Establishing influence of light fields and photophysiology parameterization on the performance of coupled physical ecosystem models of quantity

Establishing influence of light fields and photophysiology parameterization on the
performance of coupled physical ecosystem models of quantity and timing of primary production in the Barents Sea.

Arctic seas are warming faster than any other part of the global ocean with rapid changes in ice cover fundamentally altering coupling between physical, chemical and biological processes. The NERC Changing Arctic Ocean program is focused on understanding these feedback mechanisms and how they will cascade upwards through ecosystem functions. In particular, Arctic PRIZE and PEANUTS aim to understand the impact of these changes on both the timing and volume of primary production with potential impacts on the subsequent trophic level characterised by zooplankton (copepods).

The aim of this project is to establish the sensitivity of existing nutrient-phytoplankton-zooplankton (NPZ) models to the range of forcing mechanisms they encompass and to establish a hierarchy of potential upgrades in terms of their benefit-cost. In particular, we want to examine the impact of incorporating more complete light field models and better resolved photophysiology on overall performance. Does the additional computational cost of such approaches result in significantly superior predictive skill? To what extent does better resolved phytoplankton community composition and spectral light field result in improved prediction of primary production?

The overall aim is to establish recommendations for optimised modelling approaches that combine sufficient predictive skill with minimised model complexity. Importantly, we hope to establish an optimised set of model inputs that will drive future observation programs in an area where such efforts are particularly challenging. Specific objectives include:

1. Derivation of a bio-optical model for the Barents Sea taking into account seasonal changes in taxonomic composition and photophysiology.
2. Application of the bio-optical model in radiative transfer simulations and validation against in situ radiometry observations.
3. Assessment of the performance of existing and increasingly complex light field models against light fields from radiometric simulations.
4. Implementation of light field models into existing planktonic ecosystem model.
5. Determination of the impact of increasingly complex light field models against specific target parameters including timing and composition of algal blooms and computational requirements.
6. Formulation of recommendations for future light field modelling and measurement requirements.