Climate model biases and projected changes in climate extremes

极端气候，如强风暴、洪水或干旱，对世界各地的社会和生态系统产生巨大影响。为了使社会适应不利的气候变化影响，需要对未来极端气候进行准确预测。我们对这些预测的信心因变量而异。虽然未来极端高温的加剧几乎是肯定的，但其他事件，如温带气旋（ETCs）的变化不太清楚。减少不确定性需要彻底了解导致(i)当前气候条件下极端气候偏差和（ii）未来极端气候变化的机制，以响应全球气候模式（GCMs）中预估的温室气体（GHG）浓度。由于极端事件的动态性质，这是具有挑战性的。在这种情况下经常使用的统计方法是有限的，因为它们不能完全证明因果关系，也不能解开动态相互作用的机制。我将开发一个替代框架，探索新的方法来理解导致GCM偏差和预测极端气候变化的物理机制。未来5年将通过实现四个短期目标来取得重要进展，即利用分段位涡度反演（PPVI）和简化的GCM来评估ETC偏差和中纬度地区和北极地区的预测。这是一种创新的方法，因为PPVI迄今主要用于研究再分析数据中的个别历史事件。因此，所提出的方法将为使用PPVI评估gcm树立先例，并以新的方式推进我们的理解，这是以前研究中使用的统计方法无法实现的。我的第一个目标是使用PPVI量化不同大气水平对gcm中ETC偏差和预估的贡献。结果将允许我解决我的第二个目标，即确定导致ETC偏差的机制，并评估具有小ETC偏差的gcm是否出于正确的原因而表现良好。我的第三个目标是确定导致ETC预测变化的主要机制，并评估这些变化在多大程度上受到ETC偏差和补偿过程的影响。我的第四个目标是在用简化的GCM进行的灵敏度实验中验证这些机制。新的框架将为改进GCM和减少GCM的不确定性提供指导，这将最终帮助社会在不断变化的气候条件下提高对极端气候的适应能力。申请的资金将用于支持两名博士生的研究，他们将参与一个培训项目，以支持他们从博士生过渡到该领域的生产性专业人员。作为导师，我的职责是指导hqp完成这一过程，并帮助他们开启成功的职业生涯。

Climate extremes such as intense storms, floods, or droughts have enormous impacts on societies and ecosystems around the world. To adapt societies to adverse climate change impacts, accurate projections of future climate extremes are needed. Our confidence in these projections strongly varies among variables. While a future intensification of hot temperature extremes is virtually certain, changes in other events such as extratropical cyclones (ETCs) are less clear. Reducing uncertainties requires a thorough understanding of the mechanisms that cause (i) biases in climate extremes under current climate conditions and (ii) future changes in climate extremes in response to projected greenhouse gas (GHG) concentrations in global climate models (GCMs). This is challenging due to the dynamical nature of extreme events. Statistical approaches often used in this context are limited as they cannot fully prove causality, nor disentangle dynamically interacting mechanisms. I will develop an alternative framework that explores new ways to understand the physical mechanisms that cause GCM biases and projected changes in climate extremes. Important advancements in the next 5 years will be made by achieving four short-term objectives that assess ETC biases and projections in the mid-latitudes and in the Arctic using piecewise potential vorticity inversion (PPVI) and a simplified GCM. This is an innovative approach, as PPVI has so far been used mainly to study individual historic events in reanalysis data. The proposed method will, therefore, set a precedent for using PPVI to evaluate GCMs and advance our understanding in new ways that cannot be achieved through statistical approaches used in previous studies. My first objective is to quantify the contributions from different atmospheric levels to ETC biases and projections in GCMs using PPVI. The results will allow me to address my second objective, which is to identify the mechanisms that cause ETC biases and to assess whether GCMs with small ETC biases perform well for the right reasons. My third objective is to then identify the dominant mechanisms that are responsible for projected changes in ETCs and to evaluate to what extent these changes are affected by ETC biases and compensating processes. My fourth objective is to verify these mechanisms in sensitivity experiments conducted with a simplified GCM. The new framework will provide guidance for improving GCMs and reducing GCM uncertainties, which will ultimately help societies in becoming more resilient to climate extremes under changing climate conditions. The requested funds will support the research of two Ph.D. students who will engage in a training program that will support their transition from being a Ph.D. student to becoming a productive professional in the field. My role as a mentor will be to guide the HQPs through this process and to assist them in launching a successful career.