47 citations as recorded by crossref.

1. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution L. Bessières et al.
2. Covariance of Optimal Parameters of an Arctic Sea Ice–Ocean Model H. Sumata et al.
3. Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO–PISCES simulator M. Popov et al.
4. Analysis of the hydrosedimentary circulation in the mouth of dominated wave environment using grain size analysis, wave/current modeling and image processing case of the principal Rivers in Zemmouri bay I. Yaiche Temam et al.
5. Generating atmospheric forcing perturbations for an ocean data assimilation ensemble I. Mirouze & A. Storto
6. Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data F. Garnier et al.
7. Assimilation of satellite swaths versus daily means of sea ice concentration in a regional coupled ocean–sea ice model M. Durán Moro et al.
8. An eddifying Stommel model: fast eddy effects in a two-box ocean W. Barham & I. Grooms
9. Ensemble hindcasting of wind and wave conditions with WRF and WAVEWATCH III® driven by ERA5 R. Osinski & H. Radtke
10. Oceanic Stochastic Parameterizations in a Seasonal Forecast System M. Andrejczuk et al.
11. A Gaussian-product stochastic Gent–McWilliams parameterization I. Grooms
12. An Investigation of Ocean Model Uncertainties Through Ensemble Forecast Experiments in the Southwest Atlantic Ocean L. Lima et al.
13. Imprint of chaotic ocean variability on transports in the southwestern Pacific at interannual timescales S. Cravatte et al.
14. Diagnosing, modeling, and testing a multiplicative stochastic Gent-McWilliams parameterization I. Grooms & W. Kleiber
15. Ensemble quantification of short-term predictability of the ocean dynamics at a kilometric-scale resolution: a Western Mediterranean test case S. Leroux et al.
16. Data assimilative twin-experiment in a high-resolution Bay of Biscay configuration: 4DEnOI based on stochastic modeling of the wind forcing V. Vervatis et al.
17. Internal variability of a 3-D ocean model B. Büchmann & J. Söderkvist
18. Chaotic oceanic excitation of low-frequency polar motion variability L. Börger et al.
19. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations S. Close et al.
20. Stochastic Subgrid-Scale Ocean Mixing: Impacts on Low-Frequency Variability S. Juricke et al.
21. Assessing the Impact of Different Ocean Analysis Schemes on Oceanic and Underwater Acoustic Predictions A. Storto et al.
22. Randomly correcting model errors in the ARPEGE-Climate v6.1 component of CNRM-CM: applications for seasonal forecasts L. Batté & M. Déqué
23. Non‐Local Eddy‐Mean Kinetic Energy Transfers in Submesoscale‐Permitting Ensemble Simulations Q. Jamet et al.
24. Enhanced regional ocean ensemble data assimilation through atmospheric coupling in the SKRIPS model R. Sun et al.
25. Accounting for model error in strong‐constraint 4D‐Var data assimilation K. Howes et al.
26. Regional ocean model uncertainties using stochastic parameterizations and a global atmospheric ensemble V. Vervatis et al.
27. Requirements for an Integrated in situ Atlantic Ocean Observing System From Coordinated Observing System Simulation Experiments F. Gasparin et al.
28. On the Chaotic Variability of Deep Convection in the Mediterranean Sea R. Waldman et al.
29. Uncertainty and scale interactions in ocean ensembles: From seasonal forecasts to multidecadal climate predictions L. Zanna et al.
30. Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction S. Penny et al.
31. Observing System Evaluation Based on Ocean Data Assimilation and Prediction Systems: On-Going Challenges and a Future Vision for Designing and Supporting Ocean Observational Networks Y. Fujii et al.
32. An Ensemble-Based Probabilistic Score Approach to Compare Observation Scenarios: An Application to Biogeochemical-Argo Deployments C. Germineaud et al.
33. Assessment of a regional physical–biogeochemical stochastic ocean model. Part 1: Ensemble generation V. Vervatis et al.
34. Improved teleconnection between Arctic sea ice and the North Atlantic Oscillation through stochastic process representation K. Strommen et al.
35. Impact of Atmospheric and Model Physics Perturbations on a High‐Resolution Ensemble Data Assimilation System of the Red Sea S. Sanikommu et al.
36. Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean Y. Santana-Falcón et al.
37. Global-scale random bottom pressure fluctuations from oceanic intrinsic variability M. Zhao et al.
38. Circumpolar Variations in the Chaotic Nature of Southern Ocean Eddy Dynamics A. Hogg et al.
39. Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling Y. Matsuzaki & T. Inoue
40. Intrinsic and Atmospherically Forced Variability of the AMOC: Insights from a Large-Ensemble Ocean Hindcast S. Leroux et al.
41. A multiscale ocean data assimilation approach combining spatial and spectral localisation A. Tissier et al.
42. Parameterizing the Impact of Unresolved Temperature Variability on the Large‐Scale Density Field: Part 1. Theory. Z. Stanley et al.
43. Characterisation of uncertainties in an ocean radiative transfer model for the Black Sea through ensemble simulations L. Macé et al.
44. Model uncertainties of a storm and their influence on microplastics and sediment transport in the Baltic Sea R. Osinski et al.
45. Stochastic representations of model uncertainties at ECMWF: state of the art and future vision M. Leutbecher et al.
46. Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation A. Storto et al.
47. Assessment of a regional physical–biogeochemical stochastic ocean model. Part 2: Empirical consistency V. Vervatis et al.