The physics of cloud and water vapour feedbacks in perturbed-physics ensembles

该项目将两个强大而互补的工具应用于最先进的气候模型，这两个工具是可以通过分布式计算和详细的面向物理的观测验证来执行的非常大的扰动物理集合，以提供对大气反馈的更定量的理解，这些反馈决定了气候敏感性，即对温室气体增加的变暖反应。利用哈德利中心和气候预测网(Cpdn)以前进行的扰动物理集合的经验，我们将确定最新的哈德利中心AGCM(大气环流模式)HadGAM的一系列物理扰动，以及一套旨在测试模拟的广泛方面的紧凑诊断，重点是云和水汽反馈中涉及的物理过程。与早期的实验不同，微扰将包括参数变化和结构修改。我们将把带有这些扰动和诊断的AGCM移植到BOINC(伯克利网络计算开放基础设施)公共领域分布式计算框架。个人计算处理器技术的发展意味着所有计算都将以模型的原始(位)精度执行，从而简化了与超级计算结果的比较。来自普通公众的志愿者将在家用计算机上进行数千个由近期(卫星时代)观测到的海面温度(SST)驱动的短期扰动物理模拟，并由cpdn上传和存档输出。嵌入到分布式计算包中的软件将允许与卫星数据集进行准确比较，而不需要恢复令人望而却步的大型四维数据集。我们将与哈德利中心和NASA兰利的非NERC资助的工作人员一起，针对广泛的卫星和其他诊断验证这些模型，并分析不同的参数选择及其相互作用对模拟质量的影响，特别是云、水蒸气和辐射的影响。这些运行的持续时间相对较短，这意味着我们将能够使用连续运行来优化大气能量预算，例如，在有希望的模型版本中。晴朗和多云的大气顶通量对SST年际变化的响应将被用来确定一组规模小得多的模式，这些模式全面验证得很好，并可能显示广泛的水蒸气和云反馈。哈德利中心随后将使用这些模型运行理想化的气候变化模拟，以确定这些反馈的实际强度。这将提供对气候敏感性范围的前所未有的详细和定量的了解，这与用最先进的AGCM解释的观测结果一致。它还将首次提供最先进的地球系统模型的大气成分的可能版本的集合，而不是传统的单一最佳猜测版本。这将大大提高未来地球系统研究中模型误差的客观性和处理方法。

This project applies two powerful and complementary tools, the very large perturbed-physics ensembles that can be performed by distributed computing and detailed physically-oriented observational validation, to a state-of-the-art climate model to provide a more quantitative understanding of the atmospheric feedbacks that determine the climate sensitivity, or warming response to increasing greenhouse gases. Using the experience of previous perturbed-physics ensembles performed by the Hadley Centre and climateprediction.net (cpdn), we will identify a range of physical perturbations to the latest Hadley Centre AGCM (atmospheric general circulation model), HadGAM, and a compact set of diagnostics aimed at testing a wide range of aspects of the simulation, with emphasis on the physical processes involved in the cloud and water vapour feedbacks. Unlike earlier experiments, perturbations will encompass both parameter variations and structural modifications. We will port the AGCM, with these perturbations and diagnostics, to the BOINC (Berkeley Open Infrastructure for Network Computing) public-domain distributed computing framework. Developments in personal computing processor technology mean that all computations will be performed in the model's native (64-bit) precision, simplifying comparison with supercomputing results. Thousands of short perturbed-physics simulations driven with observed sea surface temperatures (SST) for recent (satellite-era) periods will be performed by volunteers from the general public on home computers, and output uploaded and archived by cpdn. Software embedded into the distributed computing package will allow accurate comparison with satellite datasets without the requirement of recovering prohibitively large four-dimensional datasets. In conjunction with non-NERC-funded workers at the Hadley Centre and NASA Langley, we will validate these models against a wide range of satellite and other diagnostics, and analyze the effect of different parametrization choices and their interactions on the quality of the simulation, particularly of cloud, water vapour and radiation. The relatively short duration of these runs means that we will be able to use successive runs to optimise, for example, the atmospheric energy budget in promising model versions. The response of clear- and cloudy-sky top-of-atmosphere fluxes to interannual SST variations will be used to identify a much smaller set of models that validate well across the board and are likely to display a wide range of water vapour and cloud feedbacks. The Hadley Centre will then run idealized climate change simulations with these models to establish the actual strength of these feedbacks. This will provide an unprecedentedly detailed and quantitative understanding of the range of climate sensitivities that are consistent with observations interpreted with a state-of-the-art AGCM. It will also provide for the first time an ensemble of possible versions of the atmospheric component of a state-of-the-art Earth System Model rather than the traditional single best-guess version. This will significantly improve the objectivity of, and treatment of model error in, future Earth System research.