...
首页> 外文期刊>Global change biology >Exploring uncertainty of Amazon dieback in a perturbed parameter Earth system ensemble
【24h】

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

机译:在扰动参数地球系统集合中探索亚马逊陷阱的不确定性

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译:亚马逊雨林的未来由于预计的气候变化的不确定性以及森林对这种变化(森林弹性)的响应而未确定。在这里,我们利用Hadcm3c的扰动物理集合来探讨一些不确定性在森林未来的气候和土地表面过程中的影响。这是亚马逊森林更改首次使用全部探索土地植被流程和在完全耦合的建模框架中的物理气候反馈来呈现。在三个不同的排放情景下,我们在21世纪末(瞬态响应)衡量森林报道的变化,并使一种新的适应以前使用的方法称为干季弹性,以预测长期承诺的响应在森林,气候的状态仍然不变,过去2100.我们对这一集合的分析表明,森林损失的分析比2100的实现更长的时间损失,特别是对于中档和低排放情景。在瞬态和预测的犯罪答复中,由于排放情景的强度增加,森林结果日益不确定性。然而,重要的是要注意,仿真很少会产生前面在标准模型配置下所示的未来森林损失。我们发现光合作用的低最佳温度和森林所需的高最低叶面积指数,以竞争空间似乎是黑反返的前体。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,与森林弹性相关,发现如果我们更好地确定亚马逊的结果,这两者都要减少两者的不确定性是重要的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号