259 citations as recorded by crossref.

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2. Probabilistic Forecasts of Sea Ice Trajectories in the Arctic: Impact of Uncertainties in Surface Wind and Ice Cohesion S. Cheng et al. 10.3390/oceans1040022
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7. Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean–sea ice modelling system S. Fritzner et al. 10.5194/tc-13-491-2019
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9. Wave–ice interactions in the marginal ice zone. Part 2: Numerical implementation and sensitivity studies along 1D transects of the ocean surface T. Williams et al. 10.1016/j.ocemod.2013.05.011
10. Comparison between a multi-variate nudging method and the ensemble Kalman filter for sea-ice data assimilation S. FRITZNER et al. 10.1017/jog.2018.33
11. Assimilation of Sea Surface Temperature in a Global Hybrid Coordinate Ocean Model Y. Chen et al. 10.1007/s00376-018-7284-6
12. Three-Dimensional Thermohaline Reconstruction Driven by Satellite Sea Surface Data Based on Sea Ice Seasonal Variation in the Arctic Ocean X. Wu et al. 10.3390/rs16214072
13. Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system J. Xie et al. 10.5194/tc-10-2745-2016
14. Impact of rheology on probabilistic forecasts of sea ice trajectories: application for search and rescue operations in the Arctic M. Rabatel et al. 10.5194/tc-12-935-2018
15. Modelling of the Svalbard fjord Hornsund J. Jakacki et al. 10.1016/j.oceano.2017.04.004
16. Reanalyzing temperature and salinity on decadal time scales using the ensemble optimal interpolation data assimilation method and a 3D ocean circulation model of the Baltic Sea Y. Liu et al. 10.1002/jgrc.20384
17. Estimation of Arctic land-fast ice cover based on dual-polarized Sentinel-1 SAR imagery J. Karvonen 10.5194/tc-12-2595-2018
18. Copernicus Marine Service Ocean State Report K. von Schuckmann et al. 10.1080/1755876X.2018.1489208
19. Empirical sea ice thickness retrieval during the freeze-up period from SMOS high incident angle observations M. Huntemann et al. 10.5194/tc-8-439-2014
20. Assessing the impact of observations on ocean forecasts and reanalyses: Part 1, Global studies P. Oke et al. 10.1080/1755876X.2015.1022067
21. On the Efficiency of Covariance Localisation of the Ensemble Kalman Filter Using Augmented Ensembles A. Farchi & M. Bocquet 10.3389/fams.2019.00003
22. A Quantile-Conserving Ensemble Filter Based on Kernel-Density Estimation I. Grooms & C. Riedel 10.3390/rs16132377
23. Exploring non-Gaussian sea ice characteristics via observing system simulation experiments C. Riedel & J. Anderson 10.5194/tc-18-2875-2024
24. SIMUG – finite element model of sea ice dynamics on triangular grid in local Cartesian basis S. Petrov & N. Iakovlev 10.1515/rnam-2023-0012
25. Modeling Larval Transport and Settlement of Pink Shrimp in South Florida: Dynamics of Behavior and Tides M. Criales et al. 10.1080/19425120.2014.1001541
26. New insights into SMOS sea surface salinity retrievals in the Arctic Ocean A. Supply et al. 10.1016/j.rse.2020.112027
27. Impact of data assimilation on vertical velocities in an eddy resolving ocean model G. Pilo et al. 10.1016/j.ocemod.2018.09.003
28. Intercomparison of the Arctic sea ice cover in global ocean–sea ice reanalyses from the ORA-IP project M. Chevallier et al. 10.1007/s00382-016-2985-y
29. Evaluating satellite retrieved fractional snow-covered area at a high-Arctic site using terrestrial photography K. Aalstad et al. 10.1016/j.rse.2019.111618
30. A New Brittle Rheology and Numerical Framework for Large‐Scale Sea‐Ice Models E. Ólason et al. 10.1029/2021MS002685
31. Pathfinding and optimization for vessels in ice: A literature review T. Tran et al. 10.1016/j.coldregions.2023.103876
32. Experiences in multiyear combined state–parameter estimation with an ecosystem model of the North Atlantic and Arctic Oceans using the Ensemble Kalman Filter E. Simon et al. 10.1016/j.jmarsys.2015.07.004
33. From Observation to Information and Users: The Copernicus Marine Service Perspective P. Le Traon et al. 10.3389/fmars.2019.00234
34. Impact of Atmospheric and Model Physics Perturbations on a High‐Resolution Ensemble Data Assimilation System of the Red Sea S. Sanikommu et al. 10.1029/2019JC015611
35. Intercomparison of initialization methods for seasonal-to-decadal climate predictions with the NorCPM L. Garcia-Oliva et al. 10.1007/s00382-024-07170-w
36. Assimilation of semi‐qualitative observations with a stochastic ensemble Kalman filter A. Shah et al. 10.1002/qj.3381
37. Assessment of a regional physical–biogeochemical stochastic ocean model. Part 1: Ensemble generation V. Vervatis et al. 10.1016/j.ocemod.2021.101781
38. Towards reliable Arctic sea ice prediction using multivariate data assimilation J. Liu et al. 10.1016/j.scib.2018.11.018
39. Regional-scale phytoplankton dynamics and their association with glacier meltwater runoff in Svalbard T. Dunse et al. 10.5194/bg-19-271-2022
40. The role of atmospheric uncertainty in Arctic summer sea ice data assimilation and prediction Q. Yang et al. 10.1002/qj.2523
41. Toward Improved Estimation of the Dynamic Topography and Ocean Circulation in the High Latitude and Arctic Ocean: The Importance of GOCE J. Johannessen et al. 10.1007/s10712-013-9270-y
42. Toward Optimization of Rheology in Sea Ice Models through Data Assimilation J. Stroh et al. 10.1175/JTECH-D-18-0239.1
43. State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems S. Vetra-Carvalho et al. 10.1080/16000870.2018.1445364
44. Status and future of data assimilation in operational oceanography M. Martin et al. 10.1080/1755876X.2015.1022055
45. Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction S. Penny et al. 10.3389/fmars.2019.00391
46. On the statistical properties of sea-ice lead fraction and heat fluxes in the Arctic E. Ólason et al. 10.5194/tc-15-1053-2021
47. Assimilation of remote sensing observations into a sediment transport model of China’s largest freshwater lake: spatial and temporal effects P. Zhang et al. 10.1007/s11356-015-4958-9
48. Super-resolution data assimilation S. Barthélémy et al. 10.1007/s10236-022-01523-x
49. High-Frequency Variability in the Circulation and Hydrography of the Denmark Strait Overflow from a High-Resolution Numerical Model M. Almansi et al. 10.1175/JPO-D-17-0129.1
50. Probabilistic models for harmful algae: application to the Norwegian coast E. Silva et al. 10.1017/eds.2024.11
51. Polar Ocean Observations: A Critical Gap in the Observing System and Its Effect on Environmental Predictions From Hours to a Season G. Smith et al. 10.3389/fmars.2019.00429
52. Bounded and categorized: targeting data assimilation for sea ice fractional coverage and nonnegative quantities in a single-column multi-category sea ice model M. Wieringa et al. 10.5194/tc-18-5365-2024
53. Prediction of Sea Ice Motion With Convolutional Long Short-Term Memory Networks Z. Petrou & Y. Tian 10.1109/TGRS.2019.2909057
54. Covariance Matrix Estimation for Ensemble-Based Kalman Filters with Multiple Ensembles S. Gratton et al. 10.1007/s11004-023-10063-z
55. An Evaluation of the Performance of Sea Ice Thickness Forecasts to Support Arctic Marine Transport T. Bilge et al. 10.3390/jmse10020265
56. Copernicus Ocean State Report, issue 6 10.1080/1755876X.2022.2095169
57. Relating model bias and prediction skill in the equatorial Atlantic F. Counillon et al. 10.1007/s00382-020-05605-8
58. Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories P. Rampal et al. 10.5194/tc-10-1513-2016
59. Assimilating Copernicus SST Data into a Pan-Arctic Ice–Ocean Coupled Model with a Local SEIK Filter X. Liang et al. 10.1175/JTECH-D-16-0166.1
60. Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System X. Liang et al. 10.1029/2019JC015073
61. 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. 10.3389/fmars.2019.00417
62. A stochastic operational forecasting system of the Black Sea: Technique and validation L. Vandenbulcke & A. Barth 10.1016/j.ocemod.2015.07.010
63. Risk Assessment of Polar Drillship Operations Based on Bayesian Networks Q. Wang et al. 10.3390/jmse12101873
64. Comparison of EnOI and EnKF regional ocean reanalysis systems P. Sakov & P. Sandery 10.1016/j.ocemod.2015.02.003
65. Enhanced Adaptive Inflation Algorithm for Ensemble Filters M. El Gharamti 10.1175/MWR-D-17-0187.1
66. Seismic exploration noise reduction in the Marginal Ice Zone D. Tollefsen & H. Sagen 10.1121/1.4885547
67. Quantitative assessment of two oil-in-ice surface drift algorithms V. de Aguiar et al. 10.1016/j.marpolbul.2022.113393
68. Virtual radar ice buoys – a method for measuring fine-scale sea ice drift J. Karvonen 10.5194/tc-10-29-2016
69. Measuring currents, ice drift, and waves from space: the Sea surface KInematics Multiscale monitoring (SKIM) concept F. Ardhuin et al. 10.5194/os-14-337-2018
70. Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models F. Richter et al. 10.5194/tc-12-921-2018
71. Time series of temperature in Fram Strait determined from the 2008–2009 DAMOCLES acoustic tomography measurements and an ocean model H. Sagen et al. 10.1002/2015JC011591
72. Lagrangian transport across the upper Arctic waters in the Canada Basin F. Balibrea‐Iniesta et al. 10.1002/qj.3404
73. Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas E. Silva et al. 10.3389/fmars.2021.746327
74. Ensemble quantification of short-term predictability of the ocean dynamics at a kilometric-scale resolution: a Western Mediterranean test case S. Leroux et al. 10.5194/os-18-1619-2022
75. Synoptic-scale analysis of mechanisms driving surface chlorophyll dynamics in the North Atlantic A. Ferreira et al. 10.5194/bg-12-3641-2015
76. Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013 J. Xie et al. 10.5194/os-13-123-2017
77. Empirical error functions for monthly mean Arctic sea‐ice drift H. Sumata et al. 10.1002/2015JC011151
78. Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System L. Mu et al. 10.1029/2022MS003176
79. Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation S. Metref et al. 10.3390/rs11111336
80. Estimating Winter Arctic Sea Ice Motion Based on Random Forest Models L. Zhang et al. 10.3390/rs16030581
81. Atlantic-Origin Overflow Water in the East Greenland Current L. Håvik et al. 10.1175/JPO-D-18-0216.1
82. Copernicus Marine Service Ocean State Report, Issue 5 K. von Schuckmann et al. 10.1080/1755876X.2021.1946240
83. CICE-LETKF Ensemble Analysis System with Application to Arctic Sea Ice Initialization X. Liu et al. 10.3390/jmse9090920
84. On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses L. Ponsoni et al. 10.5194/tc-13-521-2019
85. Artificial Neural Network for the Short-Term Prediction of Arctic Sea Ice Concentration M. Choi et al. 10.3390/rs11091071
86. Assessing net primary production in the northwestern Barents Sea using in situ, remote sensing and modelling approaches L. Castro de la Guardia et al. 10.1016/j.pocean.2023.103160
87. Oceanic ensemble forecasting in the Gulf of Mexico: An application to the case of the Deep Water Horizon oil spill V. Khade et al. 10.1016/j.ocemod.2017.04.004
88. Hierarchical Information-Sharing Convolutional Neural Network for the Prediction of Arctic Sea Ice Concentration and Velocity Y. Koo & M. Rahnemoonfar 10.1109/TGRS.2024.3501094
89. Arctic sea ice in the global eddy-permitting ocean reanalysis ORAP5 S. Tietsche et al. 10.1007/s00382-015-2673-3
90. Hybrid covariance super-resolution data assimilation S. Barthélémy et al. 10.1007/s10236-024-01643-6
91. Polar low variability and future projections for the Nordic and Barents Seas O. Landgren et al. 10.1002/qj.3608
92. Towards improving short-term sea ice predictability using deformation observations A. Korosov et al. 10.5194/tc-17-4223-2023
93. Sea-ice information and forecast needs for industry maritime stakeholders P. Wagner et al. 10.1080/1088937X.2020.1766592
94. A non-Gaussian analysis scheme using rank histograms for ensemble data assimilation S. Metref et al. 10.5194/npg-21-869-2014
95. On the consistency of the local ensemble square root Kalman filter perturbation update M. Bocquet & A. Farchi 10.1080/16000870.2019.1613142
96. An OSSE evaluation of the GNSS-R altimetry data for the GEROS-ISS mission as a complement to the existing observational networks J. Xie et al. 10.1016/j.rse.2018.02.053
97. Sea ice forecast verification in the Canadian Global Ice Ocean Prediction System G. Smith et al. 10.1002/qj.2555
98. Impact of Ocean and Sea Ice Initialisation On Seasonal Prediction Skill in the Arctic M. Kimmritz et al. 10.1029/2019MS001825
99. Atmospheric forcing of rapid marine-terminating glacier retreat in the Canadian Arctic Archipelago A. Cook et al. 10.1126/sciadv.aau8507
100. Assessment of High‐Resolution Dynamical and Machine Learning Models for Prediction of Sea Ice Concentration in a Regional Application S. Fritzner et al. 10.1029/2020JC016277
101. Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems G. Sutherland et al. 10.5194/tc-16-2103-2022
102. The Impact of Summer Arctic Cyclones on Chlorophyll-a Concentration and Sea Surface Temperature in the Kara Sea H. Li et al. 10.1109/JSTARS.2019.2910206
103. Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology Y. Chen et al. 10.5194/tc-18-2381-2024
104. neXtSIM: a new Lagrangian sea ice model P. Rampal et al. 10.5194/tc-10-1055-2016
105. An adaptive quality control procedure for data assimilation P. Sakov & P. Sandery 10.1080/16000870.2017.1318031
106. The Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysis G. Smith et al. 10.5194/gmd-14-1445-2021
107. Projected 21st-century changes to Arctic marine access S. Stephenson et al. 10.1007/s10584-012-0685-0
108. On the Choice of an Optimal Localization Radius in Ensemble Kalman Filter Methods P. Kirchgessner et al. 10.1175/MWR-D-13-00246.1
109. A comparison of Langmuir turbulence parameterizations and key wave effects in a numerical model of the North Atlantic and Arctic Oceans A. Ali et al. 10.1016/j.ocemod.2019.02.005
110. A comparison of an operational wave–ice model product and drifting wave buoy observation in the central Arctic Ocean: investigating the effect of sea-ice forcing in thin ice cover T. Nose et al. 10.33265/polar.v42.8874
111. In-situ observations of gelatinous zooplankton aggregations in inshore and offshore Arctic waters D. Pantiukhin et al. 10.1007/s00300-024-03306-0
112. ARGO data assimilation into the ocean dynamics model with high spatial resolution using Ensemble Optimal Interpolation (EnOI) M. Kaurkin et al. 10.1134/S0001437016060059
113. Medium range sea ice prediction in support of Japanese research vessel MIRAI’s expedition cruise in 2018 L. De Silva et al. 10.1080/1088937X.2019.1707317
114. PolarGAN: Creating realistic Arctic sea ice concentration images with user-defined geometric preferences M. Kim et al. 10.1016/j.engappai.2023.106920
115. Economic Feasibility and Possibility of Shipping via Northern Sea Route N. Otsuka 10.5988/jime.53.694
116. Internal variability of a 3-D ocean model B. Büchmann & J. Söderkvist 10.3402/tellusa.v68.30417
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118. Evaluation of Oil Spill Modeling in Ice Against In Situ Drifter Data from the Beaufort Sea D. French-McCay et al. 10.7901/2169-3358-2017.1.1523
119. Parallel implementation of a Lagrangian-based model on an adaptive mesh in C++: Application to sea-ice A. Samaké et al. 10.1016/j.jcp.2017.08.055
120. On the retrieval of sea-ice thickness using SMOS polarization differences M. GUPTA et al. 10.1017/jog.2019.26
121. Arctic shipping trends during hazardous weather and sea-ice conditions and the Polar Code’s effectiveness M. Müller et al. 10.1038/s44183-023-00021-x
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123. Lagrangian Perspective on the Origins of Denmark Strait Overflow A. Saberi et al. 10.1175/JPO-D-19-0210.1
124. Characterizing vertical upper ocean temperature structures in the European Arctic through unsupervised machine learning E. Thomas & M. Müller 10.1016/j.ocemod.2022.102092
125. Tuning and assessment of the HYCOM-NORWECOM V2.1 biogeochemical modeling system for the North Atlantic and Arctic oceans A. Samuelsen et al. 10.5194/gmd-8-2187-2015
126. Bridging observations, theory and numerical simulation of the ocean using machine learning M. Sonnewald et al. 10.1088/1748-9326/ac0eb0
127. An ensemble Kalman filter-based ocean data assimilation system improved by adaptive observation error inflation (AOEI) S. Ohishi et al. 10.5194/gmd-15-9057-2022
128. Implementation of an Adaptive Bias‐Aware Extended Kalman Filter for Sea‐Ice Data Assimilation in the HARMONIE‐AROME Numerical Weather Prediction System Y. Batrak 10.1029/2021MS002533
129. Correction of inertial oscillations by assimilation of HF radar data in a model of the Ligurian Sea L. Vandenbulcke et al. 10.1007/s10236-016-1012-5
130. RELATIONSHIP BETWEEN SEA ICE CONDITION AND NAVIGABLE SPEED ALONG THE NORTHERN SEA ROUTE N. OTSUKA et al. 10.2208/jscejoe.74.I_25
131. Assessment of an ensemble system that assimilates Jason-1/Envisat altimeter data in a probabilistic model of the North Atlantic ocean circulation G. Candille et al. 10.5194/os-11-425-2015
132. Altimetry Data Assimilation Into a Numerical Model of Ocean Dynamics in the South Atlantic I. Deinego et al. 10.1134/S0001437021050039
133. Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling Y. Matsuzaki & T. Inoue 10.1029/2021JC017911
134. Artificial Neural Network Model for Estimating Ocean Heat Content in the Sea Ice-Covered Arctic Regions Using Satellite Data K. Prakash & P. Shanmugam 10.1109/ACCESS.2022.3213942
135. Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions E. Olmedo et al. 10.3390/rs10111772
136. On the future navigability of Arctic sea routes: High-resolution projections of the Arctic Ocean and sea ice Y. Aksenov et al. 10.1016/j.marpol.2015.12.027
137. Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020 S. Cheng et al. 10.5194/tc-17-1735-2023
138. Implicitly Localized MCMC Sampler to Cope With Non-local/Non-linear Data Constraints in Large-Size Inverse Problems J. Brankart 10.3389/fams.2019.00058
139. Estimation of Ocean Biogeochemical Parameters in an Earth System Model Using the Dual One Step Ahead Smoother: A Twin Experiment T. Singh et al. 10.3389/fmars.2022.775394
140. An evaluation of high-resolution ocean reanalyses in the California current system D. Amaya et al. 10.1016/j.pocean.2022.102951
141. Floe Size Effect on Wave‐Ice Interactions: Possible Effects, Implementation in Wave Model, and Evaluation G. Boutin et al. 10.1029/2017JC013622
142. Constraining energetic slope currents through assimilation of high-frequency radar observations A. Sperrevik et al. 10.5194/os-11-237-2015
143. Ensemble kalman variational objective: a variational inference framework for sequential variational auto-encoders T. Ishizone et al. 10.1587/nolta.14.691
144. NorCPM1 and its contribution to CMIP6 DCPP I. Bethke et al. 10.5194/gmd-14-7073-2021
145. A Simple Bias Correction Scheme in Ocean Data Assimilation C. Yan & J. Zhu 10.3390/jmse11010205
146. Uncertainty of Arctic summer ice drift assessed by high‐resolution SAR data H. Sumata et al. 10.1002/2015JC010810
147. Benefit of vertical localization for sea surface temperature assimilation in isopycnal coordinate model Y. Wang et al. 10.3389/fclim.2022.918572
148. On Temporal Scale Separation in Coupled Data Assimilation with the Ensemble Kalman Filter M. Tondeur et al. 10.1007/s10955-020-02525-z
149. Framework for an Ocean‐Connected Supermodel of the Earth System F. Counillon et al. 10.1029/2022MS003310
150. Monitoring the spreading of the Amazon freshwater plume by MODIS, SMOS, Aquarius, and TOPAZ A. Korosov et al. 10.1002/2014JC010155
151. Dynamics of an assembly of rigid ice floes M. Rabatel et al. 10.1002/2015JC010909
152. Presentation of the dynamical core of neXtSIM, a new sea ice model S. Bouillon & P. Rampal 10.1016/j.ocemod.2015.04.005
153. Ocean Reanalyses: Recent Advances and Unsolved Challenges A. Storto et al. 10.3389/fmars.2019.00418
154. An improved optical flow method to estimate Arctic sea ice velocity (winter 2014–2016) H. Li et al. 10.1007/s13131-021-1867-2
155. Partitioning of Kinetic Energy in the Arctic Ocean's Beaufort Gyre M. Zhao et al. 10.1029/2018JC014037
156. Evaluation of sea-ice thickness from four reanalyses in the Antarctic Weddell Sea Q. Shi et al. 10.5194/tc-15-31-2021
157. Satellite-derived multi-year trend in primary production in the Arctic Ocean D. Petrenko et al. 10.1080/01431161.2012.762698
158. Insights on multivariate updates of physical and biogeochemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling L. Yu et al. 10.1016/j.ocemod.2018.04.005
159. Sea‐surface temperature and salinity product comparison against external in situ data in the Arctic Ocean J. Stroh et al. 10.1002/2015JC011005
160. Sensitivity of the Arctic sea ice concentration forecasts to different atmospheric forcing: a case study Q. Yang et al. 10.1007/s13131-014-0566-7
161. Decorrelation scales for Arctic Ocean hydrography – Part I: Amerasian Basin H. Sumata et al. 10.5194/os-14-161-2018
162. Effect of model error representation in the Yellow and East China Sea modeling system based on the ensemble Kalman filter K. Kwon et al. 10.1007/s10236-015-0909-8
163. Subinertial Variability in Four Southeast Greenland Fjords in Realistic Numerical Simulations R. Gelderloos et al. 10.1029/2022JC018820
164. Optimising assimilation of hydrographic profiles into isopycnal ocean models with ensemble data assimilation Y. Wang et al. 10.1016/j.ocemod.2017.04.007
165. An ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0 S. Ohishi et al. 10.5194/gmd-15-8395-2022
166. Optimising assimilation of sea ice concentration in an Earth system model with a multicategory sea ice model M. Kimmritz et al. 10.1080/16000870.2018.1435945
167. Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting? E. Hunke et al. 10.1007/s40641-020-00162-y
168. Surface currents in operational oceanography: Key applications, mechanisms, and methods J. Röhrs et al. 10.1080/1755876X.2021.1903221
169. Predictability of the extreme precipitation days in central Eastern Africa during january to may period J. Kazora et al. 10.1007/s40808-024-01967-8
170. On Suitability of ALOS-2/PALSAR-2 Dual-Polarized SAR Data for Arctic Sea Ice Parameter Estimation J. Karvonen et al. 10.1109/TGRS.2020.2985696
171. Arctic ocean–sea ice reanalysis for the period 2007–2016 using the adjoint method G. Lyu et al. 10.1002/qj.4002
172. Wave–sea-ice interactions in a brittle rheological framework G. Boutin et al. 10.5194/tc-15-431-2021
173. Enhanced regional ocean ensemble data assimilation through atmospheric coupling in the SKRIPS model R. Sun et al. 10.1016/j.ocemod.2024.102424
174. Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts F. Zhao et al. 10.5194/gmd-17-6867-2024
175. Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN–HIRLAM numerical weather prediction system version 38h1 Y. Batrak et al. 10.5194/gmd-11-3347-2018
176. TOC and satellite-sensed chlorophyll and primary production at the Arctic Front in the Nordic Seas K. Børsheim et al. 10.1016/j.jmarsys.2014.07.012
177. Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system T. Nakanowatari et al. 10.5194/tc-12-2005-2018
178. Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses B. Dong et al. 10.5194/gmd-16-4233-2023
179. Short‐term sea ice forecasting: An assessment of ice concentration and ice drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System D. Hebert et al. 10.1002/2015JC011283
180. Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation M. Bajo et al. 10.1002/qj.3544
181. Developing a common, flexible and efficient framework for weakly coupled ensemble data assimilation based on C-Coupler2.0 C. Sun et al. 10.5194/gmd-14-2635-2021
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