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“信噪比悖论”。最近很明显，许多最先进的气候模型低估了大气环流对广泛的外部驱动因素的反应。这就造成了一种令人困惑的情况，即模型对真实的世界的预测比模型被要求预测自己时更熟练（所谓的完美模型检验）。这一问题在北大西洋尤为严重，并对气候科学产生深远影响，因为用于预测未来气候的模型含有偏差，影响到如何解释这些模型并将其用于气候服务。尽管信号噪声悖论的广泛影响，它的起源仍然难以捉摸，目前没有解决方案，如何解决它。该项目将是第一个基于观测的研究的一个潜在来源的信号噪声误差有关的空气-海洋相互作用的风暴路径。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噪比悖论的原因。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噪比悖论的核心2，3。发展中的温带气旋（ETC）在大气中输送热量和动量方面起着重要作用。来自海洋的水汽和热量通量为发展ETC提供了重要的能量来源。本项目将解决以下假设，即信噪比误差的来源在于模式中低估了海气耦合的强度，导致ETC发展中的误差，最终导致大气环流响应太弱。如果这一假设得到结果的支持，我们的目标是开发一个观测紧急约束，以减少未来北大西洋气候预测的不确定性。该项目的成果预计将导致一个步骤的变化，了解的起源和潜在的解决方案的信号-噪音paradoxy.Aims和objectives的目的是测试的假设，即信号-噪音的矛盾是一个后果，在北大西洋的空气-海洋相互作用的模拟误差。为了实现这一目标，设定了以下目标：-使用EO数据来识别ETC，并在ETC生命周期的不同阶段（成因，强化，溶解），侧重于墨西哥湾流的锋面发展的海气通量。- 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中模拟的海气能量交换进行比较-确定海气耦合偏差与模型中信噪比误差大小之间是否存在关系，并使用EO观测量来约束模拟的扩散（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).