Articles | Volume 21, issue 3
https://doi.org/10.5194/bg-21-731-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-731-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Feb 2024
Research article |
| 08 Feb 2024
| 08 Feb 2024
Investigating ecosystem connections in the shelf sea environment using complex networks
Meteorology Department, University of Reading, Reading, UK
National Centre for Earth Observation, Leicester, UK
Jozef Skákala
National Centre for Earth Observation, Leicester, UK
Plymouth Marine Laboratory, Plymouth, UK
Ross Bannister
Meteorology Department, University of Reading, Reading, UK
National Centre for Earth Observation, Leicester, UK
Alberto Carrassi
Meteorology Department, University of Reading, Reading, UK
Department of Physics and Astronomy “Augusto Righi”, University of Bologna, Bologna, Italy
Stefano Ciavatta
Mercator Ocean International, Toulouse, France
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Chaotic dynamical systems are sensitive to the initial conditions, which are crucial for climate forecast. These properties are often used to inform the design of data assimilation (DA), a method used to estimate the exact initial conditions. However, obtaining the instability properties is burdensome for complex problems, both numerically and analytically. Here, we suggest a different viewpoint. We show that the skill of DA can be used to infer the instability properties of a dynamical system.
Ross Noel Bannister
Geosci. Model Dev., 13, 3789–3816, https://doi.org/10.5194/gmd-13-3789-2020, https://doi.org/10.5194/gmd-13-3789-2020, 2020
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Forecasting models start from initial conditions, and data assimilation (DA) is the way that initial conditions are found from a combination of previous model data and latest observations. The ABC model is a simplified convective-scale model developed previously, and ABC-DA is the version of this system that includes the DA capability. This system is described in the present paper, and its performance is demonstrated with a range of options that control how the data assimilation is done.
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Short summary
A complex network is a way of representing which parts of a system are connected to other parts. We have constructed a complex network based on an ecosystem–ocean model. From this, we can identify patterns in the structure and areas of similar behaviour. This can help to understand how natural, or human-made, changes will affect the shelf sea ecosystem, and it can be used in multiple future applications such as improving modelling, data assimilation, or machine learning.
A complex network is a way of representing which parts of a system are connected to other parts....
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