Can air-sea coupling solve the signal-to-noise paradox in climate predictions?

这个项目解决了气候科学中的一个主要难题：所谓的“信噪悖论”。最近很明显，许多最先进的气候模式低估了大气环流对各种外部驱动因素的响应。这就造成了一种令人困惑的情况，即模型对现实世界的预测比要求模型预测自己（所谓的完美模型测试）更有技巧。这一问题在北大西洋尤为严重，对气候科学有着深远的影响，因为用于预测未来气候的模式存在偏差，会影响对这些模型的解释和用于气候服务的方式。尽管信噪矛盾有着广泛的影响，但它的起源仍然难以捉摸，目前也没有解决办法。这个项目将是第一个基于观测的研究，研究与风暴路径上的海气相互作用有关的信噪误差的一个潜在来源。该学生将使用EO数据、机器学习技术和最先进的气候模拟来揭示信号噪声悖论的原因。风暴路径是北大西洋天气和气候的一个关键特征，最近的证据表明，它可能是解释信号-噪声悖论的核心。发展中的温带气旋（ETCs）在大气中的热量和动量输送中起着重要作用。来自海洋的湿热通量为发展中的碳排放交易系统提供了重要的能量来源。该项目将解决这样一种假设，即信号噪声误差的来源在于模型中低估了海气耦合的强度，从而导致ETC开发中的误差，最终导致大气环流响应过弱。如果这一假设得到结果的支持，我们将致力于开发一种观测紧急约束，以减少未来北大西洋气候预测的不确定性。项目成果有望在理解信号噪声悖论的起源和潜在解决方案方面产生重大变化。目的和目标目的是验证信号噪声悖论是北大西洋空气-海洋相互作用模拟误差的结果这一假设。为实现这一目标，设定了以下目标：-利用观测数据识别ETC，并描述ETC生命周期不同阶段（发生、增强、裂解）的海气通量特征，重点关注墨西哥湾流锋面发展。-将观测到的ETCs内的海气能量交换与最先进的高分辨率气候模式模拟的海气能量交换进行比较-确定海气耦合的偏差与模式中信噪误差的大小之间是否存在关系，并使用观测到的EO量来约束模型的传播（紧急约束）。

This project tackles a major conundrum in climate science: the so-called "signal-to-noise paradox". It has recently become apparent that many state-of-the-art climate models underestimate the response of the atmospheric circulation to a broad range of external drivers1. This creates the perplexing situation where model predictions of the real world are more skilful than when the model is asked to predict itself (so-called perfect model test). This issue is particularly acute in the North Atlantic and has profound implications for climate science, since the models used to make projections of future climate contain biases that affect how they can be interpreted and used for climate services. Despite the wide-ranging implications of the signal-to-noise paradox, its origins remain elusive and there are currently no solutions for how to fix it. This project will be the first observation-based study of one potential source of the signal-to-noise error related to air-sea interactions over the storm tracks. The student will use EO data, machine learning techniques and state-of-the-art climate simulations to shed new light on the causes of the signal-to-noise paradox.The storm track is a key feature of North Atlantic weather and climate and recent evidence suggests it may be central to explaining the signal-to-noise paradox2,3. Developing extratropical cyclones (ETCs) play a major role in transporting heat and momentum in the atmosphere. Fluxes of moisture and heat from the ocean provide an important source of energy to developing ETCs.This project will address the hypothesis that the origin of the signal-to-noise error lies in the strength of air-sea coupling being underestimated in models, leading to errors in ETC development that ultimately lead to a too weak atmospheric circulation response. If this hypothesis is supported by the results, we will aim to develop an observational emergent constraint to reduce uncertainty in future projections of North Atlantic climate. The project outcomes are expected to lead to a step change in understanding the origins and potential solutions to the signal-to-noise paradox.Aims and objectives The aim is to test the hypothesis that the signal-to-noise paradox is a consequence of simulated errors in North Atlantic air-sea interactions. To achieve this aim, the following objectives are set: - Use EO data to identify ETCs and characterise the air-sea fluxes at different stages of ETC lifecycle (genesis, intensification, lysis), focusing on frontal development in the Gulf Stream. - Compare the observed air-sea energy exchanges within ETCs to those simulated in stateof-the-art high resolution climate models- Establish whether there is a relationship between biases in air-sea coupling and the magnitude of the signal-to-noise error in models and use EO observed quantities to constrain modelled spread (emergent constraint).