ALPACA - Advancing the Long-range Prediction, Attribution, and forecast Calibration of the Amoc and its climate impacts

APACA - 推进 Amoc 及其气候影响的长期预测、归因和预报校准

• 批准号: NE/Y00504X/1
• 负责人: James Screen
• 金额: $ 13.27万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 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=NE%2FY00504X%2F1
• 关键词: ALPACA; Advancing; Long; range; Prediction

The Atlantic Meridional Overturning Circulation (AMOC) is a crucial component of the climate system due to its role in heat and salt transports, as well as its role in transporting and storing carbon. Variability in the strength of AMOC has been linked to important climate impacts, for instance, the number of Atlantic Hurricanes, anomalous Sahel precipitation, and European weather. Therefore, improved predictions of the AMOC would have important societal benefits.Despite its importance, the predictability of the AMOC remains relatively unexplored on timescales from one season to 10 years ahead, and many uncertainties persist in our understanding of AMOC variability. For example, we are unsure of the relative importance of different processes in driving AMOC variability on different timescales and latitudes, nor how predictable they are in state-of-the-art forecasting systems. Recent studies have provided considerable evidence that the atmospheric circulation in the North Atlantic is much more predictable than previously thought on these timescales. However, the predicted signals are far too small (the so-called signal-to-noise paradox) and predictions need to be calibrated to provide credible forecasts of society relevant variables, such as surface temperature. Given that atmospheric circulation is a key driver of AMOC, then it follows that AMOC predictions on these timescales may also suffer from similar signal-to-noise issues. Furthermore, predictions of AMOC, and its climate impact, could be improved by extending the published statistical calibrations to the ocean circulation.ALPACA will utilise AMOC observations (RAPID and OSNAP) and observation-based AMOC reconstructions to assess the quality of current AMOC forecasts in state-of-the-art seasonal and decadal prediction systems. Furthermore, we will evaluate the processes that contribute to skill and assess their consistency across models. We will also use new simulations to better understand the relative roles of different processes in driving observed variability on different timescales, and we will leverage new large ensemble simulations to quantify the role of external forcing in driving AMOC variability and change. Finally, by exploiting this new understanding, we will determine whether seasonal-to-decadal predictions of AMOC and its climate impacts can be improved through physically-consistent statistical calibrations that reduce the signal-to-noise errors in predictions. ALPACA is a collaboration between the National Centre for Atmospheric Science at the University of Reading, The National Oceanography Centre Southampton, The University of Exeter, and the Met Office Hadley Centre from the U.K., and The National Center for Atmospheric Research and the University of Miami, from the U.S, and the Barcelona Supercomputing Center from Spain.

大西洋子午翻转循环（AMOC）是气候系统的关键组成部分，因为它在热和盐传输中的作用及其在运输和储存碳中的作用。 AMOC强度的可变性与重要的气候影响有关，例如，大西洋飓风的数量，异常的萨赫勒降水和欧洲天气。因此，改进对AMOC的预测将具有重要的社会利益。尽管其重要性，但AMOC的可预测性在一个季节到未来10年的时间表上仍然相对尚未探索，并且许多不确定性仍然存在于我们对AMOC可变性的理解。例如，我们不确定不同过程在驱动不同时间尺度和纬度上的AMOC变异性方面的相对重要性，也不确定它们在最新的预测系统中的可预测性。最近的研究提供了大量证据，表明北大西洋的大气循环比以前在这些时间尺度上想象的要预测得多。但是，预测的信号太小（所谓的信号到噪声悖论），需要校准预测以提供对社会相关变量（例如表面温度）的可信预测。鉴于大气循环是AMOC的关键驱动力，因此可以遵循这些时间表上的AMOC预测也可能遭受类似的信噪比问题。此外，可以通过将已发表的统计校准扩展到海洋循环中来改善对AMOC的预测及其气候影响。Alpaca将利用AMOC观察结果（快速和OSNAP）和基于观察的AMOC重建来评估当前AMOC在正常的季节和十年级预测系统中当前AMOC的质量。此外，我们将评估有助于技能并评估其跨模型的一致性的过程。我们还将使用新的模拟更好地了解不同过程在不同时间尺度上观察到的可变性中的相对作用，我们将利用新的大型集合模拟来量化外部强迫在驱动AMOC变异性和变化中的作用。最后，通过利用这种新的理解，我们将通过物理上一致的统计校准来改善对AMOC及其气候影响的季节性到十年预测，从而减少预测中的信噪错误。羊驼是雷丁大学国家大气科学中心，南安普敦国家海洋学中心，埃克塞特大学的国家大气科学中心与英国的大都会办公室哈德利中心，美国大气研究中心和迈阿密大学，美国的美国国家中心，来自美国的巴塞罗那超级计算中心。