Articles | Volume 17, issue 6
https://doi.org/10.5194/os-17-1791-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-17-1791-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Dec 2021
Research article |
| 07 Dec 2021
| 07 Dec 2021
Assimilating realistically simulated wide-swath altimeter observations in a high-resolution shelf-seas forecasting system
Robert R. King
CORRESPONDING AUTHOR
Met Office, Exeter, UK
Matthew J. Martin
Met Office, Exeter, UK
Related authors
Robert R. King, Matthew J. Martin, Lucile Gaultier, Jennifer Waters, Clément Ubelmann, and Craig Donlon
Ocean Sci., 20, 1657–1676, https://doi.org/10.5194/os-20-1657-2024, https://doi.org/10.5194/os-20-1657-2024, 2024
Short summary
Short summary
We use simulations of our ocean forecasting system to compare the impact of additional altimeter observations from two proposed future satellite constellations. We found that, in our system, an altimeter constellation of 12 nadir altimeters produces improved predictions of sea surface height, surface currents, temperature, and salinity compared to a constellation of 2 wide-swath altimeters.
Marina Tonani, Peter Sykes, Robert R. King, Niall McConnell, Anne-Christine Péquignet, Enda O'Dea, Jennifer A. Graham, Jeff Polton, and John Siddorn
Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, https://doi.org/10.5194/os-15-1133-2019, 2019
Short summary
Short summary
A new high-resolution ocean model at 1.5 km has replaced the 7 km system for delivering short-term forecasts of the North-West European Shelf seas. The products (temperature, salinity, currents, and sea surface height) are available on the Copernicus Marine Service catalogue. This study focuses on the high-resolution impact on the quality of the products delivered to the users. Results show that the high-resolution model is better at resolving the variability of the physical variables.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
Short summary
Short summary
Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
Enda O'Dea, Rachel Furner, Sarah Wakelin, John Siddorn, James While, Peter Sykes, Robert King, Jason Holt, and Helene Hewitt
Geosci. Model Dev., 10, 2947–2969, https://doi.org/10.5194/gmd-10-2947-2017, https://doi.org/10.5194/gmd-10-2947-2017, 2017
Short summary
Short summary
An update to an ocean modelling configuration for the European North West Shelf is described. It is assessed against observations and climatologies for 1981–2012. Sensitivities in the model configuration updates are assessed to understand changes in the model system. The model improves upon an existing model of the region, although there remain some areas with significant biases. The paper highlights the dependence upon the quality of the river inputs.
Robert R. King, Matthew J. Martin, Lucile Gaultier, Jennifer Waters, Clément Ubelmann, and Craig Donlon
Ocean Sci., 20, 1657–1676, https://doi.org/10.5194/os-20-1657-2024, https://doi.org/10.5194/os-20-1657-2024, 2024
Short summary
Short summary
We use simulations of our ocean forecasting system to compare the impact of additional altimeter observations from two proposed future satellite constellations. We found that, in our system, an altimeter constellation of 12 nadir altimeters produces improved predictions of sea surface height, surface currents, temperature, and salinity compared to a constellation of 2 wide-swath altimeters.
Yann Drillet, Matthew Martin, Yasumasa Miyazawa, Mike Bell, Eric Chassignet, and Stefania Ciliberti
State Planet Discuss., https://doi.org/10.5194/sp-2024-38, https://doi.org/10.5194/sp-2024-38, 2024
Revised manuscript accepted for SP
Short summary
Short summary
This article describes the various stages of research and development that have been carried out over the last few decades to produce an operational reference service for global ocean monitoring and forecasting.
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc’h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-3143, https://doi.org/10.5194/egusphere-2024-3143, 2024
Short summary
Short summary
We describe major improvements of the Met Office's global ocean-sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1-day forecasts. The new system performance in past conditions, where sub-surface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
Michael J. Bell, Yann Drillet, Matthew Martin, Andreas Schiller, and Stefania Ciliberti
State Planet Discuss., https://doi.org/10.5194/sp-2024-41, https://doi.org/10.5194/sp-2024-41, 2024
Revised manuscript accepted for SP
Short summary
Short summary
We describe, at an elementary level, the spatially varying properties of the ocean that physical ocean models represent, the principles they use to evolve these properties with time, the physical phenomena that they simulate, and some of the roles these phenomena play within the Earth system. We also describe, in some technical detail, the methods and approximations that the models use and the difficulties that limit their accuracy or reliability.
Matthew J. Martin, Ibrahim Hoteit, Laurent Bertino, and Andrew M. Moore
State Planet Discuss., https://doi.org/10.5194/sp-2024-20, https://doi.org/10.5194/sp-2024-20, 2024
Revised manuscript accepted for SP
Short summary
Short summary
Observations of the ocean from satellites and platforms in the ocean are combined with information from computer models to produce predictions of how the ocean temperature, salinity and currents will evolve over the coming days and weeks, as well as to describe how the ocean has evolved in the past. This paper summarises the methods used to produce these ocean forecasts at various centres around the world and outlines the practical considerations for implementing such forecasting systems.
Jozef Skakala, David Ford, Keith Haines, Amos Lawless, Matthew Martin, Philip Browne, Marcin Chrust, Stefano Ciavatta, Alison Fowler, Daniel Lea, Matthew Palmer, Andrea Rochner, Jennifer Waters, Hao Zuo, Mike Bell, Davi Carneiro, Yumeng Chen, Susan Kay, Dale Partridge, Martin Price, Richard Renshaw, Georgy Shapiro, and James While
EGUsphere, https://doi.org/10.5194/egusphere-2024-1737, https://doi.org/10.5194/egusphere-2024-1737, 2024
Short summary
Short summary
In this paper we review marine data assimilation (MDA) in the UK, its stakeholders, needs, past and present developments in different areas of UK MDA, and offer a vision for their longer future. The specific areas covered are ocean physics and sea ice, marine biogeochemistry, coupled MDA, MDA informing observing network design and MDA theory. We also discuss future vision for MDA resources: observations, software, hardware and people skills.
Emma K. Fiedler, Matthew J. Martin, Ed Blockley, Davi Mignac, Nicolas Fournier, Andy Ridout, Andrew Shepherd, and Rachel Tilling
The Cryosphere, 16, 61–85, https://doi.org/10.5194/tc-16-61-2022, https://doi.org/10.5194/tc-16-61-2022, 2022
Short summary
Short summary
Sea ice thickness (SIT) observations derived from CryoSat-2 satellite measurements have been successfully used to initialise an ocean and sea ice forecasting model (FOAM). Other centres have previously used gridded and averaged SIT observations for this purpose, but we demonstrate here for the first time that SIT measurements along the satellite orbit track can be used. Validation of the resulting modelled SIT demonstrates improvements in the model performance compared to a control.
Marina Tonani, Peter Sykes, Robert R. King, Niall McConnell, Anne-Christine Péquignet, Enda O'Dea, Jennifer A. Graham, Jeff Polton, and John Siddorn
Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, https://doi.org/10.5194/os-15-1133-2019, 2019
Short summary
Short summary
A new high-resolution ocean model at 1.5 km has replaced the 7 km system for delivering short-term forecasts of the North-West European Shelf seas. The products (temperature, salinity, currents, and sea surface height) are available on the Copernicus Marine Service catalogue. This study focuses on the high-resolution impact on the quality of the products delivered to the users. Results show that the high-resolution model is better at resolving the variability of the physical variables.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
Short summary
Short summary
Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
Enda O'Dea, Rachel Furner, Sarah Wakelin, John Siddorn, James While, Peter Sykes, Robert King, Jason Holt, and Helene Hewitt
Geosci. Model Dev., 10, 2947–2969, https://doi.org/10.5194/gmd-10-2947-2017, https://doi.org/10.5194/gmd-10-2947-2017, 2017
Short summary
Short summary
An update to an ocean modelling configuration for the European North West Shelf is described. It is assessed against observations and climatologies for 1981–2012. Sensitivities in the model configuration updates are assessed to understand changes in the model system. The model improves upon an existing model of the region, although there remain some areas with significant biases. The paper highlights the dependence upon the quality of the river inputs.
J. R. Siddorn, S. A. Good, C. M. Harris, H. W. Lewis, J. Maksymczuk, M. J. Martin, and A. Saulter
Ocean Sci., 12, 217–231, https://doi.org/10.5194/os-12-217-2016, https://doi.org/10.5194/os-12-217-2016, 2016
Short summary
Short summary
The Met Office provides a range of services in the marine environment. To support these services, and to ensure they evolve to meet the demands of users and are based on the best available science, a number of scientific challenges need to be addressed. The paper summarises the key challenges, and highlights some priorities for the ocean monitoring and forecasting research group at the Met Office.
E. W. Blockley, M. J. Martin, A. J. McLaren, A. G. Ryan, J. Waters, D. J. Lea, I. Mirouze, K. A. Peterson, A. Sellar, and D. Storkey
Geosci. Model Dev., 7, 2613–2638, https://doi.org/10.5194/gmd-7-2613-2014, https://doi.org/10.5194/gmd-7-2613-2014, 2014
Cited articles
Bédard, J. and Buehner, M.: A practical assimilation approach to extract smaller-scale information from observations with spatially correlated errors: An idealized study, Q. J. Roy. Meteor. Soc., 146, 468–482, 2020. a
Benkiran, M., Ruggiero, G., Greiner, E., Le Traon, P.-Y., Remy, E., Lellouche, J. M., Bourdalle-Badie, R., Drillet, Y., and Tchonang, B.:
Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System Part 1: Methods,
Frontiers in Marine Science,
8, 947, https://doi.org/10.3389/fmars.2021.691955, 2021. a
Berg, P. and Poulsen, J. W.: Implementation details for HBM, DMI Technical Report No. 12-11, Danish Meteorological Institute, Ministry for Climate and Energy, available at: https://www.dmi.dk/fileadmin/Rapporter/TR/tr12-11.pdf (last access: 6 December 2021), 2012. a
Blockley, E. W., Martin, M. J., McLaren, A. J., Ryan, A. G., Waters, J., Lea, D. J., Mirouze, I., Peterson, K. A., Sellar, A., and Storkey, D.: Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts, Geosci. Model Dev., 7, 2613–2638, https://doi.org/10.5194/gmd-7-2613-2014, 2014. a
Bloom, S. C., Takacs, L. L., da Silva, A. M., and Ledvina, D.:
Data Assimilation Using Incremental Analysis Updates,
Mon. Weather Rev.,
124, 1256–1271, https://doi.org/https://doi.org/10.1175/1520-0493(1996)124%3C1256:DAUIAU%3E2.0.CO;2, 1996. a
Bonaduce, A., Benkiran, M., Remy, E., Le Traon, P. Y., and Garric, G.: Contribution of future wide-swath altimetry missions to ocean analysis and forecasting, Ocean Sci., 14, 1405–1421, https://doi.org/10.5194/os-14-1405-2018, 2018. a
Carrier, M. J., Ngodock, H. E., Smith, S. R., Souopgui, I., and Bartels, B.:
Examining the Potential Impact of SWOT Observations in an Ocean Analysis – Forecasting Systema,
Mon. Weather Rev.,
144, 3767–3782, https://doi.org/10.1175/MWR-D-15-0361.1, 2016. a, b
Cooper, M. and Haines, K.:
Altimetric assimilation with water property conservation,
J. Geophys. Res.-Oceans,
101, 1059–1077, 1996. a
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017. a
D'Addezio, J. M., Smith, S., Jacobs, G. A., Helber, R. W., Rowley, C., Souopgui, I., and Carrier, M. J.:
Quantifying wavelengths constrained by simulated SWOT observations in a submesoscale resolving ocean analysis/forecasting system,
Ocean Model.,
135, 40–55, https://doi.org/10.1016/j.ocemod.2019.02.001, 2019. a
De Mey-Frémaux, P., Ayoub, N., Barth, A., Brewin, R., Charria, G., Campuzano, F., Ciavatta, S., Cirano, M., Edwards, C. A., Federico, I., Gao, S., Garcia Hermosa, I., Garcia Sotillo, M., Hewitt, H., Hole, L. R., Holt, J., King, R., Kourafalou, V., Lu, Y., Mourre, B., Pascual, A., Staneva, J., Stanev, E. V., Wang, H., and Zhu, X.:
Model-Observations Synergy in the Coastal Ocean,
Frontiers in Marine Science,
6, 436, https://doi.org/10.3389/fmars.2019.00436, 2019. a
Dufau, C., Orsztynowicz, M., Dibarboure, G., Morrow, R., and Le Traon, P.-Y.:
Mesoscale resolution capability of altimetry: Present and future,
J. Geophys. Res.-Oceans,
121, 4910–4927, https://doi.org/10.1002/2015JC010904, 2016. a
Durand, M., Fu, L.-L., Lettenmaier, D. P., Alsdorf, D. E., Rodriguez, E., and Esteban-Fernandez, D.:
The surface water and ocean topography mission: Observing terrestrial surface water and oceanic submesoscale eddies,
P. IEEE,
98, 766–779, 2010. a
Flather, R.:
Results from a model of the north-east Atlantic relating to the Norwegian Coastal Current,
in: The Norwegian Coastal Current,
edited by: Sætre, R. and Mork, M.,
University of Bergen, Bergen, 2, 458, 1981. a
Fowler, A. M., Dance, S. L., and Waller, J. A.:
On the interaction of observation and prior error correlations in data assimilation,
Q. J. Roy. Meteor. Soc.,
144, 48–62, https://doi.org/10.1002/qj.3183, 2018. a
Good, S. A., Martin, M. J., and Rayner, N. A.:
EN4: Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates,
J. Geophys. Res.-Oceans,
118, 6704–6716, 2013. a
Graham, J. A., O'Dea, E., Holt, J., Polton, J., Hewitt, H. T., Furner, R., Guihou, K., Brereton, A., Arnold, A., Wakelin, S., Castillo Sanchez, J. M., and Mayorga Adame, C. G.: AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf, Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, 2018. a, b
Guillet, O., Weaver, A. T., Vasseur, X., Michel, Y., Gratton, S., and Gürol, S.:
Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh,
Q. J. Roy. Meteor. Soc.,
145, 1947–1967, 2019. a
Halliwell Jr., G. R., Srinivasan, A., Kourafalou, V., Yang, H., Willey, D., Le Henaff, M., and Atlas, R.: Rigorous Evaluation of a Fraternal Twin Ocean OSSE System for the Open Gulf of Mexico, J. Atmos. Ocean. Tech., 31, 105–130, https://doi.org/10.1175/JTECH-D-13-00011.1, 2014. a
Halliwell, G. R., Mehari, M. F., Le Hénaff, M., Kourafalou, V. H., Androulidakis, I. S., Kang, H. S., and Atlas, R.:
North Atlantic Ocean OSSE system: Evaluation of operational ocean observing system components and supplemental seasonal observations for potentially improving tropical cyclone prediction in coupled systems,
J. Oper. Oceanogr.,
10, 154–175, 2017. a
Hoffman, R. N. and Atlas, R.:
Future observing system simulation experiments,
B. Am. Meteorol. Soc.,
97, 1601–1616, 2016. a
Ingleby, B. and Huddleston, M.:
Quality control of ocean temperature and salinity profiles – Historical and real-time data,
J. Marine Syst.,
65, 158–175, 2007. a
Jacobs, G. A., Richman, J. G., Doyle, J. D., Spence, P. L., Bartels, B. P., Barron, C. N., Helber, R. W., and Bub, F. L.:
Simulating conditional deterministic predictability within ocean frontogenesis,
Ocean Model.,
78, 1–16, 2014. a
Lea, D., Drecourt, J.-P., Haines, K., and Martin, M.:
Ocean altimeter assimilation with observational-and model-bias correction,
Q. J. Roy. Meteor. Soc.,
134, 1761–1774, 2008. a
Le Henaff, M., De Mey, P., Mourre, B., and Le Traon, P.-Y.:
Contribution of a Wide-Swath Altimeter in a Shelf Seas Assimilation System: Impact of the Satellite Roll Errors,
J. Atmos. Ocean. Tech.,
25, 2133–2144, https://doi.org/10.1175/2008JTECHO576.1, 2008. a
Lellouche, J.-M., Greiner, E., Le Galloudec, O., Garric, G., Regnier, C., Drevillon, M., Benkiran, M., Testut, C.-E., Bourdalle-Badie, R., Gasparin, F., Hernandez, O., Levier, B., Drillet, Y., Remy, E., and Le Traon, P.-Y.: Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time
Lewis, H. W., Castillo Sanchez, J. M., Siddorn, J., King, R. R., Tonani, M., Saulter, A., Sykes, P., Pequignet, A.-C., Weedon, G. P., Palmer, T., Staneva, J., and Bricheno, L.: Can wave coupling improve operational regional ocean forecasts for the north-west European Shelf?, Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, 2019. a
Li, Z., Wang, J., and Fu, L.-L.:
An Observing System Simulation Experiment for Ocean State Estimation to Assess the Performance of the SWOT Mission: Part 1 – A Twin Experiment,
J. Geophys. Res.-Oceans,
124, 4838–4855, https://doi.org/10.1029/2018JC014869, 2019. a
Madec, G.: NEMO ocean engine, in: Note du Pôle de modèlisation, France, no. 27, IPSL – Institut Pierre-Simon Laplace, ISSN 1288-1619, 2008. a
Metref, S., Cosme, E., Le Guillou, F., Le Sommer, J., Brankart, J.-M., and Verron, J.:
Wide-Swath Altimetric Satellite Data Assimilation With Correlated-Error Reduction,
Frontiers in Marine Science,
6, 822, https://doi.org/10.3389/fmars.2019.00822, 2020. a
Mogensen, K., Balmaseda, M., Weaver, A., Martin, M., and Vidard, A.:
NEMOVAR: A variational data assimilation system for the NEMO ocean model,
ECMWF Newsletter,
120, 17–22, 2009. a
Mogensen, K., Balmaseda, M. A., and Weaver, A.:
The NEMOVAR ocean data assimilation system as implemented in the ECMWF ocean analysis for System 4, Technical Report TR-CMGC-12-30, European Centre for Medium-Range Weather Forecasts, CERFACS, 2012. a
Morrow, R., Blumstein, D., and Dibarboure, G.: Fine-scale altimetry and the future SWOT mission, in: New Frontiers in Operational Oceanography, edited by: Chassignet, E., Pascual, A., Tintoré, J., and Verron, J., GODAE OceanView, 191–226, https://doi.org/10.17125/gov2018.ch08, 2018.
a, b
Oke, P. R., Larnicol, G., Fujii, Y., Smith, G. C., Lea, D. J., Guinehut, S., Remy, E., Balmaseda, M. A., Rykova, T., Surcel-Colan, D., and Martin, M. J.: Assessing the impact of observations on ocean forecasts and reanalyses: Part 1, Global studies, J. Oper. Oceanogr., 8, s49–s62, 2015. a
Ruggiero, G. A., Cosme, E., Brankart, J.-M., Le Sommer, J., and Ubelmann, C.:
An Efficient Way to Account for Observation Error Correlations in the Assimilation of Data from the Future SWOT High-Resolution Altimeter Mission,
J. Atmos. Ocean. Tech.,
33, 2755–2768, https://doi.org/10.1175/JTECH-D-16-0048.1, 2016. a
Saulter, A., Bunney, C., Li, J.-G., and Palmer, T.:
Process and resolution impacts on UK coastal wave predictions from operational global-regional wave models,
in: Proceedings of the 15th International Workshop on Wave Hindcasting and Forecasting and 6th Coastal Hazard Symposium, Liverpool, UK, 10–15, 2017. a
Storkey, D., Blockley, E. W., Furner, R., Guiavarc'h, C., Lea, D., Martin, M. J., Barciela, R. M., Hines, A., Hyder, P., and Siddorn, J. R.:
Forecasting the ocean state using NEMO:The new FOAM system,
J. Oper. Oceanogr.,
3, 3–15, https://doi.org/10.1080/1755876X.2010.11020109, 2010. a
Tchonang, B. C., Benkiran, M., Le Traon, P.-Y., Jan van Gennip, S., Lellouche, J. M., and Ruggiero, G.:
Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System – Part 2: Results,
Frontiers in Marine Science,
8, 1208, https://doi.org/10.3389/fmars.2021.687414, 2021. a
Tonani, M., Sykes, P., King, R. R., McConnell, N., Péquignet, A.-C., O'Dea, E., Graham, J. A., Polton, J., and Siddorn, J.: The impact of a new high-resolution ocean model on the Met Office North-West European Shelf forecasting system, Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, 2019. a, b, c
Troccoli, A. and Haines, K.:
Use of the temperature–salinity relation in a data assimilation context,
J. Atmos. Ocean. Tech.,
16, 2011–2025, 1999. a
Uematsu, A., Nakamura, R., Nakajima, Y., and Yajima, Y.: X-band interferometric SAR sensor for the Japanese altimetry mission, COMPIRA,
in: 2013 IEEE International Geoscience and Remote Sensing Symposium – IGARSS, 21–26 July 2013, Melbourne, VIC, Australia, 2943–2946, 2013. a
Waters, J., Lea, D. J., Martin, M. J., Mirouze, I., Weaver, A., and While, J.:
Implementing a variational data assimilation system in an operational
While, J. and Martin, M. J.:
Variational bias correction of satellite sea-surface temperature data incorporating observations of the bias,
Q. J. Roy. Meteor. Soc.,
145, 2733–2754, 2019. a
Short summary
The SWOT satellite will provide a step change in our ability to measure the sea surface height over large areas, and so improve operational ocean forecasts, but will be affected by large correlated errors. We found that while SWOT observations without these errors significantly improved our system, including correlated errors degraded most variables. To realise the full benefits offered by the SWOT mission, we must develop methods to account for correlated errors in ocean forecasting systems.
The SWOT satellite will provide a step change in our ability to measure the sea surface height...
