Scenarios for modeling solar radiation modification.
Scenarios for modeling solar radiation modification.
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DOI：
10.1073/pnas.2202230119
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发表时间：
2022-08-16
影响因子：
11.1
通讯作者：
中科院分区：
文献类型：
--
作者：
太阳辐射调节（SRM；也称为太阳能地球工程）的好处和风险需要结合气候变化的风险进行评估，并且取决于冷却量等选择。如今的一个挑战是当前 SRM 模拟中使用的场景存在一定程度的任意性，这使得 SRM 和非 SRM 案例之间以及不同 SRM 场景之间的比较变得困难。我们通过以下方式解决这一差距：1）定义一组可能的场景，捕获一系列选择和不确定性；2）提供对这些场景的模拟，可广泛用于比较影响评估。这是政府间气候变化专门委员会等任何国际评估的重要前提。未来要做出有关太阳辐射调节（SRM；也称为太阳地球工程）的明智决策（例如通过反射阳光来冷却气候的平流层气溶胶注入（SAI）等方法），需要预测气候响应以及相关的人类和生态系统影响。反过来，这些预测将依赖于全球气候模型的模拟。与气候变化预测一样，这些模拟需要充分涵盖一系列可能的未来，描述不同的选择，例如开始日期和温度目标，以及风险，例如终止或中断。迄今为止的 SRM 建模模拟通常只考虑单一场景，通常带有一些不切实际或任意选择的元素（例如在 2020 年开始部署），并且通常是基于科学而非政策相关的考虑（例如，专门选择相当大的冷却来实现更大的响应）。这限制了比较 SRM 和非 SRM 场景之间以及不同 SRM 场景之间风险的能力。为了解决这一差距，我们首先概述 SRM 场景设计的一些一般注意事项。然后，我们描述一组特定的场景，以捕获一系列可能的政策选择和不确定性，并提出相应的 SAI 模拟，供广泛的社区使用。
The benefits and risks of solar radiation modification (SRM; also known as solar geoengineering) need to be evaluated in context with the risks of climate change and will depend on choices such as the amount of cooling. One challenge today is a degree of arbitrariness in the scenarios used in current SRM simulations, making comparisons difficult both between SRM and non-SRM cases and between different SRM scenarios. We address this gap by 1) defining a set of plausible scenarios capturing a range of choices and uncertainties, and 2) providing simulations of these scenarios that can be broadly used for comparative impact assessment. This is an essential precursor to any international assessment by, e.g., the Intergovernmental Panel on Climate Change. Making informed future decisions about solar radiation modification (SRM; also known as solar geoengineering)—approaches such as stratospheric aerosol injection (SAI) that would cool the climate by reflecting sunlight—requires projections of the climate response and associated human and ecosystem impacts. These projections, in turn, will rely on simulations with global climate models. As with climate-change projections, these simulations need to adequately span a range of possible futures, describing different choices, such as start date and temperature target, as well as risks, such as termination or interruptions. SRM modeling simulations to date typically consider only a single scenario, often with some unrealistic or arbitrarily chosen elements (such as starting deployment in 2020), and have often been chosen based on scientific rather than policy-relevant considerations (e.g., choosing quite substantial cooling specifically to achieve a bigger response). This limits the ability to compare risks both between SRM and non-SRM scenarios and between different SRM scenarios. To address this gap, we begin by outlining some general considerations on scenario design for SRM. We then describe a specific set of scenarios to capture a range of possible policy choices and uncertainties and present corresponding SAI simulations intended for broad community use.
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影响因子：
1.5
作者：
Intemann, Kristen
通讯作者：
Intemann, Kristen
DOI：
10.1073/pnas.1817205116
发表时间：
2019-06-04
影响因子：
11.1
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
30.7
作者：
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通讯作者：
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