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

建立光场和生物物理学参数化对巴伦支海初级生产量和时间的耦合物理生态系统模型性能的影响北极海变暖速度比全球海洋的任何其他部分都快，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改变北冰洋计划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级联。特别是，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，以及对随后以浮游动物为特征的营养级的潜在影响该项目的目的是建立现有营养浮游植物浮游动物（NPZ）的敏感性因此，需要将这些模型与它们所包含的强制机制的范围相结合，并根据其效益-成本建立潜在升级的等级。特别是，我们想研究纳入更完整的光场模型和更好地解决的生物物理学对整体性能的影响。这种方法的额外计算成本是否会导致显著的上级预测技能？在多大程度上更好地解决浮游植物群落组成和光谱光场的结果，改善初级生产力的预测？总体目标是建立优化建模方法的建议，该方法将联合收割机充分的预测技能与最小化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，以推动未来的观测计划，在这个领域，这种努力特别具有挑战性。具体目标包括：1.推导出一个考虑到分类组成和生物生理学季节变化的巴伦支海生物光学模型。生物光学模型在辐射传输模拟中的应用，以及与现场辐射测量观测的对比验证.评估现有和日益复杂的光场模型对辐射模拟光场的性能。将光场模型应用到现有的水生生态系统模型中.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。制定未来光场建模和测量要求的建议。

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.