Fundamental limits and trade-offs of stratospheric aerosol geoengineering

减少二氧化碳和其他温室气体(GHG)的净排放量对应对气候变化至关重要，但可能还不够快，不足以避免重大的气候影响。平流层气溶胶地球工程的模型预测表明，它可以减少一些气候影响，因此有可能成为全面气候变化战略的一个额外内容。然而，目前的知识不足以支持明智的决策。评估地球工程学的一个关键问题是，在地球工程学如何管理温室气体增加带来的气候反应方面，基本的限制或权衡是什么？也就是说，地球工程能做什么，不能做什么？在最近研究的基础上，该项目将解决这一基本问题。这项研究的基本动机是了解减少未来气候影响的潜在选择。需要更好的信息来支持未来有关部署的决策，并支持制定这些决策所需的治理能力的发展。这项研究将能够比以前更全面地了解部署地球工程的影响，通过生成模拟来捕获更全面的部署选项，而不是只有一两个；此外还将评估不同目标可以或不能同时实现的程度。该项目将生成一组气候模型模拟，每个模拟都对相对于其他气候目标的优先顺序做出不同的选择，并利用这一点来确定潜在的权衡(互斥的目标集)和边界(哪些目标可以实现，哪些目标不能实现)。在整个过程中，研究小组将与政策和治理专家接触，讨论可能激励不同行为者的气候目标的潜在范围，以及已确定的权衡对治理的影响。从来没有探索过各种可能的战略，部分原因是对可用自由度空间--主要是纬度和气溶胶注入季节--的优化由于不确定性和非线性相互作用(来自微物理学和气溶胶加热引起的平流层环流变化)而变得复杂，并因组合计算复杂性而变得复杂。为了应对这些挑战，研究团队将结合三项创新。首先，这项研究的关键推动因素是对设计空间的“大小”进行初步评估；有多少有用的独立自由度？这就减少了组合问题。其次，可以通过将了解平流层气溶胶光学厚度的空间和季节分布所需的模拟与评估对特定气溶胶分布的气候响应所需的模拟分开来减少计算负担，平流层光学厚度可能很短，但需要一个完整的平流层模型，后者需要多十年的模拟，但不需要准确的平流层。第三，可以通过调整注射速率的反馈来管理非线性和不确定性；这使得能够基于指定的目标而不是指定的注射速率来比较模拟。研究团队将设计一套模拟，分别满足不同的目标，并共同跨越可能的结果空间。因此，评估和可视化权衡的关键工具是通过帕累托最优曲面：作为优化标准的函数，战略及其响应是如何变化的。尽管模拟将侧重于理解物理科学的权衡取舍，但社会和治理维度在理解哪些目标可能是最重要的目标或哪些战略在政治上根本不可行方面发挥了关键作用，从而以气候模型未揭示的方式限制了空间。因此，研究团队将始终与治理专家互动，以确保研究为政策提供信息。这个奖项反映了NSF的法定使命，通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为是值得支持的。

Reducing net emissions of CO2 and other greenhouse gas (GHG) is essential to any response to climate change, but may not occur fast enough to avoid significant climate impacts. Model projections of stratospheric aerosol geoengineering suggest that it could reduce some climate impacts, and thus might potentially become an additional element of a comprehensive climate change strategy. However, current knowledge is insufficient to support informed decisions. A critical question in evaluating geoengineering is what are the fundamental limits or trade-offs in how well geoengineering can manage the climate response from increased GHG? That is, what can geoengineering do, and what can it not do? Building on recent research, this project will address this essential question. The fundamental motivation for this research is to understand a potential option to reduce future climate impacts. Better information is needed both to support future decisions around deployment, and support the development of governance capacity that will be needed to make these decisions. This research will enable a more complete view of the impacts of deploying geoengineering than has previously been possible, by generating simulations that capture a more comprehensive set of deployment options rather than just one or two; and furthermore will assess the extent to which different objectives can or cannot be simultaneously met.This project will generate a set of climate model simulations that each make different choices for which climate goals to prioritize relative to others, and use this to identify potential tradeoffs (sets of objectives that are mutually exclusive) and boundaries (which objectives are achievable and which are not). Throughout this process, the research team will engage policy and governance experts, regarding the potential range of climate goals that might motivate different actors, and on the governance implications of identified trade-offs. The full range of possible strategies has never been explored, in part because optimization over the space of available degrees of freedom – primarily latitudes and seasons of aerosol injection – is complicated by uncertainty and nonlinear interactions (from both microphysics and aerosol-heating-induced changes in stratospheric circulation), and compounded by combinatorial computational complexity. To address these challenges, the research team will combine three innovations. First, the key enabler to this research is an initial assessment on the “size” of the design space; how many usefully-independent degrees of freedom are there? This reduces the combinatorial problem. Second, the computational burden can be reduced by separating the simulations needed to understand the spatial- and seasonal- distribution of stratospheric aerosol optical depth (AOD), which can be short but require a complete stratosphere model, from those needed to assess the climate response to a specified aerosol distribution, which require multi-decadal simulations but not an accurate stratosphere. And third, nonlinearities and uncertainty can be managed through feedback that adjusts injection rates; this enables comparing simulations based on specified objectives rather than specified injection rates. The research team will design a suite of simulations that individually meet different objectives and collectively span the space of possible outcomes. From this, the key tool in evaluating and visualizing trade-offs is through Pareto-optimal surfaces: how do strategies and their responses change as a function of the optimization criteria. Although the simulations will be focused on understanding physical science tradeoffs, social and governance dimensions play a critical role in understanding which objectives may be most important to achieve or which strategies are simply politically infeasible, thus limiting the space in ways not revealed by climate modeling. Therefore, the research team will interface with governance experts throughout to ensure research informs policy. Simulations will also be made available to the wider international community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.