Understanding Differences of Event Attribution Results Arising from Modeling Strategy

模拟策略对事件归因结论的影响

+ Author Affiliations + Find other works by these authors
  • Corresponding author: Tianjun ZHOU
  • Funds:

    Supported by the National Key Research and Development Program of China (2018YFC1507701).

  • doi: 10.1007/s13351-022-1109-3
  • Note: This paper has been peer-reviewed and is just accepted by J. Meteor. Res. Professional editing and proof reading are underway. Please use with caution.

PDF

  • While there is high confidence that human activities have increased the likelihood and severity of hot extreme events over many parts of the world, there is notable spread in quantitative estimates of anthropogenic influence even on a single event. To better understand the uncertainty of attribution results, here we compare different event attribution methods using the 2015 July-August record-breaking heat event in Northwestern China as a case. To address the anthropogenic influence on the likelihood of the extreme event, we employ attribution runs with two modeling strategies – atmosphere-only and coupled simulations, with different conditioning. In atmosphere-only attribution runs, given the observed sea surface boundary conditions and external forcings at 2015, it is estimated that anthropogenic forcing has increased the likelihood of hot extremes such as that observed in 2015 in the target region by approximately 27 and 12 times in MIROC5 and HadGEM3-A-N216, respectively. In Coupled Model Intercomparison Project Phase 5 (CMIP5) fully-coupled attribution runs, given the external forcing at the 1961-2015 level and regardless of sea surface boundary conditions, there is a 21-times increase in the likelihood of similar heat events due to anthropogenic forcing. The differences in quantitative attribution results can arise from modeling strategies, which is tightly linked to different conditioning in attribution. Specifically, different ocean boundary conditions, external forcings, and air-sea coupling processes contribute to different attribution results between the two modeling strategies. Within each modeling strategy, model uncertainty affects quantitative attribution conclusions. The comparison of different attribution methods provides a better understanding of the uncertainty of attribution results, which is useful in synthesizing and interpreting attribution results.

    尽管当前研究一致指出人类活动增强了全球许多地区极端高温事件的发生概率和强度,然而对于人为影响的定量估算仍存在较大的不确定性。为理解事件归因研究中定量结论的不确定性,本文基于2015年7-8月中国西北部破纪录热浪事件这一个例,比较了不同归因方法和不同模式对归因结论的影响。为估算人类活动对此次极端事件发生概率的影响,本文采用两类模拟试验进行归因,分别是单独大气模式和耦合模式。在大气模式归因框架下,即在2015年观测海温/海冰边界条件和外强迫条件下,MIROC5和HadGEM3-A-N216大气模式表明,人类活动使得类似观测中的极端高温事件发生概率增加了约27倍和12倍。基于CMIP5的耦合模式归因则表明,在1961-2015年总体的外强迫水平下且不考虑海洋边界条件,人类活动使类似极端高温事件的发生概率增加了约21倍。可见采用不同的模拟策略会影响定量归因结论,这与归因所依赖的条件紧密相关。具体而言,大气模式和耦合模式两类归因结论的差异来自于不同的海洋边界条件、外强迫场以及海气相互作用的影响。在每一类模拟策略框架下,模式不确定性也会影响定量归因结果。本文基于不同归因方法和不同模式的比较,提高了对归因结论不确定性的理解,这有助于对归因结果进行综合集成。

  • 加载中
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Understanding Differences of Event Attribution Results Arising from Modeling Strategy

    Corresponding author: Tianjun ZHOU
  • 1. LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
  • 2. University of Chinese Academy of Sciences, Beijing 100049
Funds: Supported by the National Key Research and Development Program of China (2018YFC1507701).

Abstract: 

While there is high confidence that human activities have increased the likelihood and severity of hot extreme events over many parts of the world, there is notable spread in quantitative estimates of anthropogenic influence even on a single event. To better understand the uncertainty of attribution results, here we compare different event attribution methods using the 2015 July-August record-breaking heat event in Northwestern China as a case. To address the anthropogenic influence on the likelihood of the extreme event, we employ attribution runs with two modeling strategies – atmosphere-only and coupled simulations, with different conditioning. In atmosphere-only attribution runs, given the observed sea surface boundary conditions and external forcings at 2015, it is estimated that anthropogenic forcing has increased the likelihood of hot extremes such as that observed in 2015 in the target region by approximately 27 and 12 times in MIROC5 and HadGEM3-A-N216, respectively. In Coupled Model Intercomparison Project Phase 5 (CMIP5) fully-coupled attribution runs, given the external forcing at the 1961-2015 level and regardless of sea surface boundary conditions, there is a 21-times increase in the likelihood of similar heat events due to anthropogenic forcing. The differences in quantitative attribution results can arise from modeling strategies, which is tightly linked to different conditioning in attribution. Specifically, different ocean boundary conditions, external forcings, and air-sea coupling processes contribute to different attribution results between the two modeling strategies. Within each modeling strategy, model uncertainty affects quantitative attribution conclusions. The comparison of different attribution methods provides a better understanding of the uncertainty of attribution results, which is useful in synthesizing and interpreting attribution results.

模拟策略对事件归因结论的影响

尽管当前研究一致指出人类活动增强了全球许多地区极端高温事件的发生概率和强度,然而对于人为影响的定量估算仍存在较大的不确定性。为理解事件归因研究中定量结论的不确定性,本文基于2015年7-8月中国西北部破纪录热浪事件这一个例,比较了不同归因方法和不同模式对归因结论的影响。为估算人类活动对此次极端事件发生概率的影响,本文采用两类模拟试验进行归因,分别是单独大气模式和耦合模式。在大气模式归因框架下,即在2015年观测海温/海冰边界条件和外强迫条件下,MIROC5和HadGEM3-A-N216大气模式表明,人类活动使得类似观测中的极端高温事件发生概率增加了约27倍和12倍。基于CMIP5的耦合模式归因则表明,在1961-2015年总体的外强迫水平下且不考虑海洋边界条件,人类活动使类似极端高温事件的发生概率增加了约21倍。可见采用不同的模拟策略会影响定量归因结论,这与归因所依赖的条件紧密相关。具体而言,大气模式和耦合模式两类归因结论的差异来自于不同的海洋边界条件、外强迫场以及海气相互作用的影响。在每一类模拟策略框架下,模式不确定性也会影响定量归因结果。本文基于不同归因方法和不同模式的比较,提高了对归因结论不确定性的理解,这有助于对归因结果进行综合集成。

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return