Understanding and improving AMOC forecasts in inter-annual to decadal climate predictions

大西洋子午线翻转环流(AMOC)是北大西洋的一种重要洋流，对地球气候起着重要作用。例如，与类似纬度的其他大陆相比，AMOC及其在热量传输中的作用是英国和欧洲冬季温暖的主要原因。AMOC强度的变化还与欧洲和非洲地区气温的变化和降雨模式的变化以及飓风等极端天气事件有关。古替代证据还表明，在过去的全球气候变化期间，AMOC经历了快速、大规模和持续的变化。因此，能够预测未来几年到几十年的AMOC将为社会带来许多好处。不幸的是，在许多十年制预测系统中，AMOC的预测受到了糟糕的性能和物理上不切实际的行为的阻碍，例如大而大的“漂移”。鉴于AMOC在输送热量和淡水方面的重要作用，AMOC中的这些漂移会影响海洋和大气中的其他变量。因此，这种糟糕的表现限制了区域气候的可预测性，并严重阻碍了提供有用的气候预报。改进AMOC的预测对于提高十年气候预测的质量和信心至关重要。AMOC漂移的原因目前尚不清楚，改进预测将需要更好地了解控制AMOC的过程，以指导下一代气候预测系统的开发。AMOC在十年预报中的表现受到模式再现重要物理过程的能力的限制，例如推动北大西洋深层致密水形成的气-海相互作用，这是AMOC的一个关键组成部分。表面热量和淡水通量的偏差，或温度、盐度和海冰的海面特性的偏差会导致稠水形成的错误。改变这些水团的海洋混合过程--例如，在地下溢流或海洋漩涡中--也没有得到很好的描述，可能会导致环流错误。因此，海-气相互作用和内部海洋过程都可能导致影响AMOC的次表层海洋性质的分布出现重大误差。因此，该项目的总体目标是了解海洋模式中关键过程的表示如何干扰AMOC的成功再现和预测。学生将通过首先描述和理解过去气候预测的多模型集合中AMOC的演变来做到这一点。通过详细的基于过程的分析，他们将探索AMOC预报表现不佳的原因，并了解哪些海洋和大气过程是成功的多年预报的关键。特别是，他们将使用一种新的地表水质量转换诊断应用来解决在基于模型的预测中，海-气相互作用或内部海洋过程中的误差是主导AMOC漂移的问题。在探索了模型表现不佳的原因后，学生将开发可以在新的气候模型模拟中进行测试的具体假设。为此，学生将使用Met Office耦合气候模式设计和执行模拟实验，以测试在最先进的十年预测系统中AMOC预测的改进。该项目的一个关键成果将是向英国气象局提出建议，这将导致对未来几年气候的改进模型和预测。

The Atlantic Meridional Overturning circulation (AMOC) is a key ocean current in the North Atlantic which plays an important role in Earth's climate. For example, the AMOC - and its role in transporting heat - is the main cause of warm winters in the UK and Europe compared to other continents at similar latitudes. Changes in the strength of the AMOC have also been linked with changes in regional temperatures and shifting rainfall patterns over Europe and Africa, as well as extreme weather events such as hurricanes. Paleo-proxy evidence also suggests that the AMOC has been through rapid, large, and persistent changes in the past during periods of global climate change. Therefore, the ability to predict the AMOC from years-to-decades ahead would have many benefits for society. Unfortunately, AMOC predictions in many decadal prediction systems are hampered by poor performance and physically unrealistic behaviour such as large and substantial "drifts". Given the AMOC's important role in transporting heat and freshwater, these drifts in AMOC impact other variables in the ocean and atmosphere. Therefore, this poor performance is limiting predictability of regional climate and are a serious barrier to providing useful climate forecasts. Improving the predictions of the AMOC is crucial to improve the quality of, and the confidence in, decadal climate predictions. The causes of the AMOC drift are currently not known and improving the predictions will require better understanding of the processes controlling the AMOC to guide development of the next generation of climate prediction systems. The representation of the AMOC in decadal predictions is limited by the ability of models to reproduce important physical processes such as air-sea interactions driving the formation of deep dense water in the North Atlantic, which is a key component of the AMOC. Biases in surface heat and freshwater fluxes or sea surface properties of temperature, salinity, and sea ice lead to errors in dense water formation. Ocean mixing processes that modify these water masses - for example, at subsurface overflows or within ocean eddies - are also poorly represented and can lead to errors in circulation. Thus, both air-sea interactions and internal ocean processes can lead to significant errors in the distribution of sub-surface ocean properties that impact the AMOC. Therefore, the overall aim of this project is to understand how the representation of key processes in ocean models can interfere with successful reproduction and prediction of the AMOC. The student will do this by first characterizing and understanding the evolution of the AMOC in a multi-model ensemble of predictions of past climate. Through detailed process-based analysis they will explore the reasons for poor performance of AMOC predictions and understand which oceanic and atmospheric processes are key for a successful multi-annual prediction. In particular, they will use a novel application of surface water mass transformation diagnostics to address the question of whether errors in air-sea interactions or internal ocean processes dominate the drifts in AMOC in model-based predictions. After exploring the causes of poor model performance, the student will develop specific hypotheses that can be tested in new climate model simulations. To that end, the student will design and perform modelling experiments with the Met Office coupled climate model to test for improvements in AMOC prediction in a state-of-the-art Decadal Prediction System. One key outcome of the project will then be recommendations to the Met Office, which will lead to improved models and predictions of climate in the years ahead.