估计厄尔尼诺/南方涛动模拟统计的不确定性

IF 4.4 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Yann Y. Planton, Jiwoo Lee, Andrew T. Wittenberg, Peter J. Gleckler, Éric Guilyardi, Shayne McGregor, Michael J. McPhaden
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引用次数: 0

摘要

在评估气候模式和气候变化趋势时,经常使用大型模式模拟集合来减少内部变异的影响。然而,从内部变率中区分模式偏差和气候变化信号所需的最佳集合成员数因模式和指标而异。在这里,我们分析了经常用来描述厄尔尼诺-南方涛动(ENSO)的东赤道太平洋地区降水和海面温度的平均值、方差和偏度,这些数据是从耦合模式相互比较项目第 6 阶段气候模拟的大型集合中获得的。利用已建立的统计理论,我们开发并评估了一些方程,以先验地估计将厄尔尼诺-南方涛动统计中基于采样的不确定性限制在所需容限内所需的集合规模或模拟长度。我们的结果证实,这些统计数据的不确定性会随着时间序列长度和/或集合规模的平方根而减小。此外,我们还证明,在使用工业化前对照或历史运行进行计算时,这些统计量的不确定性基本相当。这表明,工业化前的运行有时可用于估算根据现有历史成员或集合计算的统计量的预期不确定性,以及充分描述统计量所需的模拟年数(运行持续时间和/或集合规模)。这一进步使我们能够利用现有的模拟(例如,在模型开发过程中进行的控制运行)来设计集合,以充分限制模拟内部变异性引起的诊断不确定性。这些结果很可能适用于厄尔尼诺/南方涛动以外的变量和区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Estimating Uncertainty in Simulated ENSO Statistics

Estimating Uncertainty in Simulated ENSO Statistics

Large ensembles of model simulations are frequently used to reduce the impact of internal variability when evaluating climate models and assessing climate change induced trends. However, the optimal number of ensemble members required to distinguish model biases and climate change signals from internal variability varies across models and metrics. Here we analyze the mean, variance and skewness of precipitation and sea surface temperature in the eastern equatorial Pacific region often used to describe the El Niño–Southern Oscillation (ENSO), obtained from large ensembles of Coupled model intercomparison project phase 6 climate simulations. Leveraging established statistical theory, we develop and assess equations to estimate, a priori, the ensemble size or simulation length required to limit sampling-based uncertainties in ENSO statistics to within a desired tolerance. Our results confirm that the uncertainty of these statistics decreases with the square root of the time series length and/or ensemble size. Moreover, we demonstrate that uncertainties of these statistics are generally comparable when computed using either pre-industrial control or historical runs. This suggests that pre-industrial runs can sometimes be used to estimate the expected uncertainty of statistics computed from an existing historical member or ensemble, and the number of simulation years (run duration and/or ensemble size) required to adequately characterize the statistic. This advance allows us to use existing simulations (e.g., control runs that are performed during model development) to design ensembles that can sufficiently limit diagnostic uncertainties arising from simulated internal variability. These results may well be applicable to variables and regions beyond ENSO.

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来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
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