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在受扰参数地球系统集合中探索亚马逊林火衰退的不确定性。

Exploring uncertainty of Amazon dieback in a perturbed parameter Earth system ensemble.

机构信息

Earth System Science, College of Life and Environmental Sciences, University of Exeter, Exeter, UK.

Met Office Hadley Centre, Exeter, UK.

出版信息

Glob Chang Biol. 2017 Dec;23(12):5032-5044. doi: 10.1111/gcb.13733. Epub 2017 Jun 1.

Abstract

The future of the Amazon rainforest is unknown due to uncertainties in projected climate change and the response of the forest to this change (forest resiliency). Here, we explore the effect of some uncertainties in climate and land surface processes on the future of the forest, using a perturbed physics ensemble of HadCM3C. This is the first time Amazon forest changes are presented using an ensemble exploring both land vegetation processes and physical climate feedbacks in a fully coupled modelling framework. Under three different emissions scenarios, we measure the change in the forest coverage by the end of the 21st century (the transient response) and make a novel adaptation to a previously used method known as "dry-season resilience" to predict the long-term committed response of the forest, should the state of the climate remain constant past 2100. Our analysis of this ensemble suggests that there will be a high chance of greater forest loss on longer timescales than is realized by 2100, especially for mid-range and low emissions scenarios. In both the transient and predicted committed responses, there is an increasing uncertainty in the outcome of the forest as the strength of the emissions scenarios increases. It is important to note however, that very few of the simulations produce future forest loss of the magnitude previously shown under the standard model configuration. We find that low optimum temperatures for photosynthesis and a high minimum leaf area index needed for the forest to compete for space appear to be precursors for dieback. We then decompose the uncertainty into that associated with future climate change and that associated with forest resiliency, finding that it is important to reduce the uncertainty in both of these if we are to better determine the Amazon's outcome.

摘要

由于预计的气候变化和森林对这种变化的响应(森林弹性)存在不确定性,亚马逊雨林的未来前景尚不明朗。在这里,我们使用 HadCM3C 的受扰物理集合来探索气候和陆地表面过程中的一些不确定性对森林未来的影响。这是首次使用探索陆地植被过程和物理气候反馈的集合来展示亚马逊森林的变化,这是在完全耦合的建模框架中进行的。在三种不同的排放情景下,我们测量到 21 世纪末森林覆盖面积的变化(瞬态响应),并对先前使用的一种称为“旱季弹性”的方法进行了新颖的改编,以预测森林的长期承诺响应,如果气候状况在 2100 年之后保持不变。我们对该集合的分析表明,在更长的时间内,森林损失的可能性将比 2100 年更大,尤其是在中排放和低排放情景下。在瞬态和预测的承诺响应中,随着排放情景强度的增加,森林的结果不确定性越来越大。然而,需要注意的是,很少有模拟产生了以前在标准模型配置下显示的那种规模的未来森林损失。我们发现,光合作用的最适温度较低和森林为争夺空间所需的最小叶面积指数较高,这似乎是衰退的前兆。然后,我们将不确定性分解为与未来气候变化相关的不确定性和与森林弹性相关的不确定性,发现如果我们要更好地确定亚马逊的结果,那么降低这两方面的不确定性都很重要。

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