Constraining marine boundary layer cloud properties in climate models: (CLOSURE)

自前工业化时代以来，温室气体（GHG）和气溶胶（悬浮在大气中的微小颗粒）的浓度都大幅增加。虽然人为排放的温室气体使地球变暖，但气溶胶排放发挥了重要的、但量化不足的冷却作用，抵消了温室气体造成的很大一部分全球变暖。尽管经过数十年的研究，政府间气候变化专门委员会评估报告继续强调气候敏感性和气溶胶-云相互作用（ACI）是限制我们对气候变化理解的两个关键不确定性。模式对气候变化敏感性（每单位气候强迫的全球温度变化）对温室气体排放的估计的改进主要是由模式间差异驱动的，即气候模式如何表示随着温度升高低层云和气候系统之间反馈的影响。我们用来估计未来气候情景的地球系统模式（esm）中，低水平海洋边界层（MBL）云是净辐射收支的关键调度器，而这种云的准确性严重阻碍了减少模式间差异。由于计算的限制，这些esm不能明确地表示在自然界中发生的尺度（小到气溶胶的大小）上形成MBL的小规模大气过程的关键。相反，与云形成有关的大气物理过程必须被参数化（复杂过程的简化形式）。对于气候科学家来说，在大范围的时间/空间尺度上创建复杂云过程的简化表示是一项具有挑战性的任务。这些参数化中的不确定性会影响我们在esm中准确表示MBL的能力。该项目的重点将是通过解决当前ESM参数化云滴形成（气溶胶和云之间的直接微物理联系）方面的不足，提高对小规模MBL过程的理解。这将通过使用新的建模框架来实现，利用NASA地球冒险亚轨道任务ACTIVATE（西大西洋气溶胶云气象相互作用实验）对MBL云的详细飞行测量。ACTIVATE代表了一项前所未有的新型测量活动，用于了解MBL云，因为它将涉及部署两架地面速度匹配良好的飞机。这一策略将允许在MBL上空飞行的飞机与在MBL内进行现场气溶胶和云测量的飞机同时定位云的辐射特性。这将提供一个独特的数据集，我们可以用它来约束过程尺度的云模型和大规模的esm，以改进当前的小规模ACI参数化，并随后提高MBL云在esm中表示的准确性。为了达到这些目标，CLOSURE将使用一个新的建模框架，在这个框架中，计算速度很快的云模型被称为云包模型（cloud package model， CPM）。首次被纳入了欧洲稳定机制。这些类型的云模式可以准确地模拟气溶胶粒子在上升的空气中变成云滴的过程。这种嵌入式CPM框架将通过提供额外的模型信息（例如液滴光谱）来评估esm中的ACI，从而对ACTIVATE的测量结果进行详细的调查。此外，当嵌入到ESM中时，它将提供从离线模拟到大规模过程规模的过程知识的高效无缝集成。这将用于更好地理解ACI中涉及的用于MBL云表示的关键小规模过程的作用。由此产生的MBL云过程的改进理论描述将减少未来气候情景估计中当前的不确定性。

Concentrations of both greenhouse gases (GHG) and aerosols (tiny particles suspended in the atmosphere) have increased considerably since pre-industrial time. Whilst anthropogenic emissions of GHG warm the planet, aerosol emissions exert a significant, yet poorly quantified cooling that acts to offset a significant fraction of global warming from GHG. Despite decades of research, the Intergovernmental Panel on Climate Change Assessment Report continues to highlight the climate sensitivity and aerosol-cloud-interactions (ACI) as the two key uncertainties limiting our understanding of climate change. Improving model estimates of climate change sensitivity (global temperature change per unit climate forcing) to greenhouse gas emissions is primarily driven by inter-model differences how climate models represent the impacts of feedbacks between low-level clouds and the climate system as temperature increases. Reducing these inter-model differences is severely hampered by the accuracy by which low level marine boundary layer (MBL) clouds, key modulators of the net radiation budget, are represented in the Earth System Models (ESMs) we use to provide estimates of future climate scenarios. Due to computational limitations these ESMs cannot explicitly represent small-scale atmospheric processes key for the formation of MBL at the scale at which they occur in nature (down to the size of aerosols). Instead, atmospheric physical processes related to cloud formation have to be parameterised (a simplified form of the complex process). Creating simplified representations of complex cloud processes that occur over a wide range of temporal/spatial scales is a challenging undertaking for climate scientists. Uncertainties in these parameterisations propagates through to our ability to accurately represent MBL in ESMs. The focus of this project will be to improve understanding of small-scale MBL processes by addressing current deficiencies in ESM parameterisations of cloud droplet formation, the direct microphysical link between aerosols and clouds. This will be achieved by using new modelling frameworks to capitalise on detailed flight measurements of MBL clouds from the NASA Earth Venture Suborbital mission called ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). ACTIVATE represents a novel measurement campaign of unprecedented scope for understanding MBL clouds as it will involve the deployment of two aircraft with well-matched groundspeeds. This strategy will allow for co-location of radiative properties of clouds from an aircraft flying above the MBL with an aircraft performing in-situ aerosol and cloud measurements within the MBL. This will provide a unique dataset with which we can constrain both process-scale cloud models, and large-scale ESMs to improve current small-scale ACI parameterisations, and subsequently the accuracy by which MBL clouds are represented in ESMs. To reach these goals the CLOSURE will use a new modelling framework in which a computationally fast cloud model known as a cloud parcel model (CPM). has been embedded in an ESM for the first time. These types of cloud models can accurately simulate the growth of a population of aerosol particles into cloud droplets in an ascending parcel of air. This embedded CPM framework will crucially allow for a detailed investigation of ACI in ESMs against measurements from ACTIVATE by providing additional model information for evaluation, e.g. droplet spectra. Furthermore, it will provide an efficient and seamless integration of process knowledge gained at the process scale from offline simulation to the large-scale when embedded in the ESM. This will be used to provide better understanding on the role of key small-scale processes involved in ACI for the representation of MBL clouds. The resulting improved theoretical descriptions of MBL cloud processes will reduce current uncertainties in future climate scenarios estimates.