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

含有冰和水的混合物的云（混合相云）可能会随着气候变化而变化。预计变暖将导致这些云中的水量增加和冰量减少。由于水滴比冰晶反射更多的太阳辐射（并导致更少的降水），预计云层会变得更亮，从而对中高纬度的气候系统产生冷却效应（或负反馈）。云相反馈的大小是非常不确定的。如果反馈很强，那么未来全球气温将上升得更慢，但如果反馈很弱，那么气温将上升得更快。最近的研究表明，调整气候模型中冰和水的比例以匹配卫星观测结果可以使地球的平衡气候敏感性（二氧化碳加倍变暖）增加1.5度;因此，地球可能比想象的更快变暖。反馈过程进一步复杂化的事实是，特殊的颗粒，冰成核颗粒（INPs），触发冰的生产，可能是更丰富的在一个温暖的世界，INP源，如冰川山谷，将被冰雪覆盖的时间更短。INP浓度的增加意味着云中有更多的冰，并导致正反馈。这两个相反的反馈有助于我们所说的云相反馈。这个建议将提高我们对冰粒子如何在云中形成以及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，我们将解决与初始冰形成与云的反射率之间的联系以及反射率如何随着变暖而变化的过程链相关的开放性问题。我们已经设计了一个飞机运动针对的条件最相关的云反馈问题：适度冷的云，将是最敏感的温度变化，高INP浓度可能会影响大面积的北大西洋。这些冷空气爆发云提供了一个理想的气象条件，研究的形成和演变的各种浅混合相云，这是重要的云feedbacks.Second，我们将解决知识的缺乏在中高纬地区的INPs的来源，分布和季节循环。我们的策略是使用测量来识别INPs的来源，并使用这些信息来通知我们的全球INPs模型中的中高纬度来源。我们将进行新的长期测量，为期一整年，并在北极的主要源区进行船载测量。我们已经建立了一个庞大的合作伙伴网络，他们将提供北方和南方中高纬度地区的INP数据，这将使我们能够将研究扩展到地球仪。有关云过程和INP的新知识将用于改善气象局天气和气候模式中混合相云的代表性。该模型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结果以及卫星观测结果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另一边的对比案例。我们预计新的知识将导致这些气候关键云的代表性大大改善。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，我们将利用新的知识来制定一个计划，以改善如何在全球气候模型中处理混合相云，以便这项工作可以在后续项目中进行。

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.