Articles | Volume 7, issue 1
https://doi.org/10.5194/os-7-75-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-7-75-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Jan 2011
Research article |
| 28 Jan 2011
Assessment of the three dimensional temperature and salinity observational networks in the Baltic Sea and North Sea
W. Fu
Center for Ocean and Ice (COI), Danish Meteorological Institute (DMI), Denmark
J. L. Høyer
Center for Ocean and Ice (COI), Danish Meteorological Institute (DMI), Denmark
J. She
Center for Ocean and Ice (COI), Danish Meteorological Institute (DMI), Denmark
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Cited
19 citations as recorded by crossref.
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- Reconstruction of Large-Scale Sea Surface Temperature and Salinity Fields Using Sub-Regional EOF Patterns From Models J. Elken et al. 10.3389/feart.2019.00232
- Designing a Large Scale Autonomous Observing Network: A Set Theory Approach D. Byrne et al. 10.3389/fmars.2022.879003
- Objective array design for three-dimensional temperature and salinity observation: Application to the South China Sea M. Qu et al. 10.1007/s13131-021-1975-z
- Unstructured-grid model for the North Sea and Baltic Sea: Validation against observations Y. Zhang et al. 10.1016/j.ocemod.2015.11.009
- Simple heterogeneity parametrization for sea surface temperature and chlorophyll J. Skákala & T. Smyth 10.1016/j.jmarsys.2016.01.010
- Assessing the state of the Barents Sea using indicators: how, when, and where? C. Hansen et al. 10.1093/icesjms/fsab053
- Physical processes in the transition zone between North Sea and Baltic Sea. Numerical simulations and observations E. Stanev et al. 10.1016/j.ocemod.2015.07.002
- On the Role of Temperature and Salinity Data Assimilation to Constrain a Coupled Physical–Biogeochemical Model in the Baltic Sea W. Fu 10.1175/JPO-D-15-0027.1
- Optimising environmental monitoring for carbon dioxide sequestered offshore P. Cazenave et al. 10.1016/j.ijggc.2021.103397
- A pre-operational three Dimensional variational data assimilation system in the North/Baltic Sea S. Zhuang et al. 10.5194/os-7-771-2011
- Developing European operational oceanography for Blue Growth, climate change adaptation and mitigation, and ecosystem-based management J. She et al. 10.5194/os-12-953-2016
- Optimizing Monitoring Programs: A Case Study Based on the OSPAR Eutrophication Assessment for UK Waters L. García-García et al. 10.3389/fmars.2018.00503
- Evaluating acoustic-trawl survey strategies using an end-to-end ecosystem model A. Holmin et al. 10.1093/icesjms/fsaa120
- Optimizing observational networks combining gliders, moored buoys and FerryBox in the Bay of Biscay and English Channel G. Charria et al. 10.1016/j.jmarsys.2016.04.003
- Disclosing the truth: Are models better than observations? M. Skogen et al. 10.3354/meps13574
- Environmental drivers affecting the status of top commercial fish stocks in the Baltic Sea: review M. Rosciszewski-Dodgson & G. Cirella 10.3389/fmars.2024.1399707
- Ecosystem modelling across a salinity gradient from the North Sea to the Baltic Sea M. Maar et al. 10.1016/j.ecolmodel.2011.03.006
17 citations as recorded by crossref.
- A 20-year reanalysis experiment in the Baltic Sea using three-dimensional variational (3DVAR) method W. Fu et al. 10.5194/os-8-827-2012
- The future of the western Baltic Sea: two possible scenarios U. Gräwe et al. 10.1007/s10236-013-0634-0
- Reconstruction of Large-Scale Sea Surface Temperature and Salinity Fields Using Sub-Regional EOF Patterns From Models J. Elken et al. 10.3389/feart.2019.00232
- Designing a Large Scale Autonomous Observing Network: A Set Theory Approach D. Byrne et al. 10.3389/fmars.2022.879003
- Objective array design for three-dimensional temperature and salinity observation: Application to the South China Sea M. Qu et al. 10.1007/s13131-021-1975-z
- Unstructured-grid model for the North Sea and Baltic Sea: Validation against observations Y. Zhang et al. 10.1016/j.ocemod.2015.11.009
- Simple heterogeneity parametrization for sea surface temperature and chlorophyll J. Skákala & T. Smyth 10.1016/j.jmarsys.2016.01.010
- Assessing the state of the Barents Sea using indicators: how, when, and where? C. Hansen et al. 10.1093/icesjms/fsab053
- Physical processes in the transition zone between North Sea and Baltic Sea. Numerical simulations and observations E. Stanev et al. 10.1016/j.ocemod.2015.07.002
- On the Role of Temperature and Salinity Data Assimilation to Constrain a Coupled Physical–Biogeochemical Model in the Baltic Sea W. Fu 10.1175/JPO-D-15-0027.1
- Optimising environmental monitoring for carbon dioxide sequestered offshore P. Cazenave et al. 10.1016/j.ijggc.2021.103397
- A pre-operational three Dimensional variational data assimilation system in the North/Baltic Sea S. Zhuang et al. 10.5194/os-7-771-2011
- Developing European operational oceanography for Blue Growth, climate change adaptation and mitigation, and ecosystem-based management J. She et al. 10.5194/os-12-953-2016
- Optimizing Monitoring Programs: A Case Study Based on the OSPAR Eutrophication Assessment for UK Waters L. García-García et al. 10.3389/fmars.2018.00503
- Evaluating acoustic-trawl survey strategies using an end-to-end ecosystem model A. Holmin et al. 10.1093/icesjms/fsaa120
- Optimizing observational networks combining gliders, moored buoys and FerryBox in the Bay of Biscay and English Channel G. Charria et al. 10.1016/j.jmarsys.2016.04.003
- Disclosing the truth: Are models better than observations? M. Skogen et al. 10.3354/meps13574
2 citations as recorded by crossref.
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