Going electric: Incorporating marine electromagnetism into ocean assimilation models
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N. R. Schnepf↗
SEARCH · Engineering Papers
Results for “ocean model”
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Sea spray effects on typhoon prediction in the Yellow and East China Seas: case studies using a coupled atmosphere-ocean-wave model for Lingling (2019) and Maysak (2020)
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Sinil Yang↗
Optimization of a Parallel Ocean General Circulation Model
Global climate modeling is one of the grand chalenges of computational science, and ocean modeling plays an important role in both understanding the current climatic conditions and predicting the future climate change.
Optimization Ocean Modeling Parallel Computations↗
JIGSAW-GEO (1.0): Locally Orthogonal Staggered Unstructured Grid Generation for General Circulation Modelling on the Sphere
An algorithm for the generation of non-uniform, locally orthogonal staggered unstructured spheroidal grids is described. This technique is designed to generate very high-quality staggered VoronoiDelaunay meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric simulation, ocean-modelling and numerical weather prediction. Using a recently developed Frontal-Delaunay refinement technique, a method for the construction of high-quality unstructured spheroidal Delaunay triangulations is introduced. A locally orthogonal polygonal grid, derived from the associated Voronoi diagram, is computed as the staggered dual. It is shown that use of the Frontal-Delaunay refinement technique allows for the generation of very high-quality unstructured triangulations, satisfying a priori bounds on element size and shape. Grid quality is further improved through the application of hill-climbing-type optimisation techniques. Overall, the algorithm is shown to produce grids with very high element quality and smooth grading characteristics, while imposing relatively low computational expense. A selection of uniform and non-uniform spheroidal grids appropriate for high-resolution, multi-scale general circulation modelling are presented. These grids are shown to satisfy the geometric constraints associated with contemporary unstructured C-grid-type finite-volume models, including the Model for Prediction Across Scales (MPAS-O). The use of user-defined mesh-spacing functions to generate smoothly graded, non-uniform grids for multi-resolution-type studies is discussed in detail.
geophysical fluid dynamics↗
In Situ Analysis of Orthopyroxene in Diogenites Using Laser Ablation ICP-MS
Howardites, eucrites and diogenites (HED) form a suit of igneous achondrite meteorites that are thought to have formed on a single asteroidal body. While there have been many different models proposed for the formation of the HED parent asteroid they can be generalized into two end member models. One is the magma ocean model (e.g. [1]) in which the entire HED parent body was continuously fractionated from a planet wide magma ocean with diogenites representing the lower crust and eucrites being upper crustal rocks. The second model hypothesizes that diogenites and eucrites were formed as a series of intrusions and/or extrusions of partial melts of a primitive proto-Vesta [2]. We use in situ trace element analysis together with major and minor element analysis to try and distinguish between these different hypotheses for the evolution of the HED parent body.
Elk, Mattias↗
A GPU‐Based Ocean Dynamical Core for Routine Mesoscale‐Resolving Climate Simulations
Abstract We describe an ocean hydrostatic dynamical core implemented in Oceananigans optimized for Graphical Processing Unit (GPU) architectures. On 64 A100 GPUs, equivalent to 16 computational nodes in current state‐of‐the‐art supercomputers, our dynamical core can simulate a decade of near‐global ocean dynamics per wall‐clock day at an 8‐km horizontal resolution; a resolution adequate to resolve the ocean's mesoscale eddy field. Such efficiency, achieved with relatively modest hardware resources, suggests that climate simulations on GPUs can incorporate fully eddy‐resolving ocean models. This removes a major source of systematic bias in current IPCC coupled model projections, the parameterization of ocean eddies, and represents a major advance in climate modeling. We discuss the computational strategies, focusing on GPU‐specific optimization and numerical implementation details that enable such high performance.
Silvestri, Simone [Massachusetts Institute of Tech↗
High-Resolution Modeling of the Gulf of Mexico using E3SM
Coastal ocean modeling is a high priority in the DOE‘s Energy Exascale Earth System Model (E3SM). The goal is to accurately predict the risk of damage to coastal resources and infrastructure due to a changing climate in the coming decades. North American coastal communities are areas of particular interest, as this fits under the topic of US national security and planning assessments in a changing climate. LANL Institutional Computing time for the Tier 1 allocation ”Coastal Ocean and Sea Ice Modeling” have been used for development and testing of numerical methods needed for E3SM coastal applications.
54 ENVIRONMENTAL SCIENCES↗
ENSO Mechanisms
This current leading theory of the El Nino-Southern Oscillation (ENSO) phenomenon involves reflection of equatorial waves on the western ocean boundary to shift the ENSO phase from El Nino to La Nina and vice versa. However, recent satellite altimetry and In situ observations indicate that this theory has several flaws. These include imperfect equatorial wave reflection on the western ocean boundary, a maxima of the simulated coupled wind-sea surface temperature (SST) interaction located too far into the eastern equatorial Pacific, and an excessive role of thermocline displacement on SST in this region. We show that the central equatorial Pacific SST is fundamental in driving the EIVSO ocean-atmosphere coupled system, through the east-west displacement of the eastern edge of the warm pool, perfectly related with ENSO. Within the equatorial wave-guide, the dominance of surface zonal advection in these displacements is demonstrated with four different satellite and in situ data sets and three ocean models. This demonstration is supported by the evidence of a convergence of water masses into the eastern edge of the warm pool, resulting in a well-defined salinity front. All these results lead us to propose a notable modification of the leading delayed-action oscillator theory for the oscillatory nature of ENSO. Simulations with a linearized coupled ocean-atmosphere model result in 3-6 year ENSO-like oscillations, with many Of the variable model parameters found very close to their observed values. This simple model suggests that ocean processes ignored or underestimated in the delayed action oscillator theory, such as zonal current convergence, zonal advection of sea surface temperature and equatorial wave reflection from the eastern-ocean boundary, are fundamental to the development of ENSO, in particular to its manifestations in the central equatorial Pacific.
Picaut, Joel↗
Rain-Induced Stratification of the Equatorial Indian Ocean and Its Potential Feedback to the Atmosphere
Surface freshening through precipitation can act to stably stratify the upper ocean, forming a rain layer (RL). RLs inhibit subsurface vertical mixing, isolating deeper ocean layers from the atmosphere. This process has been studied using observations and idealized simulations. The present ocean modeling study builds upon this body of work by incorporating spatially resolved and realistic atmospheric forcing. Fine-scale observations of the upper ocean collected during the Dynamics of the Madden-Julian Oscillation field campaign are used to verify the General Ocean Turbulence Model (GOTM). Spatiotemporal characteristics of equatorial Indian Ocean RLs are then investigated by forcing a 2D array of GOTM columns with realistic and well-resolved output from an existing regional atmospheric simulation. RL influence on the ocean-atmosphere system is evaluated through analysis of RL-induced modification to surface fluxes and sea surface temperature (SST). This analysis demonstrates that RLs cool the ocean surface on time scales longer than the associated precipitation event. A second simulation with identical atmospheric forcing to that in the first, but with rainfall set to zero, is performed to investigate the role of rain temperature and salinity stratification in maintaining cold SST anomalies within RLs. Approximately one third, or 0.1°C, of the SST reduction within RLs can be attributed to rain effects, while the remainder is attributed to changes in atmospheric temperature and humidity. The prolonged RL-induced SST anomalies enhance SST gradients that have been shown to favor the initiation of atmospheric convection. These findings encourage continued research of RL feedbacks to the atmosphere.
54 ENVIRONMENTAL SCIENCES↗
Modeling the Gulf Stream System: How Far from Reality?
Analyses of a primitive equation ocean model simulation of the Atlantic Ocean circulation at 1/6 deg horizontal resolution are presented with a focus on the Gulf Stream region. Among many successful features of this simulation, this letter describes the Gulf Stream separation from the coast of North America near Cape Hatteras, meandering of the Gulf Stream between Cape Hatteras and the Grand Banks, and the vertical structure of temperature and velocity associated with the Gulf Stream. These results demonstrate significant improvement in modeling the Gulf Stream system using basin- to global scale ocean general circulation models. Possible reasons responsible for the realistic Gulf Stream simulation are discussed, contrasting the major differences between the present model configuration and those of previous eddy resolving studies.
Choa, Yi↗
The roles of vertical mixing, solar radiation, and wind stress in a model simulation of the sea surface temperature seasonal cycle in the tropical Pacfic Ocean
The climatological seasonal cycle of sea surface temperature (SST) in the tropical Pacific is simulated using a newly developed upper ocean model. The roles of vertical mixing, solar radiation, and wind stress are investigated in a hierarchy of numerical experiments with various combinations of vertical mixing algorithms and surface-forcing products. It is found that the large SST annual cycle in the eastern equatorial Pacific is, to a large extent, controlled by the annually varying mixed layer depth which, in turn, is mainly determined by the competing effects of solar radiation and wind forcing. With the application of our hybrid vertical mixing scheme the model-simulated SST annual cycle is much improved in both amplitude and phase as compared to the case of a constant mixed layer depth. Beside the strong effects on vertical mixing, solar radiation is the primary heating term in the surface layer heat budget, and wind forcing influences SST by driving oceanic advective processes that redistribute heat in the upper ocean. For example, the SST seasonal cycle in the western Pacific basically follows the semiannual variation of solar heating, and the cycle in the central equatorial region is significantly affected by the zonal advective heat flux associated with the seasonally reversing South Equatorial Current. It has been shown in our experiments that the amount of heat flux modification needed to eliminate the annual mean SST errors in the model is, on average, no larger than the annual mean uncertainties among the various surface flux products used in this study. Whereas a bias correction is needed to account for remaining uncertainties in the annual mean heat flux, this study demonstrates that with proper treatment of mixed layer physics and realistic forcing functions the seasonal variability of SST is capable of being simulated successfully in response to external forcing without relying on a relaxation or damping formulation for the dominant surface heat flux contributions.
Chen, Dake↗
Detection of Rossby Waves in Multi-Parameters in Multi-Mission Satellite Observations and HYCOM Simulations in the Indian Ocean
Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12-deg global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified.
SSH (SEA SURFACE HEIGHT)↗
Core Formation in the Earth: Constraints from Ni and Co
Due to their metal-loving nature, Ni and Co were strongly partitioned into the metallic core and were left depleted in the silicate mantle during core formation in the Earth. Based on experimental liquid metal- liquid silicate partition coefficients (D), studies have suggested that core formation in an early magma Ocean can explain the observed mantle depletions of Ni and Co [l-51. However, the conditions proposed by the magma ocean models have ranged from pressures of 24 to 59 GPa and temperatures of 2200 to < 4000 K. Furthermore, the proposed magma Ocean oxygen fugacities have differed by nearly two orders of magnitude.Chabot and Agee noted that the different models predicted contradictory behaviors for D(Ni) and D(Co) as a function of temperature. With the hope of resolving the discrepancies between the magma ocean models, we conducted a systematic experimental study to constrain the effects of temperature on D(Ni) and D(Co).
Chabot, N. L.↗
A model El Nino-Southern Oscillation
A coupled atmosphere-ocean model is developed and used to study the ENSO (El Nino/Southern Oscillation) phenomenon. With no anomalous external forcing, the coupled model reproduces certain key features of the observed phenomenon, including the recurrence of warm events at irregular intervals with a preference for three to four years. It is shown that the mean sea surface temperature, wind and ocean current fields determine the characteristic spatial structure of ENSO anomalies. The tendency for phase-locking of anomalies is explained in terms of a variation in coupling strength associated with the annual cycle in the mean fields. Sensitivity studies reveal that both the amplitude and the time scale of the oscillation are sensitive to several parameters that affect the strength of the atmosphere-ocean coupling. Stronger coupling implies larger oscillations with a longer timescale. A critical element of the model oscillation is the variability in the equatorial heat content of the upper ocean. Equatorial heat content increases prior to warm events and decreases sharply during the events. A theory for this variability and the associated transitions between non-El Nino and El Nino states is presented. Implications of the model results for the prediction of El Nino events are discussed.
Zebiak, Stephen E.↗
Applications of Data Assimilation to Analysis of the Ocean on Large Scales
It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height anomalies. Because of its potential for large scale synoptic coverage of the deep ocean, acoustic travel time data should be a natural complement to satellite altimetry. Satellite data give us vertical integrals associated with thermodynamic and dynamic processes.
Miller, Robert N.↗
Machine Learning Eliminates Reanalysis Warm Bias and Reveals Weaker Winter Surface Cooling Over Arctic Sea Ice
The surface energy budget governs Arctic sea-ice growth/melt, yet observations are sparse, and reanalysis data sets suffer from systematic biases. Here, we train a neural network with observational data to bias-correct hourly ERA5 fluxes over Arctic ice-covered regions (≥70°N; sea-ice concentration >80%) for 1994–2024. Training data cover two full seasonal cycles and different sea-ice regimes. The neural network reduces RMSE for net shortwave radiation by ∼40%, downward longwave radiation by ∼16% and the total surface energy budget by ∼55%, eliminating the wintertime warm bias of ∼4 K in ERA5. Wintertime surface cooling is reduced by ∼50%, yielding thermodynamic ice-growth estimates of ∼80–120 cm, consistent with SMOS–CryoSat satellite thickness increases and in contrast to the 150–200 cm growth implied by ERA5. Our bias-corrected data capture the observed clear/cloudy states of the winter boundary layer and can be used to study Arctic climatology, evaluate climate models and drive sea-ice-ocean models.
Hossain, Akil [Alfred Wegener Institute for Polar ↗
Combined MODIS/AMSR-E SST Composites for Regional Weather Applications
Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.
Jedlovec, Gary↗
An Assessment of the Predictability of Northern Winter Seasonal Means with the NSIPP 1 AGCM
This atlas assesses the predictability of January-February-March (JFM) means using version 1 of the NASA Seasonal-to-Interannual Prediction Project Atmospheric General Circulation Model (the NSIPP 1 AGCM). The AGCM is part of the NSIPP coupled atmosphere-land-ocean model. For these results, the atmosphere was run uncoupled from the ocean, but coupled with an interactive land model. The results are based on 20 ensembles of nine JFM hindcasts for the period 1980-1999, with sea surface temperature (SST) and sea ice specified from observations. The model integrations were started from initial atmospheric conditions (taken from NCEP/NCAR reanalyses) centered on December 15. The analysis focuses on 200 mb height, precipitation, surface temperature, and sea-level pressure. The results address issues of both predictability and forecast skill. Various signal-to-noise measures are computed to demonstrate the potential for skillful prediction on seasonal time scales under the assumption of a perfect model and perfectly known oceanic boundary forcings. The results show that the model produces a realistic ENSO response in both the tropics and extratropics.
Suarez, Max J.↗