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

建立光场和光生理参数化对巴伦支海初级生产数量和时间耦合物理生态系统模型性能的影响。北极海域的变暖速度比全球海洋的任何其他部分都要快，冰盖的快速变化从根本上改变了物理、化学和生物过程之间的耦合。NERC改变北冰洋项目的重点是了解这些反馈机制，以及它们如何通过生态系统功能向上层叠。特别地，Arctic PRIZE和PEANUTS旨在了解这些变化对初级生产的时间和数量的影响，以及对以浮游动物（桡足类）为特征的后续营养水平的潜在影响。该项目的目的是建立现有营养物-浮游植物-浮游动物（NPZ）模型对其所包含的强迫机制范围的敏感性，并根据其收益-成本建立潜在升级的层次结构。特别是，我们想要检查合并更完整的光场模型和更好地解决光生理对整体性能的影响。这些方法的额外计算成本是否会显著提高预测技能？更好地分辨浮游植物群落组成和光谱光场在多大程度上改善了初级产量的预测？总体目标是建立优化建模方法的建议，将足够的预测技能与最小的模型复杂性相结合。重要的是，我们希望建立一套优化的模型输入，这将推动未来在一个特别具有挑战性的领域的观测项目。具体目标包括：1。考虑到分类学组成和光生理季节变化的巴伦支海生物光学模型的推导。生物光学模型在辐射传输模拟中的应用及其对原位辐射测量观测的验证。评估现有的和日益复杂的光场模型对辐射模拟光场的性能。将光场模型应用于现有的浮游生态系统模型。确定日益复杂的光场模型对特定目标参数的影响，包括藻华的时间和组成以及计算要求。为未来的光场建模和测量要求提出建议。

Establishing influence of light fields and photophysiology parameterization on theperformance 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.