18 citations as recorded by crossref.

1. Towards a Multi‐Platform Assimilative System for North Sea Biogeochemistry J. Skákala et al. 10.1029/2020JC016649
2. Determination of discrete sampling locations minimizing both the number of samples and the maximum interpolation error: Application to measurements of carbonate chemistry in surface ocean V. Guglielmi et al. 10.1016/j.seares.2023.102336
3. An observing system simulation experiment for Indian Ocean surface pCO2 measurements V. Valsala et al. 10.1016/j.pocean.2021.102570
4. LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry C. Nissen et al. 10.5194/gmd-17-6415-2024
5. Delayed-Mode Quality Control of Oxygen, Nitrate, and pH Data on SOCCOM Biogeochemical Profiling Floats T. Maurer et al. 10.3389/fmars.2021.683207
6. Using machine learning and Biogeochemical-Argo (BGC-Argo) floats to assess biogeochemical models and optimize observing system design A. Mignot et al. 10.5194/bg-20-1405-2023
7. The impact of ocean biogeochemistry on physics and its consequences for modelling shelf seas J. Skákala et al. 10.1016/j.ocemod.2022.101976
8. Investigating ecosystem connections in the shelf sea environment using complex networks I. Higgs et al. 10.5194/bg-21-731-2024
9. The Southern Ocean carbon and climate observations and modeling (SOCCOM) project: A review J. Sarmiento et al. 10.1016/j.pocean.2023.103130
10. EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters J. Bruggeman et al. 10.5194/gmd-17-5619-2024
11. Combining neural networks and data assimilation to enhance the spatial impact of Argo floats in the Copernicus Mediterranean biogeochemical model C. Amadio et al. 10.5194/os-20-689-2024
12. PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks G. Pietropolli et al. 10.5194/gmd-17-7347-2024
13. A solution for autonomous, adaptive monitoring of coastal ocean ecosystems: Integrating ocean robots and operational forecasts D. Ford et al. 10.3389/fmars.2022.1067174
14. How uncertain and observable are marine ecosystem indicators in shelf seas? J. Skákala et al. 10.1016/j.pocean.2024.103249
15. Deep chlorophyll maximum and nutricline in the Mediterranean Sea: emerging properties from a multi-platform assimilated biogeochemical model experiment A. Teruzzi et al. 10.5194/bg-18-6147-2021
16. Mechanisms driving ESM-based marine ecosystem predictive skill on the east African coast W. Jeon et al. 10.1088/1748-9326/ac7d63
17. Can assimilation of satellite observations improve subsurface biological properties in a numerical model? A case study for the Gulf of Mexico B. Wang et al. 10.5194/os-17-1141-2021
18. Ocean biogeochemical modelling K. Fennel et al. 10.1038/s43586-022-00154-2