Articles | Volume 17, issue 6
https://doi.org/10.5194/os-17-1527-2021
© 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-17-1527-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Using feature-based verification methods to explore the spatial and temporal characteristics of the 2019 chlorophyll-a bloom season in a model of the European Northwest Shelf
Marion Mittermaier
CORRESPONDING AUTHOR
Verification, Impacts and Post-Processing, Weather Science, Met
Office, Exeter, EX1 3PB, UK
Rachel North
Verification, Impacts and Post-Processing, Weather Science, Met
Office, Exeter, EX1 3PB, UK
Jan Maksymczuk
Ocean Forecasting Research & Development, Weather Science, Met
Office, Exeter, EX1 3PB, UK
Christine Pequignet
Ocean Forecasting Research & Development, Weather Science, Met
Office, Exeter, EX1 3PB, UK
David Ford
Ocean Forecasting Research & Development, Weather Science, Met
Office, Exeter, EX1 3PB, UK
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Mike Bush, Tom Allen, Caroline Bain, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Humphrey Lean, Adrian Lock, James Manners, Marion Mittermaier, Cyril Morcrette, Rachel North, Jon Petch, Chris Short, Simon Vosper, David Walters, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Nigel Wood, and Mohamed Zerroukat
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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
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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.
David Walters, Ian Boutle, Malcolm Brooks, Thomas Melvin, Rachel Stratton, Simon Vosper, Helen Wells, Keith Williams, Nigel Wood, Thomas Allen, Andrew Bushell, Dan Copsey, Paul Earnshaw, John Edwards, Markus Gross, Steven Hardiman, Chris Harris, Julian Heming, Nicholas Klingaman, Richard Levine, James Manners, Gill Martin, Sean Milton, Marion Mittermaier, Cyril Morcrette, Thomas Riddick, Malcolm Roberts, Claudio Sanchez, Paul Selwood, Alison Stirling, Chris Smith, Dan Suri, Warren Tennant, Pier Luigi Vidale, Jonathan Wilkinson, Martin Willett, Steve Woolnough, and Prince Xavier
Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, https://doi.org/10.5194/gmd-10-1487-2017, 2017
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
David A. Ford, Johan van der Molen, Kieran Hyder, John Bacon, Rosa Barciela, Veronique Creach, Robert McEwan, Piet Ruardij, and Rodney Forster
Biogeosciences, 14, 1419–1444, https://doi.org/10.5194/bg-14-1419-2017, https://doi.org/10.5194/bg-14-1419-2017, 2017
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This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea. These observations were used to validate two physical–biogeochemical ocean model simulations, each of which used different variants of the widely used European Regional Seas Ecosystem Model (ERSEM). The results suggest the ability of the models to reproduce the observed phytoplankton community structure was dependent on the details of the biogeochemical model parameterizations used.
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
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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.
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Short summary
Regions of enhanced chlorophyll-a concentrations can be identified by applying a threshold to the concentration value to a forecast and observed field (or analysis). These regions can then be treated and analysed as features using diagnostic techniques to consider of the evolution of the chlorophyll-a blooms in space and time. This allows us to understand whether the biogeochemistry in the model has any skill in predicting these blooms, their location, intensity, onset, duration and demise.
Regions of enhanced chlorophyll-a concentrations can be identified by applying a threshold to...