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Science Group

Marine Systems Modelling

Our mission is to promote greater fundamental understanding of marine systems by developing and applying state-of-the-art computational models. These models simulate marine system functioning and its response to local and global pressures. We use this understanding to promote sustainable use of marine ecosystems, addressing many of the UN sustainable development goals and contributing to IPCC reporting.

Increasingly society requires predictions of how our oceans and coastal seas will be transformed by global (e.g. climate change) and local (e.g. pollution) pressures and how these may impact the resources the ocean provides. Reaching informed management solutions to predicted problems is also essential. These questions demand analysis of interactions and feedbacks within complex systems that occur over many different spatial and temporal scales. Only state-of-the-art numerical models can deliver such information.

We take a “systems” approach, integrating oceanography, marine physics, chemistry, biology, and ecology across the water column, sediments and land and atmospheric interfaces. We integrate models with data from laboratory experiments, in situ and remotely sensed marine observations to test hypotheses, validate simulations, sustain monitoring, and improve forecasts. Our whole systems approach provides an unrivalled ability to understand the marine system and improve predictions of change in the ocean state, ecological functioning, and ecosystem services.

Our work includes: scaling climate pressures to regional and local issues; assessing viability and impacts of aquaculture and fisheries; assessing the function and impact of Marine Protected Areas; supporting sustainable development of the blue economy and associated policies; assessing the fate and impact of micro-plastics, pathogens and other pollutants; predicting ecological status (e.g. deoxygenation, eutrophication, acidification); assessing the impact of climate change, the global ocean carbon cycle (blue carbon); researching climate change mitigation techniques and their consequences for marine systems, including renewables and carbon capture and storage.

In collaboration with the UK Met Office, the UK National Partnership for Ocean Prediction (NPOP) and the UK National Centre for Earth Observations (NCEO) we work to keep UK marine modelling a world-leading national capability.

Much of our work is customer facing, in particular working closely with industry and government departments (BEIS, Defra) in the fields of carbon capture and storage, nuisance species such as Harmful Algal Blooms (“red-tides”) and aquaculture & fisheries. We are leading partners in international science networks, including OceanPredict, International Council for the Exploration of the Sea (ICES) working groups, the North East Atlantic hub of the global Ocean Acidification Observing Network, OSPAR Intersessional Correspondence Group on Ocean Acidification, and Advances in Marine Ecosystem Modelling Research.

PML Project pages

Other projects

CLASS - Modelling 21/22
MISSION ATLANTIC - Towards the Sustainable Develo
SANH  - Phase A -South Asia Nitrogen Hub
CAMPUS - Combining Autonomous
NCEO (SA5) DA 2020-2021
ACTOM - Act on Offshore Monitoring
COMFORT - Our common future ocean -
Blue Communities
DARE - Detection and Attribution…

Resources and Links

Accessing our codes
Some of the codes we develop, including ERSEM are open source and can be obtained via Zenodo: 
Model results

Some model simulation data for both hindcasts and climate forecasts can be found here:

Operational model data
We are part of the consortium that supplies operational models of the North West European Shelf, the data can be accessed here:

We also lead an operational forecast system of the Plymouth Marine region covering the new National Marine Park area:

Advances in Marine Ecosystem Modelling Research (AMEMR)
Every three years we run a dedicated conference for international marine ecosystem modellers that serves as a community hub for sharing and developing ideas and networks: 


  • Flexible modelling suite - We have developed a flexible and inter-operable suite of hydrodynamic and ecosystem models which can be used to design models of appropriate complexity to address a range of scientific and practical questions, comprising physics to fish, local to global, and hindcast to climate scale forecast.
  • Biogeochemical and Ecosystem Modelling (ERSEM) - We develop ERSEM as an open source resource. ERSEM is a unique model in that it contains multiple plankton types, a fully resolved benthic system, the microbial loop, multi-nutrient variable stoichiometry and the carbonate system. ERSEM is modular and interfaced with the Framework for Aquatic Biogeochemical Modelling (FABM), enabling ready configuration to support different complexities and scenarios as necessary and can be coupled with many different hydrodynamic frameworks that allow us to (potentially) simulate every marine ecosystem on earth, from coastal to global.
  • Climate projections - We use our models to project the future evolution of marine systems under changing climate scenarios to understand the extent of changes to water temperature, ocean acidification, (de)oxygenation and nutrient availability, how these may impact ecosystems and society.
  • Aquaculture - PML has developed a specialist shellfish aquaculture model (ShellSim) which enables the projection of culture yields for several commonly farmed species. When coupled with hydrodynamic and ecosystem models we can assess sustainability and carrying capacity for individual farms or regions.
  • Fisheries and charismatic species - We develop and or operate a range of models that describe specific species such as seagrasses, jellyfish and fisheries. Coupling these with our hydrodynamic-ecosystem models allows us to forecast productivity, ranges and nuisance occurrence. 
  • High resolution modelling - Based on the FVCOM model system which allows for variable resolution across the model domain we are able to apply physical-ecosystem models that explore highly localised processes and interactions, whilst not omitting regional dynamics. 
  • Pollution, pathogen and particle tracking - Based primarily on the high-resolution models we have developed PyLag, an offline particle tracking model that can be used to track the dispersal of a range of particles in the marine system including plastics and pathogens.
  • Offshore energy -  We into, apply our models to predict the behaviour of hypothetical leakage and derive strategies to appropriately monitor Carbon Capture and Storage (CCS) sites. Other research investigates the impact of renewable energy infrastructure on the marine environment. Further we develop predictive tools to help keep power station coolant water intakes free of biofouling.
  • Operational modelling and data assimilation - PML  leads biogeochemical data assimilation for marine ecology, within national (UK NPOP) and international (OceanPredict) networks .As part of a consortium we supply the operational simulations of the North West European shelf and ourselves deliver operational simulations of the Plymouth region.

Latest publications

View more publications on our repository

People who work in this area of research

Dr Yuri Artioli

Marine Ecosystem Modeller
yuti6/22/2024 6:14:23

Dr Muchamad Al Azhar

Ocean Modeller
maz6/22/2024 6:14:23

Deep S. Banerjee

Modelling Scientist
dba6/22/2024 6:14:23

Professor Jerry Blackford

Head of Science: Marine Systems Modelling
jcb6/22/2024 6:14:23

Dr James Clark

Marine Ecosystem Modeller
jcl6/22/2024 6:14:23

Dr Lee de Mora

Marine Ecosystem Modeller
ledm6/22/2024 6:14:23

Dr Marius Dewar

made6/22/2024 6:14:23

Professor Kevin Flynn

Plankton ecophysiology modeller
kjf6/22/2024 6:14:23

Dr Molly James

Marine Ecosystems Modeller
moja6/22/2024 6:14:23

Dr Susan Kay

Numerical Modeller
suka6/22/2024 6:14:23

Dr Gennadi Lessin

Marine System Modeller
gle6/22/2024 6:14:23

Dr Yaru Li

yli6/22/2024 6:14:23

Dr Rebecca Millington

Regional-Global Biogeochemical Modelling Scientist
rmi6/22/2024 6:14:23

Francesco Pallottino

PhD Student
fpa6/22/2024 6:14:23

Dr Dale Partridge

dapa6/22/2024 6:14:23

Dr Helen Powley

hpo6/22/2024 6:14:23

Dr Sevrine Sailley

Ecosystem modeller
sesa6/22/2024 6:14:23

Dr Jozef Skakala

Ecosystem modeller
jos6/22/2024 6:14:23

Dr Ricardo Torres

Systems Modeller Data Assimilation
rito6/22/2024 6:14:23

Michael Wathen

Research Software Engineer
miwa6/22/2024 6:14:23

Dr Robert Wilson

Ecosystem Modeller
rwi6/22/2024 6:14:23