Current Climate Change Reports ( IF 9.3 ) Pub Date : 2019-09-10 , DOI: 10.1007/s40641-019-00141-y Peter M Cox 1
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Purpose of Review
Feedbacks between CO2-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 CO2 concentration, carbon loss from tropical land under warming and CO2 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.
中文翻译：
气候-碳循环反馈的新限制
审查目的
CO 2引起的气候变化和碳循环之间的反馈现在通常在用于预测未来气候变化的地球系统模型（ESM）中体现。将气候-碳循环反馈纳入气候预测是一个重要的进步，但也增加了一个重要的新的不确定性来源。本次审查评估了减少与气候碳循环反馈相关的不确定性的紧急约束的潜力。
最近的发现
新兴约束技术涉及使用完整的模型集合来寻找地球系统的可观测特征（例如趋势、年际变化或季节性变化）与未来的不确定方面之间的跨集合关系。关注减少未来大气CO 2浓度的不确定性、变暖下热带土地的碳损失以及中高纬度光合作用的CO 2施肥的例子是这些不同类型的紧急约束的例子。
概括
新兴约束的力量在于，它们利用模型预测中的持久范围来减少真实地球系统未来的不确定性，但也存在不加区别的数据挖掘和系统模型错误可能产生误导性约束的风险。以假设驱动的理论为主导的方法可以克服这些风险，并揭示紧急约束的真正前景——不仅可以作为减少未来气候变化不确定性的方法，还可以促进我们对地球系统的理解取得进展。
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