Improving simple climate models through a traceable and process-based analysis of ocean heat uptake in AOGCMs and observations

未来气候变化预测为全球遏制人类温室气体排放导致的全球变暖趋势提供了重要指导。提供这些预测的主要工具是大气-海洋环流耦合模式。然而，这些模型在计算上运行起来仍然非常昂贵。因此，简单的气候模式（SCM）已经开发出来，它能够模拟AOGCM中看到的气候响应，但计算成本大大降低。SCMs有多种用途，例如模拟预测如何依赖于关键气候参数，或用于解释AOGCM预测。供应链模型经常用于政策咨询，为了确定供应链模型的有用性和准确性，必须确定其可追溯到全面的AOGCM，并最终追溯到现实。标准模式、AOGCM和观测之间的联系和可追溯性是通过校准过程建立的，校准是确定特定模式控制参数值的关键步骤。似乎有两种主要的校准：物理校准和行为校准，它们的运作方式非常不同。物理校准是通过调用物理参数或对所涉及的物理过程的观测约束来指定给定模型的控制参数的校准。相比之下，行为校准是指指定相同的控制参数，以便模型再现过去、现在或未来条件下实际或模拟气候系统的各种紧急特性。由于气候变化主要受海洋热吸收（OHU）控制，因此气候变化预测的准确性取决于SCM和AOGCM中控制OHU的物理过程的代表性的有效性。这些过程的表现方式在SCM中有很大的不同，从显式到完全隐式的表现。在这个项目中，三个具体的SCM被认为是。在MAGICC中，海洋热吸收通过每个半球的两个垂直平流/扩散方程明确表示。在Gregory（2000）的双层模型中，它通过两个简单的具有两个时间尺度的常微分方程来表示。在Good et al.（2011，2012）的阶跃响应方法中，海洋热吸收是完全隐含的。在本提案中，我们的第一个目标是通过测试每个SCM在相同范围的气候变化情景下的相对表现来评估其通用性程度，以确定OHU的简化表示表现更好。我们的第二个目标将是调查物理和行为校准之间的联系，通过实施MAGICC的物理校准，并测试它是否改善或恶化其性能以及为什么。这将提供关键的新见解，了解海洋热量吸收的哪些方面是强大的，哪些方面需要进一步研究，这将提高SCM的可信度。第一个和第二个目标涉及《呼吁》的目标2。我们的第三个目标将是开发一个通用的和灵活的方法来约束海洋热吸收过程，通过使用NEMO及其伴随的NEMOTAM，允许从物理和行为约束的混合参数的最佳校准。这将使英国具备系统地重新校准海洋模型的关键能力，方法是结合海洋混合过程的观测和理论进展，并测试对气候变化预测的影响。此外，NEMO的优化设置可能对未来许多其他类型的研究有用。这涉及《呼吁》的目标1。这将为NERC-气象局制定UKESM 1的联合战略做出关键贡献。

Future climate change predictions provide essential guidance for the global efforts to curb the global warming trend caused by human emissions of greenhouse gases. The main tool to provide these projections are coupled atmosphere-ocean general circulation models (AOGCMs). However, these models are computationally still very expensive to run. Therefore, simple climate models (SCMs) have been developed, which are able to mimic the climate response seen in the AOGCMs, but at a much reduced computational cost. SCMs are being used for several purposes, e.g. simulating how the projections depend on key climate parameters, or for the interpretation of the AOGCM projections. SCMs are often used for policy advice.To ascertain the usefulness and accuracy of SCMs, it is essential to establish their traceability to comprehensive AOGCMs and ultimately to reality. The link and hence the traceability between SCMs, AOGCMs and observations is established through the process of calibration, which is the key step whereby the values of the control parameters of a given model are set up. There appear to be two main kinds of calibration: physical and behavioural, which operate very differently. A physical calibration is one that specifies the control parameters of a given model by invoking physical arguments or observational constraints on the physical processes involved. In contrast, a behavioural calibration is one that specifies the same control parameters so that the model reproduces various emergent properties of the actual or simulated climate system, under past, present or future conditions. Because climate change is primarily controlled by ocean heat uptake (OHU), the accuracy of climate change projections depends on the validity of the representation of the physical processes controlling OHU in SCMs and AOGCMs. How these processes are represented varies widely across SCMs, and ranges from explicit to entirely implicit representations. In this project, three specific SCMs are considered. In MAGICC, ocean heat uptake is explicitly represented through two vertical advection/diffusion equations for each hemisphere. In Gregory (2000)'s two-layer model, it is represented via two simple ordinary differential equations with two-time scales. In Good et al. (2011,2012)'s step-response approach, ocean heat uptake is entirely implicit. In this proposal, our first objective will be to assess the degree of generality of each SCM by testing their relative performances on the same range of climate change scenarios, in order to identify which simplified representation of OHU performs better. Our second objective will be to investigate the link between physical and behavioural calibration, by implementing a physical calibration of MAGICC, and testing whether it improves or deteriorates its performances and why. This will provide key new insights on which aspects of ocean heat uptake are robust, and which are in need of further study, which will enhance the credibility of SCMs. The first and second objectives address Goal 2 of the Call. Our third objective will be to develop a versatile and flexible approach to constraining ocean heat uptake processes by using NEMO and its adjoint NEMOTAM, allowing for the optimal calibration of mixing parameters from both physical and behavioural constraints. This will endow the UK with a key capability for systematically re-calibrating ocean models by incorporating observational and theoretical advances on ocean mixing processes, and testing the implications for climate change projections. Moreover, the optimisation set-up for NEMO is potentially useful for many other types of studies in the future. This addresses Goal 1 of the Call. This will make a key contribution to the joint NERC-Met Office strategy for the development of UKESM1.