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

限制气候模型中的海洋边界层云特性：（关闭）

基本信息

批准号：
NE/W001713/1
负责人：
Daniel Partridge
金额：
$ 82.8万
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：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FW001713%2F1
关键词：
Constraining marine boundary layer cloud

项目摘要

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.

自工业化前以来，温室气体(GHG)和气溶胶(大气中悬浮的微小颗粒)的浓度都有了相当大的提高。虽然温室气体的人为排放使地球变暖，但气溶胶排放产生了一种显著的、但量化程度不高的冷却，抵消了温室气体造成的全球变暖的很大一部分。尽管进行了数十年的研究，但政府间气候变化评估委员会的报告继续强调气候敏感性和气溶胶-云-相互作用(ACI)是限制我们理解气候变化的两个关键不确定性。改进对温室气体排放的气候变化敏感性(每单位气候强迫的全球温度变化)的模型估计主要是由于模型间的差异，即气候模型如何表示低层云和气候系统之间随着气温升高而反馈的影响。低层海洋边界层(MBL)云是净辐射收支的关键调节器，我们用来提供未来气候情景估计的地球系统模型(ESM)的准确性严重阻碍了这些模型间差异的缩小。由于计算上的限制，这些模式不能明确地代表在自然界中形成MBL的小尺度大气过程的关键(精确到气溶胶的大小)。相反，与云形成相关的大气物理过程必须被参数化(复杂过程的简化形式)。对气候科学家来说，创建在广泛的时间/空间尺度上发生的复杂云过程的简化表示是一项具有挑战性的任务。这些参数中的不确定性影响到我们在ESM中准确表示MBL的能力。该项目的重点将是通过解决目前ESM对云滴形成(气溶胶和云之间的直接微物理联系)的参数化方面的不足，来提高对小规模MBL过程的理解。这将通过使用新的模拟框架来利用NASA地球冒险亚轨道任务名为Activate(西大西洋上空气溶胶云气象相互作用)的MBL云的详细飞行测量来实现。ACTIVATE代表了一项新的测量活动，其规模前所未有，因为它将涉及部署两架具有良好匹配地面速度的飞机。这一战略将允许将在MBL上空飞行的飞机的云的辐射特性与在MBL内进行现场气溶胶和云测量的飞机放在一起。这将提供一个独特的数据集，我们可以用它来约束流程规模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。为了实现这些目标，闭合将使用一个新的建模框架，在该框架中，一个计算速度很快的云模型被称为云包模型(CPM)。首次嵌入到ESM中。这些类型的云模型可以准确地模拟气溶胶粒子群体在上升的空气中成长为云滴的过程。这一嵌入式CPM框架将通过提供额外的用于评估的模型信息(例如液滴光谱)，关键地允许针对Activate的测量详细调查ESM中的ACI。此外，它将提供从离线模拟到嵌入ESM时在工艺尺度上获得的工艺知识的高效和无缝集成。这将被用来更好地理解ACI中涉及的关键小规模流程在MBL云表示中的作用。由此产生的对MBL云过程的理论描述的改进将减少未来气候情景估计中当前的不确定性。