Mathematical Sciences: Global Change Research Program

9634300 Lempert虽然技术问题似乎对气候变化政策至关重要，但综合评估界目前缺乏一个适当的框架来考虑新技术对政策选择的影响。根本的问题是，在相关的时间跨度内，技术的演变是不可预测的。目前可用的决策分析工具是基于对未来做出一些可信的最佳估计预测的能力。然而，气候变化等政策问题面临着极端的不确定性，不可能构建具有良好特征的最佳估计。在这种情况下，基于预测的政策分析往往无法解决利益攸关方之间的激烈辩论，这些利益攸关方相信不同的最佳估计，往往导致对可能的政策选择的有限思考。在他们最近的工作中，研究人员展示了一种替代的政策分析框架，它不依赖于对未来做出最佳估计预测。该方法基于两个概念，即适应性策略和探索性建模。探索性建模通过对问题的许多看似合理的公式进行大量的计算机模拟实验来处理具有大量不确定性的问题，而不是使用计算机资源来提高单个最佳估计模型的分辨率。自适应决策战略侧重于对环境政策进行建模，决策者可以根据对相关环境和经济系统的观察进行中期修正。在这一研究项目中，研究人员将使用探索性建模/适应战略框架来审查新技术的潜力如何影响近期的气候变化政策选择。这项研究有两个具体目标：1)展示和推进探索性建模/适应战略框架的能力；2)研究一个中心的气候变化政策问题--除了碳税之外，社会应该在什么条件下推行特定于技术的政策(例如，税收抵免、补贴或政府采购)？政策制定者经常必须做出决定，其最终成功取决于在做出决定时无法预测的因素。然而，目前用于帮助政策制定者比较替代政策的决策分析工具是建立在对未来做出一些可信的最佳估计预测的能力的基础上的。在极端不确定的情况下，基于预测的政策分析往往无法解决利益攸关方之间的激烈辩论，这些利益攸关方相信不同的最佳估计，而且往往导致对可能的政策选择的有限思考。气候变化就是一个重要的例子。未来的技术发展可能会对气候变化政策产生深远影响，但没有人能准确预测技术对未来减少温室气体排放的成本的影响，也没有人能准确预测各种政策将对这些成本产生的影响。在最近的工作中，研究人员展示了一种新的政策分析框架，它不依赖于对未来做出最佳估计预测。这种方法基于两个概念，称为自适应策略和探索性建模，它们利用了最近的计算机技术提供的新的分析能力。探索性建模通过对大量可信的未来估计进行计算机模拟实验，并使用抽样策略和数据可视化在结果中找到重要模式，来处理具有极端不确定性的问题。适应性决策侧重于对环境政策进行建模，决策者可以根据对相关环境和经济系统的观察进行中期修正。在这个研究项目中，研究人员将使用探索性建模/适应战略框架来检查新技术的潜力应该如何影响近期的气候变化政策选择。具体而言，该项目将：1)展示和推进探索性建模/适应战略框架的能力；2)审查气候变化政策的一个核心问题-除征收碳税外，社会应在什么条件下推行针对技术的政策(例如，税收抵免、补贴或政府采购)？

9634300 Lempert Although technology issues appear vital to climate-change policy, the Integrated Assessment community currently lacks a suitable framework for considering the implications of new technology for policy choices. The fundamental problem is the unpredictability of the evolution of technology over the time spans of relevance. Currently available decision-analysis tools are predicated on the ability to craft some credible best- estimate prediction of the future. However, policy problems such as climate change face extreme uncertainties for which it is not possible to construct well-characterized best estimates. In such cases, prediction-based policy analysis is often unable to resolve acrimonious debate among stakeholders who believe in different best estimates, and often results in constrained thinking about possible policy options. In their recent work the investigators have demonstrated an alternative framework for policy analysis that does not depend on making best-estimate predictions of the future. The approach is based on two concepts called adaptive strategies and exploratory modeling. Exploratory modeling treats problems having massive uncertainty by conducting a large number of computer simulation- experiments on many plausible formulations of the problem, rather than using computer resources to increase the resolution of a single best-estimate model. Adaptive-decision strategies focus on modeling environmental policies where decision-makers can make midcourse corrections based on observations of the relevant environmental and economic systems. In this research project the investigators will use the exploratory modeling/adaptive strategies framework to examine how the potential of new technology should affect near- term climate change policy choices. The research has two specific goals: 1) demonstrate and advance the capabilities of the exploratory modeling/ adaptive strategies framework, and 2) examine a central climate-change po licy question -- under what conditions should society pursue technology-specific policies (e.g., tax credits, subsidies, or government procurements) in addition to carbon taxes? Policy-makers must often make decisions whose ultimate success depends on factors that cannot be predicted at the time the decision is made. However, currently available decision- analysis tools used to help policy-makers compare alternative policies are predicated on the ability to craft some credible best-estimate prediction of the future. Under conditions of extreme uncertainty, prediction-based policy analysis is often unable to resolve acrimonious debate among stakeholders who believe in different best estimates, and often results in constrained thinking about possible policy options. Climate change provides an important example. Future technology developments could have profound impacts on climate-change policy, but no one can accurately predict the impacts of technology on the future costs of reducing greenhouse-gas emissions, nor the effects that various policies will have on these costs. In recent work, the investigators have demonstrated a new framework for policy analysis that does not depend on making best-estimate predictions of the future. The approach is based on two concepts, called adaptive strategies and exploratory modeling, that take advantage of the new analytic capabilities provided by recent computer technology. Exploratory modeling treats problems having extreme uncertainty by conducting computer simulation-experiments on a very large number of plausible estimates of the future and using sampling strategies and data visualization to find important patterns in the results. Adaptive-decision focus on modeling environmental policies where decision- makers can make midcourse corrections based on observations of the relevant environmental and economic systems. In this research project, the investigators will use the exploratory modeling/adaptive strategies framework to examine how the potential of new technology should affect near-term climate change policy choices. In particular, the project will: 1) demonstrate and advance the capabilities of the exploratory modeling/adaptive strategies framework, and 2) examine a central climate-change policy question -- under what conditions should society pursue technology-specific policies (e.g., tax credits, subsidies, or government procurements) in addition to carbon taxes?