Resolving climate sensitivity associated with shallow mixed phase cloud in the oceanic mid- to high-latitudes (M-Phase)

含有冰和水混合物的云(混合相云)很可能会随着气候变化而变化。预计气候变暖将导致这些云层中的水量增加，冰量减少。由于水滴比冰晶反射更多的太阳辐射(导致更少的降水)，云层预计会变得更亮，从而对中高纬度的气候系统造成降温效应(或负反馈)。云相反馈的大小非常不确定。如果反馈很强，那么未来全球气温的上升将会更慢，但如果反馈很弱，那么气温将上升得更快。最近有研究表明，调整气候模型中的冰水比例以与卫星观测相匹配，可以将地球的平衡气候敏感度(随着二氧化碳增加一倍而变暖)增加1.5度；因此，地球变暖的速度可能比想象的快。反馈过程进一步复杂化，因为触发冰产生的特殊粒子-冰核粒子(INP)在气候变暖的世界中可能更加丰富，因为冰川山谷等INP来源将被冰雪覆盖的时间更短。INP浓度的增加将意味着云中有更多的冰，并导致积极的反馈。这两个相反的反馈有助于我们所说的云相反馈。这一提议将提高我们对云中冰粒如何形成以及这如何影响云相反馈的理解。冰的形成是控制这种反馈的关键过程。这个问题可以分为两个部分：首先，我们将解决与将初始冰形成与云的反射率联系起来的过程链以及反射率将如何随着变暖而变化的公开问题。我们已经设计了一项针对与云反馈问题最相关的条件的飞机战役：对温度变化最敏感的中等冷云，以及高INP浓度可能影响北大西洋大片地区的情况。这些冷空气暴发云为研究对云反馈起重要作用的浅层混合相云的形成和演变提供了理想的气象条件。其次，我们将解决对中高纬度INP的来源、分布和季节周期缺乏了解的问题。我们的战略是使用测量来确定INP的来源，并利用这些信息将中纬度到高纬度的来源纳入我们的INP全球模型。我们将通过全年开展新的长期测量，并在北极重点源区进行船载测量。我们已经建立了一个庞大的合作伙伴网络，他们将贡献北部和南部中高纬度地区的INP数据，这将使我们能够将我们的研究扩展到全球。关于云过程和INP的新知识将用于改善混合相云在气象局天气和气候模式中的表现。该模式将以非常高的空间分辨率运行，以便能够模拟冷空气爆发中的单个云。该模型将通过与我们的测量以及与卫星观测进行比较来进行测试和改进。然后，我们将把这项研究扩展到南大洋和大西洋对岸的对比案例。我们预计，新的知识将极大地改善这些气候关键云的表现。然后，我们将对选定的案例进行敏感性分析，以测试这些云系统将如何应对气候变化。最后，我们将利用新知识制定一项计划，以改进全球气候模型中混合相云的处理方式，以便在后续项目中开展这项工作。

Clouds containing a mixture of ice and water (mixed-phase clouds) are likely to change in response to climate change. It is expected that warming will cause an increase in the amount of water and a decrease in the amount of ice in these clouds. Because water droplets reflect more solar radiation than ice crystals (and cause less precipitation), the clouds are expected to become brighter, thereby causing a cooling effect (or negative feedback) on the climate system at mid- to high-latitudes. The magnitude of the cloud-phase feedback is very uncertain. If the feedback is strong then global temperatures will increase more slowly in future, but if it is weak then temperatures will increase more rapidly. It was recently shown that adjusting the ratio of ice and water in a climate model to match satellite observations could increase Earth's equilibrium climate sensitivity (warming with a doubling of CO2) by 1.5 degrees; hence, Earth may warm faster than thought. The feedback process is further complicated by the fact that the special particles, ice nucleating particles (INPs), which trigger ice production, may be more abundant in a warmer world where INP sources, such as glacial valleys, will be covered in ice and snow for less time. Increased INP concentrations would mean more ice in clouds and lead to a positive feedback. These two opposing feedbacks contribute to what we refer to as the cloud-phase feedback.This proposal will improve our understanding of how ice particles form in clouds and how this affects the cloud-phase feedback. Ice formation is the key process that controls this feedback. The problem can be broken down into two parts: First, we will address the open questions related to the chain of processes that link initial ice formation to the reflectivity of the clouds and how the reflectivity will change with warming. We have designed an aircraft campaign targeted at conditions of most relevance to the cloud feedback problem: moderately cold clouds that will be most sensitive to changes in temperature, and where high INP concentrations are likely to influence large regions of the N Atlantic. These cold-air outbreaks clouds provide an ideal meteorological situation for studying the formation and evolution of the kinds of shallow mixed-phase clouds which are important for cloud feedbacks.Second, we will address the paucity of knowledge on the sources, distribution and seasonal cycles of INPs at the mid- to high-latitudes. Our strategy is to use measurements to identify sources of INPs and use this information to inform the inclusion of mid- to high-latitude sources in our global model of INPs. We will perform new long-term measurements through a whole year and ship borne measurements through the key source regions in the Arctic. We have built a substantial network of Partners who will contribute INP data across the northern and southern mid- to high-latitudes which will allow us to expand our study to the globe.The new knowledge on cloud processes and INP will be used to improve the representation of mixed-phase clouds in the Met Office weather and climate model. The model will be run at very high spatial resolution so that the individual clouds in the cold-air outbreaks can be simulated. The model will be tested and improved by comparing it to our measurements as well as against satellite observations. We will then extend this study to contrasting cases from the Southern Ocean and the other side of the Atlantic. We anticipate the new knowledge will lead to a greatly improved representation of these climatically critical clouds. We will then perform a sensitivity analysis on selected cases in order to test how these cloud systems will respond to climate change. Finally, we will use the new knowledge to develop a plan for improving how mixed-phase clouds are treated in global climate models so that this work can be carried out in a follow-on project.