estimation of mean sea surfaces in the north Atlantic, the Pacific and the Indian Ocean using GEOS-3 altimeter data

NASA Technical Reports Server (NTRS)

Marsh, J. G.; Martin, T. V.; Mccarthy, J. J.; Chovitz, P. S.

1979-01-01

The mean surfaces of several regions of the world's oceans were estimated using GEOS-3 altimeter data. The northwest Atlantic, the northeast Pacific off the coast of California, the Indian Ocean, the southwest Pacific, and the Phillipine Sea are included. These surfaces have been oriented with respect to a common earth center-of-mass system by constraining the separate solutions to conform to precisely determined laser reference control orbits. The same reference orbits were used for all regions assuring continuity of the separate solutions. Radial accuracies of the control orbits were in the order of one meter. The altimeter measured sea surface height crossover differences were minimized by the adjustment of tilt and bias parameters for each pass with the exception of laser reference control passes. The tilt and bias adjustments removed long wavelength errors which were primarily due to orbit error. Ocean tides were evaluated. The resolution of the estimated sea surfaces varied from 0.25 degrees off the east coast of the United States to about 2 degrees in part of the Indian Ocean near Australia. The rms crossover discrepancy after adjustment varied from 30 cm to 70 cm depending upon geographic location. Comparisons of the altimeter derived mean sea surface in the North Atlantic with the 5 feet x 5 feet GEM-8 detailed gravimetric geoid indicated a relative consistency of better than a meter.

Scientific advances of the MyOcean projects underpinning the transition towards the Marine Copernicus service

NASA Astrophysics Data System (ADS)

Brasseur, Pierre

2015-04-01

The MyOcean projects supported by the European Commission period have been developed during the 2008-2015 period to build an operational service of ocean physical state and ecosystem information to intermediate and downstream users in the areas of marine safety, marine resources, marine and coastal environment and weather, climate and seasonal forecasting. The "core" information provided to users is obtained through the combination of satellite and in situ observations, eddy-resolving modelling of the global ocean and regional european seas, biochemistry, ecosystem and sea-ice modelling, and data assimilation for global to basin scale circulation. A comprehensive R&D plan was established in 2010 to ensure the collection and provision of information of best possible quality for daily estimates of the ocean state (real-time), its short-term evolution, and its history over the past (reanalyses). A service validation methodology was further developed to ensure proper scientific evaluation and routine monitoring of the accuracy of MyOcean products. In this presentation, we will present an overview of the main scientific advances achieved in MyOcean using the NEMO modelling platform, ensemble-based assimilation schemes, coupled circulation-ecosystem, sea-ice assimilative models and probabilistic methodologies for ensemble validation. We will further highlight the key areas that will require additional innovation effort to support the Marine Copernicus service evolution.

An Overview of the Naval Research Laboratory Ocean Surface Flux (NFLUX) System

NASA Astrophysics Data System (ADS)

May, J. C.; Rowley, C. D.; Barron, C. N.

2016-02-01

The Naval Research Laboratory (NRL) ocean surface flux (NFLUX) system is an end-to-end data processing and assimilation system used to provide near-real time satellite-based surface heat flux fields over the global ocean. Swath-level air temperature (TA), specific humidity (QA), and wind speed (WS) estimates are produced using multiple polynomial regression algorithms with inputs from satellite sensor data records from the Special Sensor Microwave Imager/Sounder, the Advanced Microwave Sounding Unit-A, the Advanced Technology Microwave Sounder, and the Advanced Microwave Scanning Radiometer-2 sensors. Swath-level WS estimates are also retrieved from satellite environmental data records from WindSat, the MetOp scatterometers, and the Oceansat scatterometer. Swath-level solar and longwave radiative flux estimates are produced utilizing the Rapid Radiative Transfer Model for Global Circulation Models (RRTMG). Primary inputs to the RRTMG include temperature and moisture profiles and cloud liquid and ice water paths from the Microwave Integrated Retrieval System. All swath-level satellite estimates undergo an automated quality control process and are then assimilated with atmospheric model forecasts to produce 3-hourly gridded analysis fields. The turbulent heat flux fields, latent and sensible heat flux, are determined from the Coupled Ocean-Atmosphere Response Experiment (COARE) 3.0 bulk algorithms using inputs of TA, QA, WS, and a sea surface temperature model field. Quality-controlled in situ observations over a one-year time period from May 2013 through April 2014 form the reference for validating ocean surface state parameter and heat flux fields. The NFLUX fields are evaluated alongside the Navy's operational global atmospheric model, the Navy Global Environmental Model (NAVGEM). NFLUX is shown to have smaller biases and lower or similar root mean square errors compared to NAVGEM.

Spatial Distribution, Structure, Biomass, and Physiology of Microbial Assemblages across the Southern Ocean Frontal Zones during the Late Austral Winter

PubMed Central

Hanson, Roger B.; Lowery, H. Kenneth

1985-01-01

We examined the spatial distributions of picoplankton, nanoplankton, and microplankton biomass and physiological state relative to the hydrography of the Southern Ocean along 90° W longitude and across the Drake Passage in the late austral winter. The eastern South Pacific Ocean showed some large-scale biogeographical differences and size class variability. Microbial ATP biomass was greatest in euphotic surface waters. The horizontal distributions of microbial biomass and physiological state (adenylate energy charge ratio) coincided with internal currents (fronts) of the Antarctic Circumpolar Current. In the Drake Passage, the biological scales in the euphotic and aphotic zones were complex, and ATP, total adenylate, and adenylate energy charge ratio isopleths were compressed due to the extension of the sea ice from Antarctica and constriction of the Circumpolar Current through the narrow passage. The physiological state of microbial assemblages and biomass were much higher in the Drake Passage than in the eastern South Pacific Ocean. The temperature of Antarctic waters, not dissolved organic carbon, was the major variable controlling picoplankton growth. Estimates of picoplankton production based on ATP increments with time suggest that production under reduced predation pressure was 1 to 10 μg of carbon per liter per day. Our results demonstrate the influence of large-scale hydrographic processes on the distribution and structure of microplankton, nanoplankton, and picoplankton across the Southern Ocean. PMID:16346777

Upper Atmosphere Heating From Ocean-Generated Acoustic Wave Energy

DOE PAGES

Bowman, D. C.; Lees, J. M.

2018-04-27

We present that colliding sea surface waves generate the ocean microbarom, an acoustic signal that may transmit significant energy to the upper atmosphere. Previous estimates of acoustic energy flux from the ocean microbarom and mountain-wind interactions are on the order of 0.01 to 1 mW/m 2, heating the thermosphere by tens of Kelvins per day. We captured upgoing ocean microbarom waves with a balloon-borne infrasound microphone; the maximum acoustic energy flux was approximately 0.05 mW/m 2. This is about half the average value reported in previous ground-based microbarom observations spanning 8 years. The acoustic flux from the microbarom episode describedmore » here may have heated the thermosphere by several Kelvins per day while the source persisted. Lastly, we suggest that ocean wave models could be used to parameterize acoustically generated heating of the upper atmosphere based on sea state.« less

Upper Atmosphere Heating From Ocean-Generated Acoustic Wave Energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, D. C.; Lees, J. M.

We present that colliding sea surface waves generate the ocean microbarom, an acoustic signal that may transmit significant energy to the upper atmosphere. Previous estimates of acoustic energy flux from the ocean microbarom and mountain-wind interactions are on the order of 0.01 to 1 mW/m 2, heating the thermosphere by tens of Kelvins per day. We captured upgoing ocean microbarom waves with a balloon-borne infrasound microphone; the maximum acoustic energy flux was approximately 0.05 mW/m 2. This is about half the average value reported in previous ground-based microbarom observations spanning 8 years. The acoustic flux from the microbarom episode describedmore » here may have heated the thermosphere by several Kelvins per day while the source persisted. Lastly, we suggest that ocean wave models could be used to parameterize acoustically generated heating of the upper atmosphere based on sea state.« less

Impact of anthropogenic CO2 on the CaCO3 system in the oceans.

PubMed

Feely, Richard A; Sabine, Christopher L; Lee, Kitack; Berelson, Will; Kleypas, Joanie; Fabry, Victoria J; Millero, Frank J

2004-07-16

Rising atmospheric carbon dioxide (CO2) concentrations over the past two centuries have led to greater CO2 uptake by the oceans. This acidification process has changed the saturation state of the oceans with respect to calcium carbonate (CaCO3) particles. Here we estimate the in situ CaCO3 dissolution rates for the global oceans from total alkalinity and chlorofluorocarbon data, and we also discuss the future impacts of anthropogenic CO2 on CaCO3 shell-forming species. CaCO3 dissolution rates, ranging from 0.003 to 1.2 micromoles per kilogram per year, are observed beginning near the aragonite saturation horizon. The total water column CaCO3 dissolution rate for the global oceans is approximately 0.5 +/- 0.2 petagrams of CaCO3-C per year, which is approximately 45 to 65% of the export production of CaCO3.

Marine debris from the Oregon Dungeness crab fishery recovered in the Northwestern Hawaiian Islands: identification and oceanic drift paths.

PubMed

Ebbesmeyer, Curtis C; Ingraham, W J; Jones, Jason A; Donohue, Mary J

2012-01-01

Two Dungeness crab trap tags and floats lost off the State of Oregon, USA during the 2006-2007 fishing season were recovered 4years later in the Northwestern Hawaiian Islands (NWHI): on Lisianski Island on July 15, 2010; and on Kure Atoll on December 10, 2010. This is the first documented recovery of marine debris from Oregon fisheries in the NWHI. We simulate the oceanic drift tracks of the derelict fishing gear with the Ocean Surface Current Simulator (OSCURS) model using estimated loss dates in Oregon based on interviews with the crab trap owners and known recovery sites and dates in the NWHI. These data confirm the US Pacific Northwest as a source of marine debris deposited in the NWHI and provide enhanced understanding of the oceanic drift pathways of marine debris in the North Pacific Ocean. Copyright © 2011 Elsevier Ltd. All rights reserved.

Toward the Inference of Deglacial Ocean Dynamics from the Spatial Pattern of LGM-to-Modern d13C and d18O Change

NASA Astrophysics Data System (ADS)

Gebbie, G.; Peterson, C. D.; Lisiecki, L. E.; Spero, H. J.

2014-12-01

Estimates of the whole-ocean d13C change between the Last Glacial Maximum (LGM) and the modern-day are converging to values of about 0.4 per mil, and are of great use in partitioning land versus ocean contributions to the deglacial carbon cycle. To determine which specific oceanic processes are at play, however, knowledge of the spatial pattern of LGM-to-modern d13C and d18O change is critical. Spatial maps have mostly focused on Atlantic d13C, with less progress for d18O and the Pacific and Indian sectors, due to the concentration of sediment-core observations in the Atlantic and the difficulty in making meaningful maps from sparse data. Here, we demonstrate that a state estimation (or data assimilation) method based on recently compiled data and a simple kinematic ocean model simultaneously produces reasonable results for: 1) global maps of d13C and d18O, 2) uncertainty in the estimated properties, and 3) oceanic water-mass geometry. The observations include benthic d13C and d18O data from 493 marine sediment cores that were collected from the scientific literature and NOAA, PANGEA, and Delphi databases. The kinematic model permits each data point to have influence both up- and downstream along a water-mass pathway, typically allowing a larger geographical range than a statistical interpolation method. No assumption regarding the state of the circulation is necessary, and the modern-day circulation need not be assumed to be representative of the LGM. With this method, meridional (or other) sections can be compared between ocean basins. Furthermore, the internally-consistent d18O and d13C maps are used to determine the LGM-to-modern spatial changes that are robust given the uncertainty and sparsity of data. Rather than simply focus on property maps, we suggest that the link between observations and circulation changes (as reflected by the paths that water travels), points the way toward dynamical processes that must be explained. A particular application of our result is the geographic constraint of possible unobserved reservoirs of d13C or radiocarbon and calculation of their potential impact on the global chain of events during the deglaciation.

An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval

NASA Astrophysics Data System (ADS)

Skourup, Henriette; Farrell, Sinéad Louise; Hendricks, Stefan; Ricker, Robert; Armitage, Thomas W. K.; Ridout, Andy; Andersen, Ole Baltazar; Haas, Christian; Baker, Steven

2017-11-01

State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high-frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multisensor oceanographic time series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04 and DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, intersatellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m.

Evaluation of hydrodynamic ocean models as a first step in larval dispersal modelling

NASA Astrophysics Data System (ADS)

Vasile, Roxana; Hartmann, Klaas; Hobday, Alistair J.; Oliver, Eric; Tracey, Sean

2018-01-01

Larval dispersal modelling, a powerful tool in studying population connectivity and species distribution, requires accurate estimates of the ocean state, on a high-resolution grid in both space (e.g. 0.5-1 km horizontal grid) and time (e.g. hourly outputs), particularly of current velocities and water temperature. These estimates are usually provided by hydrodynamic models based on which larval trajectories and survival are computed. In this study we assessed the accuracy of two hydrodynamic models around Australia - Bluelink ReANalysis (BRAN) and Hybrid Coordinate Ocean Model (HYCOM) - through comparison with empirical data from the Australian National Moorings Network (ANMN). We evaluated the models' predictions of seawater parameters most relevant to larval dispersal - temperature, u and v velocities and current speed and direction - on the continental shelf where spawning and nursery areas for major fishery species are located. The performance of each model in estimating ocean parameters was found to depend on the parameter investigated and to vary from one geographical region to another. Both BRAN and HYCOM models systematically overestimated the mean water temperature, particularly in the top 140 m of water column, with over 2 °C bias at some of the mooring stations. HYCOM model was more accurate than BRAN for water temperature predictions in the Great Australian Bight and along the east coast of Australia. Skill scores between each model and the in situ observations showed lower accuracy in the models' predictions of u and v ocean current velocities compared to water temperature predictions. For both models, the lowest accuracy in predicting ocean current velocities, speed and direction was observed at 200 m depth. Low accuracy of both model predictions was also observed in the top 10 m of the water column. BRAN had more accurate predictions of both u and v velocities in the upper 50 m of water column at all mooring station locations. While HYCOM predictions of ocean current speed were generally more accurate than BRAN, BRAN predictions of both ocean current speed and direction were more accurate than HYCOM along the southeast coast of Australia and Tasmania. This study identified important inaccuracies in the hydrodynamic models' estimations of the real ocean parameters and on time scales relevant to larval dispersal studies. These findings highlight the importance of the choice and validation of hydrodynamic models, and calls for estimates of such bias to be incorporated in dispersal studies.

Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation. A case study for the South African current system

NASA Astrophysics Data System (ADS)

Saynisch, Jan; Semmling, Maximilian; Wickert, Jens; Thomas, Maik

2015-11-01

The Agulhas current system transports warm and salty water masses from the Indian Ocean into the Southern Ocean and into the Atlantic. The transports impact past, present, and future climate on local and global scales. The size and variability, however, of the respective transports are still much debated. In this study, an idealized model based twin experiment is used to study whether sea surface height (SSH) anomalies estimated from reflected signals of the Global Navigation Satellite System reflectometry (GNSS-R) can be used to determine the internal water mass properties and transports of the Agulhas region. A space-borne GNSS-R detector on the International Space Station (ISS) is assumed and simulated. The detector is able to observe daily SSH fields with a spatial resolution of 1-5∘. Depending on reflection geometry, the precision of a single SSH observation is estimated to reach 3 cm (20 cm) when the carrier phase (code delay) information of the reflected GNSS signal is used. The average precision over the Agulhas region is 7 cm (42 cm). The proposed GNSS-R measurements surpass the radar-based satellite altimetry missions in temporal and spatial resolution but are less precise. Using the estimated GNSS-R characteristics, measurements of SSH are generated by sampling a regional nested general circulation model of the South African oceans. The artificial observations are subsequently assimilated with a 4DVAR adjoint data assimilation method into the same ocean model but with a different initial state and forcing. The assimilated and the original, i.e., the sampled model state, are compared to systematically identify improvements and degradations in the model variables that arise due to the assimilation of GNSS-R based SSH observations. We show that SSH and the independent, i.e., not assimilated model variables velocity, temperature, and salinity improve by the assimilation of GNSS-R based SSH observations. After the assimilation of 90 days of SSH observations, improvements in the independent variables cover the whole water column. Locally, up to 39 % of the original model state are recovered. Shorter assimilation windows result in enhanced reproduction of the observed and assimilated SSH but are accompanied by an insufficient or wrong recovery of sub-surface water properties. The assimilation of real GNSS-R observations, when available, and consequently the estimation of Agulhas water mass properties and the leakage of heat and salt into the Atlantic will benefit from this model-based study.

Assessing an ensemble Kalman filter inference of Manning's n coefficient of an idealized tidal inlet against a polynomial chaos-based MCMC

NASA Astrophysics Data System (ADS)

Siripatana, Adil; Mayo, Talea; Sraj, Ihab; Knio, Omar; Dawson, Clint; Le Maitre, Olivier; Hoteit, Ibrahim

2017-08-01

Bayesian estimation/inversion is commonly used to quantify and reduce modeling uncertainties in coastal ocean model, especially in the framework of parameter estimation. Based on Bayes rule, the posterior probability distribution function (pdf) of the estimated quantities is obtained conditioned on available data. It can be computed either directly, using a Markov chain Monte Carlo (MCMC) approach, or by sequentially processing the data following a data assimilation approach, which is heavily exploited in large dimensional state estimation problems. The advantage of data assimilation schemes over MCMC-type methods arises from the ability to algorithmically accommodate a large number of uncertain quantities without significant increase in the computational requirements. However, only approximate estimates are generally obtained by this approach due to the restricted Gaussian prior and noise assumptions that are generally imposed in these methods. This contribution aims at evaluating the effectiveness of utilizing an ensemble Kalman-based data assimilation method for parameter estimation of a coastal ocean model against an MCMC polynomial chaos (PC)-based scheme. We focus on quantifying the uncertainties of a coastal ocean ADvanced CIRCulation (ADCIRC) model with respect to the Manning's n coefficients. Based on a realistic framework of observation system simulation experiments (OSSEs), we apply an ensemble Kalman filter and the MCMC method employing a surrogate of ADCIRC constructed by a non-intrusive PC expansion for evaluating the likelihood, and test both approaches under identical scenarios. We study the sensitivity of the estimated posteriors with respect to the parameters of the inference methods, including ensemble size, inflation factor, and PC order. A full analysis of both methods, in the context of coastal ocean model, suggests that an ensemble Kalman filter with appropriate ensemble size and well-tuned inflation provides reliable mean estimates and uncertainties of Manning's n coefficients compared to the full posterior distributions inferred by MCMC.

Simultaneous aerosol/ocean products retrieved during the 2014 SABOR campaign using the NASA Research Scanning Polarimeter (RSP)

NASA Astrophysics Data System (ADS)

Stamnes, S.; Hostetler, C. A.; Ferrare, R. A.; Hair, J. W.; Burton, S. P.; Liu, X.; Hu, Y.; Stamnes, K. H.; Chowdhary, J.; Brian, C.

2017-12-01

The SABOR (Ship-Aircraft Bio-Optical Research) campaign was conducted during the summer of 2014, in the Atlantic Ocean, over the Chesapeake Bay and the eastern coastal region of the United States. The NASA GISS Research Scanning Polarimeter, a multi-angle, multi-spectral polarimeter measured the upwelling polarized radiances from a B200 aircraft. We present results from the new "MAPP" algorithm for RSP that is based on optimal estimation and that can retrieve simultaneous aerosol microphysical properties (including effective radius, single-scattering albedo, and real refractive index) and ocean color products using accurate radiative transfer and Mie calculations. The algorithm was applied to data collected during SABOR to retrieve aerosol microphysics and ocean products for all Aerosols-Above-Ocean (AAO) scenes. The RSP MAPP products are compared against collocated aerosol extinction and backscatter profiles collected by the NASA LaRC airborne High Spectral Resolution Lidar (HSRL-1), including lidar depth profiles of the ocean diffuse attenuation coefficient and the hemispherical backscatter coefficient.

Annual Net Community Production in the Western Subtropical North Pacific Determined from Argo-O2 Measurements

NASA Astrophysics Data System (ADS)

Yang, B.; Emerson, S. R.; Bushinsky, S. M.

2016-02-01

Export of organic carbon from the surface ocean to depth (the biological pump) helps maintain the pCO2 of the atmosphere and the O2 content of the oxygen minimum zones of the ocean. In the upper ocean, at steady state over a seasonal cycle the net organic carbon export is equal to the Annual Net Community Production (ANCP). The geographic distribution of this quantity determined by satellite-predicted Net Primary Production (NPP) and the recycling efficiency in the euphotic zone is more heterogeneous than the limited experimental estimates of ANCP. We evaluate the relationship between these two estimates of ANCP in the subtropical Western North Pacific Ocean ( 165o E and 20o N) using oxygen measurements on Argo Floats. In January of 2015 we deployed four floats with Anderaa oxygen sensors attached to a 60 cm stick on top of the float end cap, which can be readily calibrated against atmospheric pO2. We present data from these floats and air-sea oxygen flux calculations. The degree of oxygen supersaturation in summer is 1-2 percent, and in winter it fluctuates between being over and undersaturated. Evaluating the role of bubbles in winter is critical to an accurate determination of the annual flux. While there is not a full year of data at the time of writing this abstract, there will be when the Ocean Science meeting is held. So far, after nine months of measurements, there is a net flux of oxygen to the atmosphere, indicating that photosynthesis exceeds respiration. In February we will present a full annual cycle of air-sea oxygen flux and an estimate of ANCP in this very rarely studied region of the ocean.

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume; Koster, Randal D. (Editor)

2014-01-01

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele; Kovach, Robin M.; Vernieres, Guillaume

2014-01-01

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE PAGES

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.; ...

2018-03-01

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

Use of surface drifters to increase resolution and accuracy of oceanic geostrophic circulation mapped from satellite only (altimetry and gravimetry)

NASA Astrophysics Data System (ADS)

Mulet, Sandrine; Rio, Marie-Hélène; Etienne, Hélène

2017-04-01

Strong improvements have been made in our knowledge of the surface ocean geostrophic circulation thanks to satellite observations. For instance, the use of the latest GOCE (Gravity field and steady-state Ocean Circulation Explorer) geoid model with altimetry data gives good estimate of the mean oceanic circulation at spatial scales down to 125 km. However, surface drifters are essential to resolve smaller scales, it is thus mandatory to carefully process drifter data and then to combine these different data sources. In this framework, the global 1/4° CNES-CLS13 Mean Dynamic Topography (MDT) and associated mean geostrophic currents have been computed (Rio et al, 2014). First a satellite only MDT was computed from altimetric and gravimetric data. Then, an important work was to pre-process drifter data to extract only the geostrophic component in order to be consistent with physical content of satellite only MDT. This step include estimate and remove of Ekman current and wind slippage. Finally drifters and satellite only MDT were combined. Similar approaches are used regionally to go further toward higher resolution, for instance in the Agulhas current or along the Brazilian coast. Also, a case study in the Gulf of Mexico intends to use drifters in the same way to improve weekly geostrophic current estimate.

Estimated Water Flows in 2005: United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, C A; Belles, R D; Simon, A J

2011-03-16

Flow charts depicting water use in the United States have been constructed from publicly available data and estimates of water use patterns. Approximately 410,500 million gallons per day of water are managed throughout the United States for use in farming, power production, residential, commercial, and industrial applications. Water is obtained from four major resource classes: fresh surface-water, saline (ocean) surface-water, fresh groundwater and saline (brackish) groundwater. Water that is not consumed or evaporated during its use is returned to surface bodies of water. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states inmore » addition to Puerto Rico and the Virgin Islands) and one national water flow chart representing a comprehensive systems view of national water resources, use, and disposition.« less

Mapping Error in Southern Ocean Transport Computed from Satellite Altimetry and Argo

NASA Astrophysics Data System (ADS)

Kosempa, M.; Chambers, D. P.

2016-02-01

Argo profiling floats afford basin-scale coverage of the Southern Ocean since 2005. When density estimates from Argo are combined with surface geostrophic currents derived from satellite altimetry, one can estimate integrated geostrophic transport above 2000 dbar [e.g., Kosempa and Chambers, JGR, 2014]. However, the interpolation techniques relied upon to generate mapped data from Argo and altimetry will impart a mapping error. We quantify this mapping error by sampling the high-resolution Southern Ocean State Estimate (SOSE) at the locations of Argo floats and Jason-1, and -2 altimeter ground tracks, then create gridded products using the same optimal interpolation algorithms used for the Argo/altimetry gridded products. We combine these surface and subsurface grids to compare the sampled-then-interpolated transport grids to those from the original SOSE data in an effort to quantify the uncertainty in volume transport integrated across the Antarctic Circumpolar Current (ACC). This uncertainty is then used to answer two fundamental questions: 1) What is the minimum linear trend that can be observed in ACC transport given the present length of the instrument record? 2) How long must the instrument record be to observe a trend with an accuracy of 0.1 Sv/year?

Applied estimation for hybrid dynamical systems using perceptional information

NASA Astrophysics Data System (ADS)

Plotnik, Aaron M.

This dissertation uses the motivating example of robotic tracking of mobile deep ocean animals to present innovations in robotic perception and estimation for hybrid dynamical systems. An approach to estimation for hybrid systems is presented that utilizes uncertain perceptional information about the system's mode to improve tracking of its mode and continuous states. This results in significant improvements in situations where previously reported methods of estimation for hybrid systems perform poorly due to poor distinguishability of the modes. The specific application that motivates this research is an automatic underwater robotic observation system that follows and films individual deep ocean animals. A first version of such a system has been developed jointly by the Stanford Aerospace Robotics Laboratory and Monterey Bay Aquarium Research Institute (MBARI). This robotic observation system is successfully fielded on MBARI's ROVs, but agile specimens often evade the system. When a human ROV pilot performs this task, one advantage that he has over the robotic observation system in these situations is the ability to use visual perceptional information about the target, immediately recognizing any changes in the specimen's behavior mode. With the approach of the human pilot in mind, a new version of the robotic observation system is proposed which is extended to (a) derive perceptional information (visual cues) about the behavior mode of the tracked specimen, and (b) merge this dissimilar, discrete and uncertain information with more traditional continuous noisy sensor data by extending existing algorithms for hybrid estimation. These performance enhancements are enabled by integrating techniques in hybrid estimation, computer vision and machine learning. First, real-time computer vision and classification algorithms extract a visual observation of the target's behavior mode. Existing hybrid estimation algorithms are extended to admit this uncertain but discrete observation, complementing the information available from more traditional sensors. State tracking is achieved using a new form of Rao-Blackwellized particle filter called the mode-observed Gaussian Particle Filter. Performance is demonstrated using data from simulation and data collected on actual specimens in the ocean. The framework for estimation using both traditional and perceptional information is easily extensible to other stochastic hybrid systems with mode-related perceptional observations available.

Stormwater plume detection by MODIS imagery in the southern California coastal ocean

USGS Publications Warehouse

Nezlin, N.P.; DiGiacomo, P.M.; Diehl, D.W.; Jones, B.H.; Johnson, S.C.; Mengel, M.J.; Reifel, K.M.; Warrick, J.A.; Wang, M.

2008-01-01

Stormwater plumes in the southern California coastal ocean were detected by MODIS-Aqua satellite imagery and compared to ship-based data on surface salinity and fecal indicator bacterial (FIB) counts collected during the Bight'03 Regional Water Quality Program surveys in February-March of 2004 and 2005. MODIS imagery was processed using a combined near-infrared/shortwave-infrared (NIR-SWIR) atmospheric correction method, which substantially improved normalized water-leaving radiation (nLw) optical spectra in coastal waters with high turbidity. Plumes were detected using a minimum-distance supervised classification method based on nLw spectra averaged within the training areas, defined as circular zones of 1.5-5.0-km radii around field stations with a surface salinity of S 33.0 ('ocean'). The plume optical signatures (i.e., the nLw differences between 'plume' and 'ocean') were most evident during the first 2 days after the rainstorms. To assess the accuracy of plume detection, stations were classified into 'plume' and 'ocean' using two criteria: (1) 'plume' included the stations with salinity below a certain threshold estimated from the maximum accuracy of plume detection; and (2) FIB counts in 'plume' exceeded the California State Water Board standards. The salinity threshold between 'plume' and 'ocean' was estimated as 32.2. The total accuracy of plume detection in terms of surface salinity was not high (68% on average), seemingly because of imperfect correlation between plume salinity and ocean color. The accuracy of plume detection in terms of FIB exceedances was even lower (64% on average), resulting from low correlation between ocean color and bacterial contamination. Nevertheless, satellite imagery was shown to be a useful tool for the estimation of the extent of potentially polluted plumes, which was hardly achievable by direct sampling methods (in particular, because the grids of ship-based stations covered only small parts of the plumes detected via synoptic MODIS imagery). In most southern California coastal areas, the zones of bacterial contamination were much smaller than the areas of turbid plumes; an exception was the plume of the Tijuana River, where the zone of bacterial contamination was comparable with the zone of plume detected by ocean color. ?? 2008 Elsevier Ltd.

Stormwater plume detection by MODIS imagery in the southern California coastal ocean

NASA Astrophysics Data System (ADS)

Nezlin, Nikolay P.; DiGiacomo, Paul M.; Diehl, Dario W.; Jones, Burton H.; Johnson, Scott C.; Mengel, Michael J.; Reifel, Kristen M.; Warrick, Jonathan A.; Wang, Menghua

2008-10-01

Stormwater plumes in the southern California coastal ocean were detected by MODIS-Aqua satellite imagery and compared to ship-based data on surface salinity and fecal indicator bacterial (FIB) counts collected during the Bight'03 Regional Water Quality Program surveys in February-March of 2004 and 2005. MODIS imagery was processed using a combined near-infrared/shortwave-infrared (NIR-SWIR) atmospheric correction method, which substantially improved normalized water-leaving radiation (nLw) optical spectra in coastal waters with high turbidity. Plumes were detected using a minimum-distance supervised classification method based on nLw spectra averaged within the training areas, defined as circular zones of 1.5-5.0-km radii around field stations with a surface salinity of S < 32.0 ("plume") and S > 33.0 ("ocean"). The plume optical signatures (i.e., the nLw differences between "plume" and "ocean") were most evident during the first 2 days after the rainstorms. To assess the accuracy of plume detection, stations were classified into "plume" and "ocean" using two criteria: (1) "plume" included the stations with salinity below a certain threshold estimated from the maximum accuracy of plume detection; and (2) FIB counts in "plume" exceeded the California State Water Board standards. The salinity threshold between "plume" and "ocean" was estimated as 32.2. The total accuracy of plume detection in terms of surface salinity was not high (68% on average), seemingly because of imperfect correlation between plume salinity and ocean color. The accuracy of plume detection in terms of FIB exceedances was even lower (64% on average), resulting from low correlation between ocean color and bacterial contamination. Nevertheless, satellite imagery was shown to be a useful tool for the estimation of the extent of potentially polluted plumes, which was hardly achievable by direct sampling methods (in particular, because the grids of ship-based stations covered only small parts of the plumes detected via synoptic MODIS imagery). In most southern California coastal areas, the zones of bacterial contamination were much smaller than the areas of turbid plumes; an exception was the plume of the Tijuana River, where the zone of bacterial contamination was comparable with the zone of plume detected by ocean color.

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

A Southern Ocean variability study using the Argo-based Model for Investigation of the Global Ocean (AMIGO)

NASA Astrophysics Data System (ADS)

Lebedev, Konstantin

2017-04-01

The era of satellite observations of the ocean surface that started at the end of the 20th century and the development of the Argo project in the first years of the 21st century, designed to collect information of the upper 2000 m of the ocean using satellites, provides unique opportunities for continuous monitoring of the Global Ocean state. Starting from 2005, measurements with the Argo floats have been performed over the majority of the World Ocean. In November 2007, the Argo program reached coverage of 3000 simultaneously operating floats (one float in a three-degree square) planned during the development of the program. Currently, 4000 Argo floats autonomously profile the upper 2000-m water column of the ocean from Antarctica to Spitsbergen increasing World Ocean temperature and salinity databases by 12000 profiles per month. This makes it possible to solve problems on reconstructing and monitoring the ocean state on an almost real-time basis, study the ocean dynamics, obtain reasonable estimates of the climatic state of the ocean in the last decade and estimate existing intraclimatic trends. We present the newly developed Argo-Based Model for Investigation of the Global Ocean (AMIGO), which consists of a block for variational interpolation of the profiles of drifting Argo floats to a regular grid and a block for model hydrodynamic adjustment of variationally interpolated fields. Such a method makes it possible to obtain a full set of oceanographic characteristics - temperature, salinity, density, and current velocity - using irregularly located Argo measurements (the principle of the variational interpolation technique entails minimization of the misfit between the interpolated fields defined on the regular grid and irregularly distributed data; hence the optimal solution passes as close to the data as possible). The simulations were performed for the entire globe limited in the north by 85.5° N using 1° grid spacing in both longitude and latitude. At the depths exceeding 2000 m, in which Argo data are lacking, the temperature and salinity data were taken from the WOA-09 database. The constant temperature and salinity values from the Argo data for the corresponding month (year, season) derived using the variational technique described above were specified as the boundary conditions at the ocean surface. The constant wind stress in the corresponding month (year, season) was specified from the ECMWF ERA-Interim reanalysis data. The mass, salt, and heat transports over several regions of the Antarctic Circumpolar Current (ACC) and at its northern boundary (35° S) were calculated, seasonal and intra-decadal variation of the transports was studied. The calculations cover the 12-year period from 2005 to 2016. The AMIGO database enjoys free public access on the Internet at: http://argo.ocean.ru/. The results are represented as monthly, seasonal, and annual data and climatological mean fields. The spatial resolution of the data is one degree in latitude and longitude, and the temporal resolution is one month. The work was supported by the Russian Science Foundation (project 16-17-10149).

Are Surface Waters Around Greenland Getting Saltier in a Warming Climate?

NASA Astrophysics Data System (ADS)

Vinogradova, N. T.; Ponte, R. M.; Piecuch, C. G.; Little, C. M.

2016-02-01

During the past two decades, most surface waters around Greenland ice sheet and in the Nordic Seas became significantly saltier. Given the fact that these waters feed the North Atlantic thermohaline circulation, an increase in surface salinity, which can exceed 0.2 psu in places, might have an important impact on the global ocean circulation and on future projections of the climate state. Surface salinification may seem counter-intuitive to the reported long-term increase in freshwater supply to the region from river discharge and ice melting, sparking debates about whether the freshening of the subpolar gyre has ceased, and whether the recent salinification, if continued, will be able to forestall the projected slowdown of the overturning circulation. Here we assess what controls contemporary salinity changes by examining various terms of the salinity budget, including the dilution effect due to air-sea fluxes of freshwater, fluxes of salt due to sea ice formation/melting, and ocean fluxes of salinity associated with advective and diffusive processes. We use an ocean state estimate produced by the ECCO consortium to consider the budgets over the period 1992-2011. ECCO estimates produce salinity fields close to the observations and, crucial for our purposes, permit closed budget diagnostics of salinity and respective fluxes. The budgets are formulated within the entire water column in order to examine three-dimensional structure of freshwater storage and establish a link between the surface and upper-ocean change in near-Greenland waters. Over the past two decades, patterns of change are evident in all budget terms, with ocean fluxes either offsetting or enhancing surface forcing, including the effects of sea ice dynamics. Interpretation is provided within the context of a changing climate, including intensification of the hydrological cycle and weakening of ocean transports and overturning, as well as natural decadal-to-interdacadal variability present in the system.

Circumpolar Estimates of Isopycnal Mixing in the ACC from Argo Floats

NASA Astrophysics Data System (ADS)

Roach, C. J.; Balwada, D.; Speer, K. G.

2015-12-01

There are few direct observations of cross-stream isopycnal mixing in the interior of the Southern Ocean, yet such measurements are needed to determine the role of eddies transporting properties across the ACC, and key to progress toward testing theories of meridional overturning. In light of this we examine if it is possible to obtain estimates of mixing from Argo float trajectories. We divided the Southern Ocean into overlapping 15ο longitude bins before estimating mixing. Resulting diffusivities ranged from 300 to 3000 m2s-1, with peaks corresponding to the Scotia Sea; Kerguelen and Campbell Plateaus. Comparison of our diffusivities with previous regional studies demonstrated good agreement. Tests of the methodology in the DIMES region found that mixing from Argo floats agreed closely with mixing from RAFOS floats. To further test the method we used the Southern Ocean State Estimate velocity fields to advect particles with Argo and RAFOS float like behaviours. Stirring estimates from the particles agreed well with each other in the Kerguelen Island region, South Pacific and Scotia Sea, despite the differences in the imposed behaviour. Finally, these estimates were compared to mixing length suppression theory presented in Ferrari and Nikurashin 2010. This mixing length suppression theory quantifies horizontal diffusivity similar to Prandtl (1925), but the mixing length is suppressed in the presence of mean flows and eddy phase speeds. Our results suggest that the theory can explain both the structure and magnitude of mixing using mean flow data. An exception is near the Kerguelen and Campbell Plateaus where theory under-estimates mixing relative to our results.

The ocean in near equilibrium with atmospheric methyl bromide

NASA Astrophysics Data System (ADS)

Hu, Lei; Yvon-Lewis, Shari; Liu, Yina; Bianchi, Thomas S.

2012-09-01

Saturation-anomaly measurements of methyl bromide (CH3Br) were made in the eastern Pacific (3/30-4/27, 2010) and the eastern Atlantic (10/25-11/26, 2010) to assess the oceanic saturation state as the phaseout of fumigation - non-Quarantine and Pre-Shipment (non-QPS) uses of CH3Br nears completion and atmospheric concentrations continue to decline. These cruises occurred 16 years after the Bromine Latitudinal Air-Sea Transect (BLAST) cruises, which were conducted in the same regions and first established a global oceanic net sink of -12.6 Gg yr-1 for atmospheric CH3Br in 1994. Results from this study suggest saturation anomalies of CH3Br in the surface ocean have become less negative than those observed 16 years ago as the atmospheric burden has declined over the past decade. The global net sea-to-air flux was estimated at 0 to 3 Gg yr-1 in 2010, suggesting that the ocean may become a net small source to atmospheric CH3Br. There are no significant differences between this study and previous studies for measured biological loss rate constants and calculated annual production rates, suggesting that annual production rates and biological degradation rate constants for CH3Br in the surface ocean have likely remained relatively constant over the past 16 years. When including the biological loss rate constants from this study and all previous studies, the mean global biological loss rate constant is constrained to 0.05 ± 0.01 d-1 (at a 95% confidence level). Combining chemical and eddy degradation rate constants, and using an updated gas transfer velocity, we estimate the CH3Br partial atmospheric lifetime with respect to oceanic loss to be 3.1 (2.3 to 5.0) years. Although the new partial atmospheric lifetime is about 1.3 years longer than the best prior estimate, it does not change the overall atmospheric lifetime of CH3Br, 0.8 (0.7-0.9) years.

A Markov Environment-dependent Hurricane Intensity Model and Its Comparison with Multiple Dynamic Models

NASA Astrophysics Data System (ADS)

Jing, R.; Lin, N.; Emanuel, K.; Vecchi, G. A.; Knutson, T. R.

2017-12-01

A Markov environment-dependent hurricane intensity model (MeHiM) is developed to simulate the climatology of hurricane intensity given the surrounding large-scale environment. The model considers three unobserved discrete states representing respectively storm's slow, moderate, and rapid intensification (and deintensification). Each state is associated with a probability distribution of intensity change. The storm's movement from one state to another, regarded as a Markov chain, is described by a transition probability matrix. The initial state is estimated with a Bayesian approach. All three model components (initial intensity, state transition, and intensity change) are dependent on environmental variables including potential intensity, vertical wind shear, midlevel relative humidity, and ocean mixing characteristics. This dependent Markov model of hurricane intensity shows a significant improvement over previous statistical models (e.g., linear, nonlinear, and finite mixture models) in estimating the distributions of 6-h and 24-h intensity change, lifetime maximum intensity, and landfall intensity, etc. Here we compare MeHiM with various dynamical models, including a global climate model [High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR)], a regional hurricane model (Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model), and a simplified hurricane dynamic model [Coupled Hurricane Intensity Prediction System (CHIPS)] and its newly developed fast simulator. The MeHiM developed based on the reanalysis data is applied to estimate the intensity of simulated storms to compare with the dynamical-model predictions under the current climate. The dependences of hurricanes on the environment under current and future projected climates in the various models will also be compared statistically.

Global Models of Ridge-Push Force, Geoid, and Lithospheric Strength of Oceanic plates

NASA Astrophysics Data System (ADS)

Mahatsente, Rezene

2017-12-01

An understanding of the transmission of ridge-push related stresses in the interior of oceanic plates is important because ridge-push force is one of the principal forces driving plate motion. Here, I assess the transmission of ridge-push related stresses in oceanic plates by comparing the magnitude of the ridge-push force to the integrated strength of oceanic plates. The strength is determined based on plate cooling and rheological models. The strength analysis includes low-temperature plasticity (LTP) in the upper mantle and assumes a range of possible tectonic conditions and rheology in the plates. The ridge-push force has been derived from the thermal state of oceanic lithosphere, seafloor depth and crustal age data. The results of modeling show that the transmission of ridge-push related stresses in oceanic plates mainly depends on rheology and predominant tectonic conditions. If a lithosphere has dry rheology, the estimated strength is higher than the ridge-push force at all ages for compressional tectonics and at old ages (>75 Ma) for extension. Therefore, under such conditions, oceanic plates may not respond to ridge-push force by intraplate deformation. Instead, the plates may transmit the ridge-push related stress in their interior. For a wet rheology, however, the strength of young lithosphere (<75 Ma) is much less than the ridge-push force for both compressional and extensional tectonics. In this case, the ridge-push related stress may dissipate in the interior of oceanic plates and diffuses by intraplate deformation. The state of stress within a plate depends on the balance of far-field and intraplate forces.

The impact of low pH, low aragonite saturation state on calcifying corals: an in-situ study of ocean acidification from the "ojos" of Puerto Morelos, Mexico

NASA Astrophysics Data System (ADS)

Crook, E. D.; Paytan, A.; Potts, D. C.; Hernandez Terrones, L.; Rebolledo-Vieyra, M.

2010-12-01

Recent increases in atmospheric carbon dioxide have resulted in rising aqueous CO2 concentrations that lower the pH of the oceans (Caldeira and Wickett 2003, 2005, Doney et al., 2009). It is estimated that over the next 100 years, the pH of the surface oceans will decrease by ~0.4 pH units (Orr et al., 2005), which is expected to hinder the calcifying capabilities of numerous marine organisms. Previous field work (Hall-Spencer et al., 2008) indicates that ocean acidification will negatively impact calcifying species; however, to date, very little is known about the long-term impacts of ocean acidification from the in-situ study of coral reef ecosystems. The Yucatán Peninsula of Quintana Roo, Mexico, represents an ecosystem where naturally low pH groundwater (7.14-8.07) has been discharging offshore at highly localized points (called ojos) for millennia. We present preliminary chemical and biological data on a selection of ojos from lagoon sites in Puerto Morelos, Mexico. Our findings indicate a decrease in species richness and size with proximity to the low pH waters. We address the potential long-term implications of low pH, low aragonite saturation state on coral reef ecosystems.

The impact of a pressurized regional sea or global ocean on stresses on Enceladus

NASA Astrophysics Data System (ADS)

Johnston, Stephanie A.; Montési, Laurent G. J.

2017-06-01

Liquid water is likely present in the interior of Enceladus, but it is still debated whether this water forms a global ocean or a regional sea and whether the present-day situation is stable. As the heat flux of Enceladus exceeds most heat source estimates, the liquid water is likely cooling and crystallizing, which results in expansion and pressurization of the sea or ocean. We determine, using an axisymmetric Finite Element Model, the tectonic patterns that pressurization of a regional sea or global ocean might produce at the surface of Enceladus. Tension is always predicted above where the ice is thinnest and generates cracks that might be at the origin of the Tiger Stripes. Tectonic activity is also expected in an annulus around the sea if the ice shell is in contact with but slips freely along the rocky core of the satellite. Cracks at the north pole are expected if the shell slips along the core or if there is a global ocean with thin ice at the pole. Water is likely injected along the base of the ice when the shell is grounded, which may lead to cycles of tectonic activity with the shell alternating between floating and grounded states and midlatitude faulting occurring at the transition from a grounded to a floating state.

Observed ocean thermal response to Hurricanes Gustav and Ike

NASA Astrophysics Data System (ADS)

Meyers, Patrick C.; Shay, Lynn K.; Brewster, Jodi K.; Jaimes, Benjamin

2016-01-01

The 2008 Atlantic hurricane season featured two hurricanes, Gustav and Ike, crossing the Gulf of Mexico (GOM) within a 2 week period. Over 400 airborne expendable bathythermographs (AXBTs) were deployed in a GOM field campaign before, during, and after the passage of Gustav and Ike to measure the evolving upper ocean thermal structure. AXBT and drifter deployments specifically targeted the Loop Current (LC) complex, which was undergoing an eddy-shedding event during the field campaign. Hurricane Gustav forced a 50 m deepening of the ocean mixed layer (OML), dramatically altering the prestorm ocean conditions for Hurricane Ike. Wind-forced entrainment of colder thermocline water into the OML caused sea surface temperatures to cool by over 5°C in GOM common water, but only 1-2°C in the LC complex. Ekman pumping and a near-inertial wake were identified by fluctuations in the 20°C isotherm field observed by AXBTs and drifters following Hurricane Ike. Satellite estimates of the 20° and 26°C isotherm depths and ocean heat content were derived using a two-layer model driven by sea surface height anomalies. Generally, the satellite estimates correctly characterized prestorm conditions, but the two-layer model inherently could not resolve wind-forced mixing of the OML. This study highlights the importance of a coordinated satellite and in situ measurement strategy to accurately characterize the ocean state before, during, and after hurricane passage, particularly in the case of two consecutive storms traveling through the same domain.

30 CFR 291.105 - What must a complaint contain?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 2 2011-07-01 2011-07-01 false What must a complaint contain? 291.105 Section 291.105 Mineral Resources BUREAU OF OCEAN ENERGY MANAGEMENT, REGULATION, AND ENFORCEMENT, DEPARTMENT... impacts; (d) Estimate any financial impact or burden; (e) State the specific relief or remedy requested...

A Stable U Isotopic Perspective on the U Budget and Global Extent of Modern Anoxia in the Ocean.

NASA Astrophysics Data System (ADS)

Tissot, F.; Dauphas, N.

2015-12-01

Isotopic fractionation between U4+ and U6+makes U stable isotopes potential tracers of global paleoredox conditions. In this work [1], we put the U-proxy up to a test against a highly constrained system: the modern ocean. We measured a large number of seawater samples from geographically diverse locations and found that the open ocean has a homogenous isotopic composition at δ238USW= -0.392 ± 0.005 ‰ (rel. to CRM-112a). From our measurement of rock samples (n=64) and compilations of literature data (n=380), we then estimated the U isotopic compositions of the various reservoirs involved in the modern oceanic U budget, as well as the fractionation factors associated with U incorporation into those reservoirs. Using a steady-state model, we compared the isotopic composition of the seawater predicted by the four most recent U oceanic budgets [2-5] to the modern seawater value we measured. Three of these budgets [2-4] predict a seawater isotopic composition in very good agreement with the observed δ238USW, which strengthens our confidence in the isotopic fractionation factors associated with each deposition environment and the fact that U is at steady-state in the modern ocean. The U oceanic budget of Henderson and Anderson (2003) does not reproduce the observed seawater composition because the U flux to anoxic/euxinic sediments relative to the total U flux out of the ocean is high in their model, which our analysis shows cannot be correct. The U isotopic composition of seawater is used to constrain the extent of anoxia in the modern ocean (% of seafloor covered by anoxic/euxinic sediments), which is 0.21 ± 0.09 %. This work demonstrates that stable isotopes of U can indeed trace the extent of anoxia in the modern global ocean, thereby validating the application of U isotope measurements to paleoredox reconstructions. Based on the above work, we will present the best estimate of the modern oceanic U budget. [1] Tissot F.L.H., Dauphas N. (2015) Geochim Cosmochim Ac 167, 113-143 [2] Barnes C. E., Cochran J. K. (1990) Earth Planet Sc Lett 97, 94-101 [3] Morford J. L., Emerson S. (1999) Geochim Cosmochim Ac 63, 1735-1750 [4] Dunk R. M., Mills R. A., Jenkins W. J. (2002) Chemical Geology 190, 45-67 [5] Henderson G. M., Anderson R. F. (2003) Rev Mineral Geochem 52, 493-531

Improvements to the swath-level near-surface atmospheric state parameter retrievals within the NRL Ocean Surface Flux System (NFLUX)

NASA Astrophysics Data System (ADS)

May, J. C.; Rowley, C. D.; Meyer, H.

2017-12-01

The Naval Research Laboratory (NRL) Ocean Surface Flux System (NFLUX) is an end-to-end data processing and assimilation system used to provide near-real-time satellite-based surface heat flux fields over the global ocean. The first component of NFLUX produces near-real-time swath-level estimates of surface state parameters and downwelling radiative fluxes. The focus here will be on the satellite swath-level state parameter retrievals, namely surface air temperature, surface specific humidity, and surface scalar wind speed over the ocean. Swath-level state parameter retrievals are produced from satellite sensor data records (SDRs) from four passive microwave sensors onboard 10 platforms: the Special Sensor Microwave Imager/Sounder (SSMIS) sensor onboard the DMSP F16, F17, and F18 platforms; the Advanced Microwave Sounding Unit-A (AMSU-A) sensor onboard the NOAA-15, NOAA-18, NOAA-19, Metop-A, and Metop-B platforms; the Advanced Technology Microwave Sounder (ATMS) sensor onboard the S-NPP platform; and the Advanced Microwave Scannin Radiometer 2 (AMSR2) sensor onboard the GCOM-W1 platform. The satellite SDRs are translated into state parameter estimates using multiple polynomial regression algorithms. The coefficients to the algorithms are obtained using a bootstrapping technique with all available brightness temperature channels for a given sensor, in addition to a SST field. For each retrieved parameter for each sensor-platform combination, unique algorithms are developed for ascending and descending orbits, as well as clear vs cloudy conditions. Each of the sensors produces surface air temperature and surface specific humidity retrievals. The SSMIS and AMSR2 sensors also produce surface scalar wind speed retrievals. Improvement is seen in the SSMIS retrievals when separate algorithms are used for the even and odd scans, with the odd scans performing better than the even scans. Currently, NFLUX treats all SSMIS scans as even scans. Additional improvement in all of the surface retrievals comes from using a 3-hourly SST field, as opposed to a daily SST field.

Ocean heat content variability in an ensemble of twentieth century ocean reanalyses

NASA Astrophysics Data System (ADS)

de Boisséson, Eric; Balmaseda, Magdalena Alonso; Mayer, Michael

2017-08-01

This paper presents a ten-member ensemble of twentieth century Ocean ReAnalyses called ORA-20C. ORA-20C assimilates temperature and salinity profiles and is forced by the ECMWF twentieth century atmospheric reanalysis (ERA-20C) over the 1900-2010 period. This study attempts to identify robust signals of ocean heat content change in ORA-20C and detect contamination by model errors, initial condition uncertainty, surface fluxes and observing system changes. It is shown that ORA-20C trends and variability in the first part of the century result from the surface fluxes and model drift towards a warmer mean state and weak meridional overturning circulation. The impact of the observing system in correcting the mean state causes the deceleration of the warming trend and alters the long-term climate signal. The ensemble spread reflects the long-lasting memory of the initial conditions and the convergence of the system to a solution compatible with surface fluxes, the ocean model and observational constraints. Observations constrain the ocean heat uptake trend in the last decades of the twentieth century, which is similar to trend estimations from the post-satellite era. An ocean heat budget analysis attributes ORA-20C heat content changes to surface fluxes in the first part of the century. The heat flux variability reflects spurious signals stemming from ERA-20C surface fields, which in return result from changes in the atmospheric observing system. The influence of the temperature assimilation increments on the heat budget is growing with time. Increments control the most recent ocean heat uptake signals, highlighting imbalances in forced reanalysis systems in the ocean as well as in the atmosphere.

Deriving Two-Dimensional Ocean Wave Spectra and Surface Height Maps from the Shuttle Imaging Radar (SIR-B)

NASA Technical Reports Server (NTRS)

Tilley, D. G.

1986-01-01

Directional ocean wave spectra were derived from Shuttle Imaging Radar (SIR-B) imagery in regions where nearly simultaneous aircraft-based measurements of the wave spectra were also available as part of the NASA Shuttle Mission 41G experiments. The SIR-B response to a coherently speckled scene is used to estimate the stationary system transfer function in the 15 even terms of an eighth-order two-dimensional polynomial. Surface elevation contours are assigned to SIR-B ocean scenes Fourier filtered using a empirical model of the modulation transfer function calibrated with independent measurements of wave height. The empirical measurements of the wave height distribution are illustrated for a variety of sea states.

A Decade of Satellite Ocean Color Observations

NASA Technical Reports Server (NTRS)

McClain, Charles R.

2009-01-01

After the successful Coastal Zone Color Scanner (CZCS, 1978-1986), demonstration that quantitative estimations of geophysical variables such as chlorophyll a and diffuse attenuation coefficient could be derived from top of the atmosphere radiances, a number of international missions with ocean color capabilities were launched beginning in the late 1990s. Most notable were those with global data acquisition capabilities, i.e., the Ocean Color and Temperature Sensor (OCTS 1996-1997), the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, United States, 1997-present), two Moderate Resolution Imaging Spectroradiometers, (MODIS, United States, Terra/2000-present and Aqua/2002-present), the Global Imager (GLI, Japan, 2002-2003), and the Medium Resolution Imaging Spectrometer (MERIS, European Space Agency, 2002-present). These missions have provided data of exceptional quality and continuity, allowing for scientific inquiries into a wide variety of marine research topics not possible with the CZCS. This review focuses on the scientific advances made over the past decade using these data sets.

Evaluating Carbonate System Algorithms in a Nearshore System: Does Total Alkalinity Matter?

PubMed Central

Sweet, Julia; Brzezinski, Mark A.; McNair, Heather M.; Passow, Uta

2016-01-01

Ocean acidification is a threat to many marine organisms, especially those that use calcium carbonate to form their shells and skeletons. The ability to accurately measure the carbonate system is the first step in characterizing the drivers behind this threat. Due to logistical realities, regular carbonate system sampling is not possible in many nearshore ocean habitats, particularly in remote, difficult-to-access locations. The ability to autonomously measure the carbonate system in situ relieves many of the logistical challenges; however, it is not always possible to measure the two required carbonate parameters autonomously. Observed relationships between sea surface salinity and total alkalinity can frequently provide a second carbonate parameter thus allowing for the calculation of the entire carbonate system. Here, we assessed the rigor of estimating total alkalinity from salinity at a depth <15 m by routinely sampling water from a pier in southern California for several carbonate system parameters. Carbonate system parameters based on measured values were compared with those based on estimated TA values. Total alkalinity was not predictable from salinity or from a combination of salinity and temperature at this site. However, dissolved inorganic carbon and the calcium carbonate saturation state of these nearshore surface waters could both be estimated within on average 5% of measured values using measured pH and salinity-derived or regionally averaged total alkalinity. Thus we find that the autonomous measurement of pH and salinity can be used to monitor trends in coastal changes in DIC and saturation state and be a useful method for high-frequency, long-term monitoring of ocean acidification. PMID:27893739

Evaluating Carbonate System Algorithms in a Nearshore System: Does Total Alkalinity Matter?

PubMed

Jones, Jonathan M; Sweet, Julia; Brzezinski, Mark A; McNair, Heather M; Passow, Uta

2016-01-01

Ocean acidification is a threat to many marine organisms, especially those that use calcium carbonate to form their shells and skeletons. The ability to accurately measure the carbonate system is the first step in characterizing the drivers behind this threat. Due to logistical realities, regular carbonate system sampling is not possible in many nearshore ocean habitats, particularly in remote, difficult-to-access locations. The ability to autonomously measure the carbonate system in situ relieves many of the logistical challenges; however, it is not always possible to measure the two required carbonate parameters autonomously. Observed relationships between sea surface salinity and total alkalinity can frequently provide a second carbonate parameter thus allowing for the calculation of the entire carbonate system. Here, we assessed the rigor of estimating total alkalinity from salinity at a depth <15 m by routinely sampling water from a pier in southern California for several carbonate system parameters. Carbonate system parameters based on measured values were compared with those based on estimated TA values. Total alkalinity was not predictable from salinity or from a combination of salinity and temperature at this site. However, dissolved inorganic carbon and the calcium carbonate saturation state of these nearshore surface waters could both be estimated within on average 5% of measured values using measured pH and salinity-derived or regionally averaged total alkalinity. Thus we find that the autonomous measurement of pH and salinity can be used to monitor trends in coastal changes in DIC and saturation state and be a useful method for high-frequency, long-term monitoring of ocean acidification.

Optimizing Ocean Space: Co-siting Open Ocean Aquaculture

NASA Astrophysics Data System (ADS)

Cobb, B. L.; Wickliffe, L. C.; Morris, J. A., Jr.

2016-12-01

In January of 2016, NOAA's National Marine Fisheries Service released the Gulf Aquaculture Plan (GAP) to manage the development of environmentally sound and economically sustainable open ocean finfish aquaculture in the Gulf of Mexico (inside the U.S. Exclusive Economic Zone [EEZ]). The GAP provides the first regulatory framework for aquaculture in federal waters with estimated production of 64 million pounds of finfish, and an estimated economic impact of $264 million annually. The Gulf of Mexico is one of the most industrialized ocean basins in the world, with many existing ocean uses including oil and natural gas production, shipping and commerce, commercial fishing operations, and many protected areas to ensure conservation of valuable ecosystem resources and services. NOAA utilized spatial planning procedures and tools identifying suitable sites for establishing aquaculture through exclusion analyses using authoritative federal and state data housed in a centralized geodatabase. Through a highly collaborative, multi-agency effort a mock permitting exercise was conducted to illustrate the regulatory decision-making process for the Gulf. Further decision-making occurred through exploring co-siting opportunities with oil and natural gas platforms. Logistical co-siting was conducted to reduce overall operational costs by looking at distance to major port and commodity tonnage at each port. Importantly, the process of co-siting allows aquaculture to be coupled with other benefits, including the availability of previously established infrastructure and the reduction of environmental impacts.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Oceanic Loading and Local Distortions at the Baksan, Russia, and Gran Sasso, Italy, Strain Stations

NASA Astrophysics Data System (ADS)

Milyukov, V. K.; Amoruso, A.; Crescentini, L.; Mironov, A. P.; Myasnikov, A. V.; Lagutkina, A. V.

2018-03-01

Reliable use of strain data in geophysical studies requires their preliminary correction for ocean loading and various local distortions. These effects, in turn, can be estimated from the tidal records which are contributed by solid and oceanic loading. In this work, we estimate the oceanic tidal loading at two European strain stations (Baksan, Russia, and Gran Sasso, Italy) by analyzing the results obtained with the different Earth and ocean models. The influence of local distortions on the strain measurements at the two stations is estimated.

Atlantic meridional heat transports computed from balancing Earth's energy locally: AMOC and Ocean Meridional Heat Transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trenberth, Kevin E.; Fasullo, John T.

The Atlantic Meridional Overturning Circulation plays a major role in moving heat and carbon around in the ocean. A new estimate of ocean heat transports for 2000 through 2013 throughout the Atlantic is derived. Top-of-atmosphere radiation is combined with atmospheric reanalyses to estimate surface heat fluxes and combined with vertically integrated ocean heat content to estimate ocean heat transport divergence as a residual. Atlantic peak northward ocean heat transports average 1.18 ± 0.13PW (1 sigma) at 15°N but vary considerably in latitude and time. Results agree well with observational estimates at 26.5°N from the RAPID array, but for 2004–2013 themore » meridional heat transport is 1.00 ± 0.11PW versus 1.23 ± 0.11PW for RAPID. In addition, these results have no hint of a trend, unlike the RAPID results. Finally, strong westerlies north of a meridian drive ocean currents and an ocean heat loss into the atmosphere that is exacerbated by a decrease in ocean heat transport northward.« less

Atlantic meridional heat transports computed from balancing Earth's energy locally: AMOC and Ocean Meridional Heat Transport

DOE PAGES

Trenberth, Kevin E.; Fasullo, John T.

2017-02-18

The Atlantic Meridional Overturning Circulation plays a major role in moving heat and carbon around in the ocean. A new estimate of ocean heat transports for 2000 through 2013 throughout the Atlantic is derived. Top-of-atmosphere radiation is combined with atmospheric reanalyses to estimate surface heat fluxes and combined with vertically integrated ocean heat content to estimate ocean heat transport divergence as a residual. Atlantic peak northward ocean heat transports average 1.18 ± 0.13PW (1 sigma) at 15°N but vary considerably in latitude and time. Results agree well with observational estimates at 26.5°N from the RAPID array, but for 2004–2013 themore » meridional heat transport is 1.00 ± 0.11PW versus 1.23 ± 0.11PW for RAPID. In addition, these results have no hint of a trend, unlike the RAPID results. Finally, strong westerlies north of a meridian drive ocean currents and an ocean heat loss into the atmosphere that is exacerbated by a decrease in ocean heat transport northward.« less

Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations

NASA Astrophysics Data System (ADS)

Durán Moro, Marina; Brankart, Jean-Michel; Brasseur, Pierre; Verron, Jacques

2017-07-01

Satellite sensors increasingly provide high-resolution (HR) observations of the ocean. They supply observations of sea surface height (SSH) and of tracers of the dynamics such as sea surface salinity (SSS) and sea surface temperature (SST). In particular, the Surface Water Ocean Topography (SWOT) mission will provide measurements of the surface ocean topography at very high-resolution (HR) delivering unprecedented information on the meso-scale and submeso-scale dynamics. This study investigates the feasibility to use these measurements to reconstruct meso-scale features simulated by numerical models, in particular on the vertical dimension. A methodology to reconstruct three-dimensional (3D) multivariate meso-scale scenes is developed by using a HR numerical model of the Solomon Sea region. An inverse problem is defined in the framework of a twin experiment where synthetic observations are used. A true state is chosen among the 3D multivariate states which is considered as a reference state. In order to correct a first guess of this true state, a two-step analysis is carried out. A probability distribution of the first guess is defined and updated at each step of the analysis: (i) the first step applies the analysis scheme of a reduced-order Kalman filter to update the first guess probability distribution using SSH observation; (ii) the second step minimizes a cost function using observations of HR image structure and a new probability distribution is estimated. The analysis is extended to the vertical dimension using 3D multivariate empirical orthogonal functions (EOFs) and the probabilistic approach allows the update of the probability distribution through the two-step analysis. Experiments show that the proposed technique succeeds in correcting a multivariate state using meso-scale and submeso-scale information contained in HR SSH and image structure observations. It also demonstrates how the surface information can be used to reconstruct the ocean state below the surface.

Variational stereo imaging of oceanic waves with statistical constraints.

PubMed

Gallego, Guillermo; Yezzi, Anthony; Fedele, Francesco; Benetazzo, Alvise

2013-11-01

An image processing observational technique for the stereoscopic reconstruction of the waveform of oceanic sea states is developed. The technique incorporates the enforcement of any given statistical wave law modeling the quasi-Gaussianity of oceanic waves observed in nature. The problem is posed in a variational optimization framework, where the desired waveform is obtained as the minimizer of a cost functional that combines image observations, smoothness priors and a weak statistical constraint. The minimizer is obtained by combining gradient descent and multigrid methods on the necessary optimality equations of the cost functional. Robust photometric error criteria and a spatial intensity compensation model are also developed to improve the performance of the presented image matching strategy. The weak statistical constraint is thoroughly evaluated in combination with other elements presented to reconstruct and enforce constraints on experimental stereo data, demonstrating the improvement in the estimation of the observed ocean surface.

Global distribution and surface activity of macromolecules in offline simulations of marine organic chemistry

DOE PAGES

Ogunro, Oluwaseun O.; Burrows, Susannah M.; Elliott, Scott; ...

2015-10-13

Here, organic macromolecules constitute high percentage components of remote sea spray. They enter the atmosphere through adsorption onto bubbles followed by bursting at the ocean surface, and go on to influence the chemistry of the fine mode aerosol. We present a global estimate of mixed-layer organic macromolecular distributions, driven by offline marine systems model output. The approach permits estimation of oceanic concentrations and bubble film surface coverages for several classes of organic compound. Mixed layer levels are computed from the output of a global ocean biogeochemistry model by relating the macromolecules to standard biogeochemical tracers. Steady state is assumed formore » labile forms, and for longer-lived components we rely on ratios to existing transported variables. Adsorption is then represented through conventional Langmuir isotherms, with equilibria deduced from laboratory analogs. Open water concentrations locally exceed one micromolar carbon for the total of protein, polysaccharide and refractory heteropolycondensate. The shorter-lived lipids remain confined to regions of strong biological activity. Results are evaluated against available measurements for all compound types, and agreement is generally quite reasonable. Global distributions are further estimated for both fractional coverage of bubble films at the air-water interface and the two-dimensional concentration excess. Overall, we show that macromolecular mapping provides a novel tool for the comprehension of oceanic surfactant distributions. Results may prove useful in planning field experiments and assessing the potential response of surface chemical behaviors to global change.« less

Physical state of the very early Earth

NASA Astrophysics Data System (ADS)

Abe, Yutaka

1993-09-01

The earliest surface environment of the Earth is reconstructed in accordance with the planetary formation theory. Formation of an atmosphere is an inevitable consequence of Earth's formation. The atmosphere near the close of accretion is composed of 200 ˜ 300 bars of H 2 and H 2O, and several tens of bars of CO and CO 2. Either by the blanketing effect of the proto-atmosphere or heating by large planetesimal impacts a magma ocean is formed during accretion. We can distinguish three stages for the thermal evolution of the magma ocean and proto-crust. Stage 0 is characterized by a super-liquidus (or completely molten) regime near the surface. At this stage the surface of the Earth is covered by a super-liquidus magma ocean. No chemical differentiation is expected during this stage. Once the energy flux released by planet formation decreases to the 200 W/m 2 level the super-liquidus magma ocean then disappears within a time interval of 1 m.y. This is the transition from stage 0 to 1. Stage 1 is characterized by a partially molten magma ocean. In the magma ocean consisting of 20 ˜ 30% partial melt, heat transport is controlled by melt-solid separation (a type of compositional convection) rather than thermal convection. Chemical differentiation of the mantle mainly occurs in this stage. Once the energy flux drops to the 160 W/m 2 level, more than 90% of water vapor in the proto-atmosphere condense to form the proto-oceans. Several tens of bars of CO and CO 2 remain in the atmosphere just after formation of the oceans. Water oceans are occasionally evaporated by large impacts. After each such event, recondensation of the ocean takes several hundred years. Although the surface is covered by a chilled proto-crust, it is short-lived because of extensive volcanic resurfacing activity as well as meteorite impacts resurfacing. This stage ends when the energy flux drops to 0.1 ˜ 1 W/m 2 level. The duration time of stage 1 is estimated to be several hundred million years (the best estimate is about 400 m.y.). Stage 2 is characterized by solid state convection. This stage continues to the present day. One of the most important change on the proto-Earth is the transition from stage 1 to 2, which occurs several hundred million years after the Earth formation. Long-lived crust is formed only after this transition.

Assessment of changes in nutrient and sediment delivery to and carbon accumulation in coastal oceans of the Eastern United States

NASA Astrophysics Data System (ADS)

Bergamaschi, B. A.; Smith, R. A.; Shih, J. S.; Sohl, T. L.; Sleeter, B. M.; Zhu, Z.

2014-12-01

Land-use and land-cover distributions are primary determinants of terrestrial fluxes of sediments and nutrients to coastal oceans. Sediment and nutrient delivery to coastal waters have already been significantly altered by changes in population and land use, resulting in modified patterns of coastal production and carbon storage. Continued population growth and increasing agricultural areal extent and intensity are expected to accelerate these changes. The USGS LandCarbon project developed prospective future land use and land cover projections based on IPCC scenarios A1b, A2 and B1 to 2050 as the basis for a multitude of biogeochemical assessments. We assessed the impacts on delivery of nutrients and sediments to the coastal ocean, and concomitant carbon storage. Fluxes were estimated using the SPARROW model, calibrated on historical water quality measurements. Significantly greater fluxes of nutrients and sediments to coastal waters by 2050 are projected by the model. For example, for the Eastern United States, nitrate fluxes for 2050 are projected to be16 to 52 percent higher than the baseline year, depending on scenario. As a consequence, an associated increase in the frequency and duration of coastal and estuarine hypoxia events and harmful algal blooms could be expected. Model estimates indicate that these prospective future nutrient and sediment fluxes will increase carbon storage rates in coastal waters by 18 to 56 percent in some regions.

What We Do Not Yet Know About Global Ocean Depths, and How Satellite Altimetry Can Help

NASA Astrophysics Data System (ADS)

Smith, W. H. F.; Sandwell, D. T.; Marks, K. M.

2017-12-01

Half Earth's ocean floor area lies several km or more away from the nearest depth measurement. Areas more than 50 km from any sounding sum to a total area larger than the entire United States land area; areas more than 100 km from any sounding comprise a total area larger than Alaska. In remote basins the majority of available data were collected before the mid-1960s, and so often are mis-located by many km, as well as mis-digitized. Satellite altimetry has mapped the marine gravity field with better than 10 km horizontal resolution, revealing nearly all seamounts taller than 2 km; new data can detect some seamounts less than 1 km tall. Seafloor topography can be estimated from satellite altimetry if sediment is thin and relief is due to seafloor spreading and mid-plate volcanism. The accuracy of the estimate depends on the geological nature of the relief and on the accuracy of the soundings available to calibrate the estimation. At best, the estimate is a band-pass-filtered version of the true depth variations, but does not resolve the small-scale seafloor roughness needed to model mixing and dissipation in the ocean. In areas of thick or variable sediment cover there can be little correlation between depth and altimetry. Yet altimeter-estimated depth is the best guess available in most of the ocean. The MH370 search area provides an illustration. Prior to the search it was very sparsely (1% to 5%) covered by soundings, many of these were old, low-tech data, and plateaus with thick sediments complicate the estimation of depth from altimetry. Even so, the estimate was generally correct about the tectonic nature of the terrain and the extent of depth variations to be expected. If ships will fill gaps strategically, visiting areas where altimetry shows that interesting features will be found, and passing near the centroids of the larger gaps, the data will be exciting in their own right and will also improve future altimetry estimates.

Revised budget for the oceanic uptake of anthropogenic carbon dioxide

USGS Publications Warehouse

Sarmiento, J.L.; Sundquist, E.T.

1992-01-01

TRACER-CALIBRATED models of the total uptake of anthropogenic CO2 by the world's oceans give estimates of about 2 gigatonnes carbon per year1, significantly larger than a recent estimate2 of 0.3-0.8 Gt C yr-1 for the synoptic air-to-sea CO2 influx. Although both estimates require that the global CO2 budget must be balanced by a large unknown terrestrial sink, the latter estimate implies a much larger terrestrial sink, and challenges the ocean model calculations on which previous CO2 budgets were based. The discrepancy is due in part to the net flux of carbon to the ocean by rivers and rain, which must be added to the synoptic air-to-sea CO2 flux to obtain the total oceanic uptake of anthropogenic CO2. Here we estimate the magnitude of this correction and of several other recently proposed adjustments to the synoptic air-sea CO2 exchange. These combined adjustments minimize the apparent inconsistency, and restore estimates of the terrestrial sink to values implied by the modelled oceanic uptake.

Satellite based Ocean Forecasting, the SOFT project

NASA Astrophysics Data System (ADS)

Stemmann, L.; Tintoré, J.; Moneris, S.

2003-04-01

The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

Analysis of satellite altimeter signal characteristics and investigation of sea-truth data requirements

NASA Technical Reports Server (NTRS)

1972-01-01

Results are presented of analysis of satellite signal characteristics as influenced by ocean surface roughness and an investigation of sea truth data requirements. The first subject treated is that of postflight waveform reconstruction for the Skylab S-193 radar altimeter. Sea state estimation accuracies are derived based on analytical and hybrid computer simulation techniques. An analysis of near-normal incidence, microwave backscattering from the ocean's surface is accomplished in order to obtain the minimum sea truth data necessary for good agreement between theoretical and experimental scattering results. Sea state bias is examined from the point of view of designing an experiment which will lead to a resolution of the problem. A discussion is given of some deficiencies which were found in the theory underlying the Stilwell technique for spectral measurements.

Antarctic Ocean Tides from GRACE Intersatellite Tracking Data and Hydrodynamic Assimilation

NASA Astrophysics Data System (ADS)

Erofeeva, S.; Han, S.; Ray, R.; Egbert, G.; Luthcke, S.

2007-12-01

Long-wavelength components of the oceanic tides surrounding Antarctica are estimated from over three years of GRACE satellite-to-satellite ranging measurements. An inversion is performed for the major constituents M2, O1, and S2, parameterized as localized average mass anomalies relative to a prior tidal model. Satellite state adjustments are made simultaneously. These long-wavelength anomalies are then assimilated into a high-resolution regional hydrodynamic tidal model. Comparisons to independent "ground truth" data, previously collected by King and Padman, show that assimilation of the GRACE inversions results in improved accuracy, for all three constituents.

Model projections of rapid sea-level rise on the northeast coast of the United States

NASA Astrophysics Data System (ADS)

Yin, Jianjun; Schlesinger, Michael E.; Stouffer, Ronald J.

2009-04-01

Human-induced climate change could cause global sea-level rise. Through the dynamic adjustment of the sea surface in response to a possible slowdown of the Atlantic meridional overturning circulation, a warming climate could also affect regional sea levels, especially in the North Atlantic region, leading to high vulnerability for low-lying Florida and western Europe. Here we analyse climate projections from a set of state-of-the-art climate models for such regional changes, and find a rapid dynamical rise in sea level on the northeast coast of the United States during the twenty-first century. For New York City, the rise due to ocean circulation changes amounts to 15, 20 and 21cm for scenarios with low, medium and high rates of emissions respectively, at a similar magnitude to expected global thermal expansion. Analysing one of the climate models in detail, we find that a dynamic, regional rise in sea level is induced by a weakening meridional overturning circulation in the Atlantic Ocean, and superimposed on the global mean sea-level rise. We conclude that together, future changes in sea level and ocean circulation will have a greater effect on the heavily populated northeastern United States than estimated previously.

Model Projections of Rapid Sea-Level Rise on the Northeast Coast of the United States

NASA Astrophysics Data System (ADS)

Yin, J.; Schlesinger, M.; Stouffer, R. J.

2009-12-01

Human-induced climate change could cause global sea-level rise. Through the dynamic adjustment of the sea surface in response to a possible slowdown of the Atlantic meridional overturning circulation, a warming climate could also affect regional sea levels, especially in the North Atlantic region, leading to high vulnerability for low-lying Florida and western Europe. In the present study, we analyse climate projections from a set of state-of-the-art climate models for such regional changes, and find a rapid dynamical rise in sea level on the northeast coast of the United States during the twenty-first century. For New York City, the rise due to ocean circulation changes amounts to 15, 20 and 21 cm for scenarios with low, medium and high rates of emissions respectively, at a similar magnitude to expected global thermal expansion. Analysing one of the climate models in detail, we find that a dynamic, regional rise in sea level is induced by a weakening meridional overturning circulation in the Atlantic Ocean, and superimposed on the global mean sea level rise. We conclude that together, future changes in sea level and ocean circulation will have a greater effect on the heavily populated northeastern United States than estimated previously.

NASA Supercomputer Improves Prospects for Ocean Climate Research

NASA Technical Reports Server (NTRS)

Menemenlis, D.; Hill, C.; Adcroft, A.; Campin, J. -M.; Cheng, B.; Ciotti, B.; Fukumori, I.; Heimbach, P.; Henze, C.; Kohl, A.;

Ocean impact on decadal Atlantic climate variability revealed by sea-level observations.

PubMed

McCarthy, Gerard D; Haigh, Ivan D; Hirschi, Joël J-M; Grist, Jeremy P; Smeed, David A

2015-05-28

Decadal variability is a notable feature of the Atlantic Ocean and the climate of the regions it influences. Prominently, this is manifested in the Atlantic Multidecadal Oscillation (AMO) in sea surface temperatures. Positive (negative) phases of the AMO coincide with warmer (colder) North Atlantic sea surface temperatures. The AMO is linked with decadal climate fluctuations, such as Indian and Sahel rainfall, European summer precipitation, Atlantic hurricanes and variations in global temperatures. It is widely believed that ocean circulation drives the phase changes of the AMO by controlling ocean heat content. However, there are no direct observations of ocean circulation of sufficient length to support this, leading to questions about whether the AMO is controlled from another source. Here we provide observational evidence of the widely hypothesized link between ocean circulation and the AMO. We take a new approach, using sea level along the east coast of the United States to estimate ocean circulation on decadal timescales. We show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres--the intergyre region. These circulation changes affect the decadal evolution of North Atlantic heat content and, consequently, the phases of the AMO. The Atlantic overturning circulation is declining and the AMO is moving to a negative phase. This may offer a brief respite from the persistent rise of global temperatures, but in the coupled system we describe, there are compensating effects. In this case, the negative AMO is associated with a continued acceleration of sea-level rise along the northeast coast of the United States.

Stirring Up the Biological Pump: Vertical Mixing and Carbon Export in the Southern Ocean

NASA Astrophysics Data System (ADS)

Stukel, Michael R.; Ducklow, Hugh W.

2017-09-01

The biological carbon pump (BCP) transports organic carbon from the surface to the ocean's interior via sinking particles, vertically migrating organisms, and passive transport of organic matter by advection and diffusion. While many studies have quantified sinking particles, the magnitude of passive transport remains poorly constrained. In the Southern Ocean weak thermal stratification, strong vertical gradients in particulate organic matter, and weak vertical nitrate gradients suggest that passive transport from the euphotic zone may be particularly important. We compile data from seasonal time series at a coastal site near Palmer Station, annual regional cruises in the Western Antarctic Peninsula (WAP), cruises throughout the broader Southern Ocean, and SOCCOM (Southern Ocean Carbon and Climate Observations and Modeling) autonomous profiling floats to estimate spatial and temporal patterns in vertical gradients of nitrate, particulate nitrogen (PN), and dissolved organic carbon. Under a steady state approximation, the ratio of ∂PN/∂z to ∂NO3-/∂z suggests that passive transport of PN may be responsible for removing 46% (37%-58%) of the nitrate introduced into the surface ocean of the WAP (with dissolved organic matter contributing an additional 3-6%) and for 23% (19%-28%) of the BCP in the broader Southern Ocean. A simple model parameterized with in situ nitrate, PN, and primary production data suggested that passive transport was responsible for 54% of the magnitude of the BCP in the WAP. Our results highlight the potential importance of passive transport (by advection and diffusion) of organic matter in the Southern Ocean but should only be considered indicative of high passive transport (rather than conclusive evidence) due to our steady state assumptions.

Plumes and Blooms: Observations, Analysis and Modeling for SIMBIOS

NASA Technical Reports Server (NTRS)

Maritorena, S.; Siegel, D. A.; Nelson, N. B.

2004-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-the-art ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case II environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. A primary goal is the use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions.

Inventory and transport of plastic debris in the Laurentian Great Lakes.

PubMed

Hoffman, Matthew J; Hittinger, Eric

2017-02-15

Plastic pollution in the world's oceans has received much attention, but there has been increasing concern about the high concentrations of plastic debris in the Laurentian Great Lakes. Using census data and methodologies used to study ocean debris we derive a first estimate of 9887 metric tonnes per year of plastic debris entering the Great Lakes. These estimates are translated into population-dependent particle inputs which are advected using currents from a hydrodynamic model to map the spatial distribution of plastic debris in the Great Lakes. Model results compare favorably with previously published sampling data. The samples are used to calibrate the model to derive surface microplastic mass estimates of 0.0211 metric tonnes in Lake Superior, 1.44 metric tonnes in Huron, and 4.41 metric tonnes in Erie. These results have many applications, including informing cleanup efforts, helping target pollution prevention, and understanding the inter-state or international flows of plastic pollution. Copyright © 2016 Elsevier Ltd. All rights reserved.

Geothermal state and fluid flow within ODP Hole 843B: results from wireline logging

NASA Astrophysics Data System (ADS)

Wiggins, Sean M.; Hildebrand, John A.; Gieskes, Joris M.

2002-02-01

Borehole fluid temperatures were measured with a wireline re-entry system in Ocean Drilling Program Hole 843B, the site of the Ocean Seismic Network Pilot Experiment. These temperature data, recorded more than 7 years after drilling, are compared to temperature data logged during Leg 136, approximately 1 day after drilling had ceased. Qualitative interpretations of the temperature data suggest that fluid flowed slowly downward in the borehole immediately following drilling, and flowed slowly upward 7 years after drilling. Quantitative analysis suggests that the upward fluid flow rate in the borehole is approximately 1 m/h. Slow fluid flow interpreted from temperature data only, however, requires estimates of other unmeasured physical properties. If fluid flows upward in Hole 843B, it may have led to undesirable noise for the borehole seismometer emplaced in this hole as part of the Ocean Seismic Network Pilot Experiment. Estimates of conductive heat flow from ODP Hole 843B are 51 mW/m 2 for the sediment and the basalt. These values are lower than the most recent Hawaiian Arch seafloor heat flow studies.

A Model-Based Evaluation of the Inverse Gaussian Transit-Time Distribution Method for Inferring Anthropogenic Carbon Storage in the Ocean

NASA Astrophysics Data System (ADS)

He, Yan-Chun; Tjiputra, Jerry; Langehaug, Helene R.; Jeansson, Emil; Gao, Yongqi; Schwinger, Jörg; Olsen, Are

2018-03-01

The Inverse Gaussian approximation of transit time distribution method (IG-TTD) is widely used to infer the anthropogenic carbon (Cant) concentration in the ocean from measurements of transient tracers such as chlorofluorocarbons (CFCs) and sulfur hexafluoride (SF6). Its accuracy relies on the validity of several assumptions, notably (i) a steady state ocean circulation, (ii) a prescribed age tracer saturation history, e.g., a constant 100% saturation, (iii) a prescribed constant degree of mixing in the ocean, (iv) a constant surface ocean air-sea CO2 disequilibrium with time, and (v) that preformed alkalinity can be sufficiently estimated by salinity or salinity and temperature. Here, these assumptions are evaluated using simulated "model-truth" of Cant. The results give the IG-TTD method a range of uncertainty from 7.8% to 13.6% (11.4 Pg C to 19.8 Pg C) due to above assumptions, which is about half of the uncertainty derived in previous model studies. Assumptions (ii), (iv) and (iii) are the three largest sources of uncertainties, accounting for 5.5%, 3.8% and 3.0%, respectively, while assumptions (i) and (v) only contribute about 0.6% and 0.7%. Regionally, the Southern Ocean contributes the largest uncertainty, of 7.8%, while the North Atlantic contributes about 1.3%. Our findings demonstrate that spatial-dependency of Δ/Γ, and temporal changes in tracer saturation and air-sea CO2 disequilibrium have strong compensating effect on the estimated Cant. The values of these parameters should be quantified to reduce the uncertainty of IG-TTD; this is increasingly important under a changing ocean climate.

Sustaining observations of the unsteady ocean circulation.

PubMed

Frajka-Williams, E

2014-09-28

Sustained observations of ocean properties reveal a global warming trend and rising sea levels. These changes have been documented by traditional ship-based measurements of ocean properties, whereas more recent Argo profiling floats and satellite records permit estimates of ocean changes on a near real-time basis. Through these and newer methods of observing the oceans, scientists are moving from quantifying the 'state of the ocean' to monitoring its variability, and distinguishing the physical processes bringing signals of change. In this paper, I give a brief overview of the UK contributions to the physical oceanographic observations, and the role they have played in the wider global observing systems. While temperature and salinity are the primary measurements of physical oceanography, new transbasin mooring arrays also resolve changes in ocean circulation on daily timescales. Emerging technologies permit routine observations at higher-than-ever spatial resolutions. Following this, I then give a personal perspective on the future of sustained observations. New measurement techniques promise exciting discoveries concerning the role of smaller scales and boundary processes in setting the large-scale ocean circulation and the ocean's role in climate. The challenges now facing the scientific community include sustaining critical observations in the case of funding system changes or shifts in government priorities. These long records will enable a determination of the role and response of the ocean to climate change. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Estimating Ocean Currents from Automatic Identification System Based Ship Drift Measurements

NASA Astrophysics Data System (ADS)

Jakub, Thomas D.

Ship drift is a technique that has been used over the last century and a half to estimate ocean currents. Several of the shortcomings of the ship drift technique include obtaining the data from multiple ships, the time delay in getting those ship positions to a data center for processing and the limited resolution based on the amount of time between position measurements. These shortcomings can be overcome through the use of the Automatic Identification System (AIS). AIS enables more precise ocean current estimates, the option of finer resolution and more timely estimates. In this work, a demonstration of the use of AIS to compute ocean currents is performed. A corresponding error and sensitivity analysis is performed to help identify under which conditions errors will be smaller. A case study in San Francisco Bay with constant AIS message updates was compared against high frequency radar and demonstrated ocean current magnitude residuals of 19 cm/s for ship tracks in a high signal to noise environment. These ship tracks were only minutes long compared to the normally 12 to 24 hour ship tracks. The Gulf of Mexico case study demonstrated the ability to estimate ocean currents over longer baselines and identified the dependency of the estimates on the accuracy of time measurements. Ultimately, AIS measurements when combined with ship drift can provide another method of estimating ocean currents, particularly when other measurements techniques are not available.

Significant wave heights from Sentinel-1 SAR: Validation and applications

NASA Astrophysics Data System (ADS)

Stopa, J. E.; Mouche, A.

2017-03-01

Two empirical algorithms are developed for wave mode images measured from the synthetic aperture radar aboard Sentinel-1 A. The first method, called CWAVE_S1A, is an extension of previous efforts developed for ERS2 and the second method, called Fnn, uses the azimuth cutoff among other parameters to estimate significant wave heights (Hs) and average wave periods without using a modulation transfer function. Neural networks are trained using colocated data generated from WAVEWATCH III and independently verified with data from altimeters and in situ buoys. We use neural networks to relate the nonlinear relationships between the input SAR image parameters and output geophysical wave parameters. CWAVE_S1A performs well and has reduced precision compared to Fnn with Hs root mean square errors within 0.5 and 0.6 m, respectively. The developed neural networks extend the SAR's ability to retrieve useful wave information under a large range of environmental conditions including extratropical and tropical cyclones in which Hs estimation is traditionally challenging.