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

了解并改进 AMOC 在年际至十年间气候预测中的预测

• 批准号: 2890063
• 金额: --
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2890063
• 关键词: Understanding; improving; AMOC; forecasts; inter

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.

大西洋子午倾覆循环（AMOC）是北大西洋中的关键海洋电流，在地球气候中起着重要作用。例如，与其他类似纬度的大陆相比，AMOC及其在运输热量中的作用是英国和欧洲温暖冬季的主要原因。 AMOC强度的变化也与区域温度的变化以及欧洲和非洲的降雨模式以及飓风等极端天气事件有关。古毒性证据还表明，在全球气候变化时期，AMOC过去一直在过去的快速，大型和持续的变化中。因此，从未来的年到十年来预测AMOC的能力将为社会带来许多好处。不幸的是，在许多十年预测系统中的AMOC预测受到表现不佳和身体不切实际的行为的阻碍，例如大而实质性的“漂移”。鉴于AMOC在运输热量和淡水中的重要作用，这些在AMOC中的漂移影响了海洋和大气中的其他变量。因此，这种差的性能限制了区域气候的可预测性，并且是提供有用的气候预测的严重障碍。改善AMOC的预测对于提高际气候预测的质量和信心至关重要。目前尚不清楚AMOC漂移的原因，并且改进预测将需要更好地理解控制AMOC的过程，以指导下一代气候预测系统的发展。 AMOC在际预测中的表示受到模型复制重要物理过程的能力的限制，例如驱动北大西洋中深浓水的空气相互作用，这是AMOC的关键组成部分。表面热量和淡水通量或温度，盐度和海冰的海面特性导致密集的水形成误差。海洋混合过程可以改变这些水质量，例如，在地下溢流​​或海洋涡流中 - 代表不佳，可能导致循环错误。因此，气海相互作用和内部海洋过程都会导致影响AMOC的地下海洋特性的分布。因此，该项目的总体目的是了解海洋模型中关键过程的表示如何干扰AMOC的成功复制和预测。学生将首先表征和理解AMOC在过去气候预测的多模型集合中的演变来做到这一点。通过详细的基于过程的分析，他们将探讨AMOC预测性能不佳的原因，并了解哪些海洋和大气过程是成功的多年预测的关键。特别是，他们将使用地表水质量转化诊断的新颖应用来解决空气相互作用或内部海洋过程中的错误是否在基于模型的预测中占主导地位。在探索了模型性能差的原因之后，学生将开发可在新的气候模型模拟中测试的特定假设。为此，学生将使用MET办公室耦合的气候模型设计和执行建模实验，以测试最先进的十年预测系统中AMOC预测的改进。然后，该项目的一个关键结果将是向大都会办公室的建议，这将导致改善未来几年的气候模型和预测。