WP4: Integrated Modelling

Transcription

1 WP4: Integrated Modelling J. I Allen, J van der Molen, J Holt, R Barciela, J Aldridge, Y Artioli, L Amoudry, J Blackford, M Butenschon, J Clark, D Ford, L Polimene, T Silva, N Stephens, S Wakelin, J Bruggeman 15 th Jan 2014 Liverpool

2 Scientific Rationale. Shelf Carbon Budget Wakelin et al 2012 The overarching scientific goal is to enhance our capacity to assess the controls on biogeochemical cycling and hence to quantify with uncertainties the budgets of carbon, nitrogen, phosphorous and silicon including their response to climate, natural variability and anthropogenic stress.

3 UK Shelf Modelling System Biogeochemical Processes Physical Processes European Regional Seas Ecosystem Model ERSEM 3D: NEMO- Shelf 1D: GOTM

4 Marine Ecosystems WP2 UK Shelf Modelling System: SSB Enhancing our capacity to assess the controls on biogeochemical cycling and hence to the budgets of carbon, nitrogen, phosphorous and silicon New and improved biogeochemical process models Revision of Benthic model Community modelling tools; 1D ERSEM-GOTM, 3D ERSEM NEMO- Shelf Hindcast simulations and re-analysis simulations. Sensitivity of biogeochemical cycles to climatic and anthropogenic drivers

5 Nutrient Cycle Developments

6 Benthic Process Model Developments

7 Project in Context Working Groups WP5 Blue Carbon

8 Legacy Deliverables and legacy Published versions of the model code Community modelling tools available on the web; 1D ERSEM- GOTM, 3D Atlantic Margin Model -(ERSEM NEMO-Shelf), model evaluation tools. Hindcast simulations and re-analysis simulations, sub sets of the data deposited with appropriate NERC data centre. Publication of new process models Scientific publications on the sensitivity of shelf seas biogeochemical cycles to climate change and other anthropogenic drivers

9 Marine Ecosystems WP2 MARINE ECOSYTEMS Improve understanding of the regulation of key ecosystem services Integrate improved knowledge in models Apply models to potential management solutions 1. Described by ecosystem model Marine Ecosystem Components Habitats Functional diversity Processes Production Decomposition Foodwebs Ecological interactions 2. Emergent properties of ecosystem model Intermediate Services Supporting Primary production Nutrient cycling Oxygen Regulating Biological control Carbon sequestration 3. Informed by ecosystem model Final Services Provisioning Fish & Shellfish Seaweed Regulating Climate regulation Cultural Healthy environment

10 ecosystem services Marine Ecosystems WP2 Challenges for Ecosystem Modelling ecosystem services biodiversity top-down control bottom-up control Limited representation, because difficult to parameterize, expensive to simulate Simplistic trophic interactions, due to lack of diversity in size, feeding mode Natural variability omitted, because linked to interspecific diversity community structure and size distribution Models require: 1. Explicit, universal description of interspecific differences and relation to function 2. Efficient tools for fast simulation 3. Logic to add and remove detail where appropriate ecosystem services Level of detail is fixed, and ideal only for some spatial resolutions Poor skill at longer time scales, because shifts in species composition not accounted for spatial scales temporal scales ecosystem services

11 physical limit to transport of oxygen Auto - Troph s Auto- Baclteria Hetro -troph s Hetro- Bacteria Organic C C N REDOX Dominant Oxidiser Anaerobic CH4 NH4 H2S Mn (III) POC /DOC NO2 Euphotic zone CO2 = CO3- NO3 Aerobic SO4- Metals NOx O2 O2 H2S > 0 ~ Anaerobic Sub Oxic Hypoxic Oxic O2 ORGANIC INORGANIC mmol O2

12 Interaction with other WPs Constructing conceptual models: What are the major drivers of the processes? e.g. is bacterial physiology important for nitrification, or this can be seen as purely chemical reaction? Are we missing more important processes? Parameterising the model: What are the measured value of the rates? How do they depends on environmental variables? Models as in-silico experiments: Is there some hypotheses that you would like to test, but you can t run a targeted experiment? Upscaling local observation to regional scales: Filling temporal and spatial gap between observations

13 I-MODSSB Summary of Phase 1 Model Development