Assessment of a regional physical–biogeochemical stochastic ocean model. Part 1: Ensemble generation

Vervatis, Vassilios; Mey-Frémaux, Pierre de; Ayoub, Nadia; Karagiorgos, John; Ghantous, Malek; Kailas, Marios; Testut, Charles-Emmanuel; Sofianos, Sarantis

doi:10.1016/j.ocemod.2021.101781

Cited by 4 publications

(3 citation statements)

References 74 publications

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“…Figure 4 (b) in Vervatis et al. (2021) shows that the ensemble spread caused by perturbation of the air temperature was large near the coastline (coastal area). A possible reason is that the perturbation of air temperature becomes relatively significant in the shallow sea area because the amount of water mass in the shallow sea area with respect to the heat flux of the atmosphere and seawater is smaller than that in the deep sea area.…”

Section: Discussionmentioning

confidence: 99%

“…Mikawa Bay is shallower than the west side of Ise Bay (Figure 2); relatively shallow water is considered to be more susceptible to wind accuracy, and results show that this is partly attributed to wind effect. Vervatis et al (2021) noted that in the open ocean, perturbing the wind speed had the greatest effect on the ensemble spread of water temperature during data assimilation by EnKF, and that perturbation of other atmospheric forcing conditions (air temperature and sea level pressure) was less dominant. They also reported that wind uncertainty had a significant impact on upper ocean uncertainty for both the geostrophic and Ekman components defined by Sverdrup dynamics.…”

Section: Effect Of Perturbations To Boundary Conditionsmentioning

confidence: 99%

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Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Matsuzaki

Inoue

2022

JGR Oceans

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Regional data assimilation is conducted for a coastal estuary using the ensemble Kalman filter, real observation data from Ise Bay, Japan, and a simulation model called the Ise Bay Simulator. The applicability and robustness of the method are then examined. We also analyze the relationship between the boundary conditions, which add perturbations and the data assimilation results of water temperature and salinity. A method of creating an ensemble by perturbing three boundary conditions (atmospheric forcing, lateral boundary conditions [open boundary conditions], and river discharge forcing) is then proposed. In situ water temperature and salinity profiles observed at fixed points are assimilated daily. The proposed assimilation method provides stable data assimilation without unnatural values for water temperature and salinity throughout the year. Further, applying a perturbation to the three boundary conditions does not lead to filter divergence, thus indicating good applicability and robustness, that is, applying a perturbation to the three boundary conditions does not degenerate the ensemble spread. According to a sensitivity experiment, perturbing the atmospheric boundary conditions of both air temperature and wind speed increases the ensemble spread of water temperature, especially near the surface layer. Wind speed has the greatest influence on the magnitude of the salinity ensemble spread, and its dominance depends on location. Perturbation of lateral boundary conditions increases the ensemble spread of water temperature and salinity at all water depths near the bay mouth, and the observations are effectively assimilated. Perturbation of river discharge forcing successfully assimilates water temperature and salinity near the estuary.

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Section: Discussionmentioning

confidence: 99%

Section: Effect Of Perturbations To Boundary Conditionsmentioning

confidence: 99%

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Matsuzaki

Inoue

2022

JGR Oceans

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“…Brodeau et al, 2016). Alternatively, Vervatis et al (2021) have shown that parameters such as air-sea transfer coefficients can be stochastically modulated in the context of an ensemble physical-biogeochemical analysis and forecast system.…”

Section: Introductionmentioning

confidence: 99%

Stochastic schemes for the perturbation of the atmospheric boundary conditions in ocean general circulation models

Storto

Yang

2023

Front. Mar. Sci.

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Advancing the representation of uncertainties in ocean general circulation numerical models is required for several applications, ranging from data assimilation to climate monitoring and extended-range prediction systems. The atmospheric forcing represents one of the main uncertainty sources in numerical ocean models. Here, we formulate and revise different approaches to perturb the air-sea fluxes used within the atmospheric boundary conditions. In particular, perturbation of the fluxes is performed either through i) stochastic modulation of the air-sea transfer coefficients; ii) stochastic modulation of the air-sea flux tendencies; iii) coarse-graining of stochastic sub-grid computation of the fluxes; or iv) multiple bulk formulas. The schemes are implemented and tested in the NEMO4 ocean model, implemented at an eddy-permitting resolution on a domain covering the North Atlantic and Arctic oceans and the Mediterranean Sea. A series of 22-year 4-member ensemble experiments with different stochastic schemes are performed and analyzed for the period 2000-2021, and results are compared in terms of the ensemble mean and, when applicable, ensemble spread of the principal oceanic diagnostics. Results indicate that the schemes, in general, can significantly improve some verification skill scores (e.g. against drifter current speed, SST analyses, and hydrographic profiles) and, in some cases, enhance the mesoscale activity and weaken the large-scale circulation. The response, however, is different depending on the specific scheme, whose choice thus depends on the target application, as detailed in the paper. These findings foster the adoption of these schemes in both extended-range operational ocean forecasts and coupled long-range climate prediction systems, where the boundary conditions perturbations may contribute to performance increases.

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Assessing impacts of observations on ocean circulation models with examples from coastal, shelf, and marginal seas

Edwards,

De Mey-Frémaux,

Barceló-Llull

et al. 2024

Front. Mar. Sci.

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Ocean observing systems in coastal, shelf and marginal seas collect diverse oceanographic information supporting a wide range of socioeconomic needs, but observations are necessarily sparse in space and/or time due to practical limitations. Ocean analysis and forecast systems capitalize on such observations, producing data-constrained, four-dimensional oceanographic fields. Here we review efforts to quantify the impact of ocean observations, observing platforms, and networks of platforms on model products of the physical ocean state in coastal regions. Quantitative assessment must consider a variety of issues including observation operators that sample models, error of representativeness, and correlated uncertainty in observations. Observing System Experiments, Observing System Simulation Experiments, representer functions and array modes, observation impacts, and algorithms based on artificial intelligence all offer methods to evaluate data-based model performance improvements according to metrics that characterize oceanographic features of local interest. Applications from globally distributed coastal ocean modeling systems document broad adoption of quantitative methods, generally meaningful reductions in model-data discrepancies from observation assimilation, and support for assimilation of complementary data sets, including subsurface in situ observation platforms, across diverse coastal environments.

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Assessment of a regional physical–biogeochemical stochastic ocean model. Part 1: Ensemble generation

Cited by 4 publications

References 74 publications

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Stochastic schemes for the perturbation of the atmospheric boundary conditions in ocean general circulation models

Assessing impacts of observations on ocean circulation models with examples from coastal, shelf, and marginal seas

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