MOCCHA Analysis of Dynamic, Cloud, and Aerosol Processes

动态、云和气溶胶过程的 MOCCHA 分析

• 批准号: NE/R009686/1
• 负责人: Ian Brooks
• 金额: $ 82.73万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FR009686%2F1
• 关键词: MOCCHA; Analysis; Dynamic; Cloud; Aerosol

The climate of the Arctic is changing rapidly, warming at least twice as fast as the global average. While climate models are generally consistent with this amplified warming, they show much greater variability between model in the Arctic than elsewhere, and have conspicuously failed to reproduce some key features of observed climate change - notably the rapid reduction in summer sea ice extent. The greatest source of uncertainty in models of Arctic climate, indeed for climate in general, is clouds. Clouds are the dominant control of the surface energy budget through their impact on both solar and infra red radiation. The effect of clouds on the surface radiation budget is commonly expressed as the 'cloud radiative effect' (CRE): the difference between the radiation under clear skies and with clouds present. Results from the latest Climate Model Intercomparison Project (CMIP5) show that the annual mean CRE of all the models is biased by -10 W m-2 with a standard deviation across the models of similar magnitude. The bias for the summer months only is +20 W m-2. A bias of just 1 W m-2 over a year is sufficient to melt/freeze a 10 cm thick layer of sea ice; these model biases are thus highly significant. We aim to reduce the bias and uncertainty resulting from model summertime clouds in the Arctic, by improving understanding and parameterization of key processes affecting their formation, development, and dissipation. Arctic summer boundary-layer clouds are mixed-phase - containing both liquid water and ice crystals. This is a thermodynamically unstable non-equilibrium state because saturation water vapour pressure over ice is lower than that over water, thus ice crystals should grow at the expense of water droplets. The clouds are maintained in a quasi-equilbrium through a complex set of interactions between aerosol (on which droplets and ice crystals form), thermodynamic, microphysical, radiative, and turbulent mixing processes. All of these individual processes have significant uncertainties associate with them, and current model parameterizations have been developed almost entirely based on measurements in mid-latitude clouds where conditions are very different. We will use a combination of state-of-the-art measurements of cloud and boundary layer properties and processes, with detailed modelling studies using the Met Office Unified Model. The measurements utilise high resolution active remote sensing systems such as cloud radar and lidar, processed through the CLOUDNET algorithm to generate detail cloud property data. These are supplemented with in situ measurements of boundary layer structure and aerosol properties. Analysis of combined model and observational data will be used to identify key failings in model parameterizations, and new understanding of the physics that must be represented in the models. An iterative process of parameterization updates and testing against observations will be used to improve the model physics. The updates will then be tested in 20-year climate model runs using cases from the Atmospheric Model Intercomparison Project (AMIP) to evaluate their impact on climate projections. The Unified Model is chosen as an ideal tool because of its seamless philosophy, using the same model physics in both operational forecast and climate models. This allows direct testing against observational cases, and easy transfer of new model updates to the climate version. The final model updates will then be put forward to the Met Office for integration into the official model releases.

北极的气候正在迅速变化，变暖速度至少是全球平均水平的两倍。虽然气候模型总体上与这种加剧的变暖相一致，但它们在北极的模型之间显示出比其他地方更大的变异性，并且明显未能重现观测到的气候变化的一些关键特征——特别是夏季海冰范围的迅速减少。 北极气候模型（实际上对于一般气候而言）最大的不确定性来源是云。云通过影响太阳和红外辐射而成为地表能量预算的主要控制者。云对地表辐射预算的影响通常表示为“云辐射效应”（CRE）：晴朗天空下和有云时的辐射之间的差异。最新气候模型比对项目（CMIP5）的结果表明，所有模型的年平均 CRE 存在 -10 W m-2 的偏差，类似量级的模型之间存在标准差。仅夏季月份的偏差为+20 W m-2。一年内仅 1 W m-2 的偏差就足以融化/冻结 10 厘米厚的海冰层；因此，这些模型偏差非常显着。我们的目标是通过提高对影响北极夏季云形成、发展和消散的关键过程的理解和参数化来减少北极夏季云模型产生的偏差和不确定性。北极夏季边界层云是混合相的——既含有液态水又含有冰晶。这是一种热力学不稳定的非平衡状态，因为冰上的饱和水蒸气压低于水上的饱和水蒸气压，因此冰晶的生长应以水滴为代价。通过气溶胶（在其上形成液滴和冰晶）、热力学、微物理、辐射和湍流混合过程之间的一系列复杂的相互作用，云保持在准平衡状态。所有这些单独的过程都具有与其相关的显着的不确定性，并且当前的模型参数化几乎完全基于条件非常不同的中纬度云中的测量而开发。我们将结合使用最先进的云和边界层属性和过程测量，以及使用气象局统一模型进行详细的建模研究。测量利用云雷达和激光雷达等高分辨率主动遥感系统，通过 CLOUDNET 算法进行处理，生成详细的云属性数据。这些还辅以边界层结构和气溶胶特性的现场测量。对组合模型和观测数据的分析将用于识别模型参数化中的关键缺陷，以及对模型中必须表示的物理现象的新理解。参数化更新和观测测试的迭代过程将用于改进模型物理。然后，这些更新将使用大气模型比对项目 (AMIP) 的案例在 20 年气候模型运行中进行测试，以评估其对气候预测的影响。统一模型因其无缝理念而被选为理想工具，在业务预测和气候模型中使用相同的模型物理原理。这允许对观测案例进行直接测试，并轻松地将新模型更新转移到气候版本。最终的模型更新将提交给英国气象局，以整合到官方模型发布中。

项目成果

Highly active ice-nucleating particles at the summer North Pole

夏季北极高度活跃的冰核颗粒

• DOI: http://dx.10.1002/essoar.10508073.1
• 发表时间: 2021
• 作者: Porter G

Resolving the size of ice-nucleating particles with a balloon deployable aerosol sampler: the SHARK

使用气球可展开气溶胶采样器解析冰核颗粒的大小：SHARK

• DOI: http://dx.10.5194/amt-13-2905-2020
• 发表时间: 2020
• 期刊: Atmospheric Measurement Techniques
• 影响因子: 3.8
• 作者: Porter G

Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System

评估使用统一模型和综合预报系统建模的北极云

• DOI: http://dx.10.5194/acp-23-4819-2023
• 发表时间: 2023
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: McCusker G

Highly Active Ice-Nucleating Particles at the Summer North Pole.

夏季北极高度活跃的冰核粒子。

• DOI: http://dx.10.1029/2021jd036059
• 发表时间: 2022
• 期刊: JGR
• 作者: Porter GCE

The Impact of Radiosounding Observations on Numerical Weather Prediction Analyses in the Arctic

无线电探测观测对北极数值天气预报分析的影响

• DOI: http://dx.10.1029/2019gl083332
• 发表时间: 2019
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Naakka T