地球系统科学
气候变化
环境科学
约束(计算机辅助设计)
气候学
碳循环
温室气体
气候模式
航程(航空)
气候系统
计算机科学
环境资源管理
生态学
数学
生态系统
材料科学
几何学
复合材料
生物
地质学
标识
DOI:10.1007/s40641-019-00141-y
摘要
Abstract Purpose of Review Feedbacks between CO 2 -induced climate change and the carbon cycle are now routinely represented in the Earth System Models (ESMs) that are used to make projections of future climate change. The inconclusion of climate-carbon cycle feedbacks in climate projections is an important advance, but has added a significant new source of uncertainty. This review assesses the potential for emergent constraints to reduce the uncertainties associated with climate-carbon cycle feedbacks. Recent Findings The emergent constraint technique involves using the full ensemble of models to find an across-ensemble relationship between an observable feature of the Earth System (such as a trend, interannual variation or change in seasonality) and an uncertain aspect of the future. Examples focussing on reducing uncertainties in future atmospheric CO 2 concentration, carbon loss from tropical land under warming and CO 2 fertilization of mid- and high-latitude photosynthesis are exemplars of these different types of emergent constraints. Summary The power of emergent constraints is that they use the enduring range in model projections to reduce uncertainty in the future of the real Earth System, but there are also risks that indiscriminate data-mining, and systematic model errors could yield misleading constraints. A hypothesis-driven theory-led approach can overcome these risks and also reveal the true promise of emergent constraints—not just as ways to reduce uncertainty in future climate change but also to catalyse advances in our understanding of the Earth System.
科研通智能强力驱动
Strongly Powered by AbleSci AI