论文标题：A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend

期刊：Nature Communications

作者：Florian Sévellec & Sybren S. Drijfhout

发表时间：2018/08/14

数字识别码：10.1038/s41467-018-05442-8

原文链接：https://www.nature.com/articles/s41467-018-05442-8?utm_source=Other_website&utm_medium=Website_links&utm_content=RenLi-Nature-Nature_Comms-Atmospheric_Science/Climate-China&utm_campaign=NATCOMMS_USG_JRCN_RL_sciencenet_warm_4th_Aug

微信链接：https://mp.weixin.qq.com/s/fGJTrqfII-4WftQEBG_nCA

根据《自然-通讯》上的一篇论文 A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend 报告，一个概率预报系统预计2018年至2022年是一个异常温暖的时期，极端温度出现的可能性将会上升。该研究提出了一种统计模型，运用笔记本电脑即可以在几百分之一秒内产出全球平均表面气温的预测值，使运用个人设备进行实时概率预测成为可能。

全球平均表面气温的变化可归因于外部因素驱动和气候系统的自然变率，前者包括温室气体排放或气溶胶，它们顺应特定的社会经济场景，而后者较难预测。因此，要提高年际气候预测的准确性，则需要改进预测气候系统的自然变率。

法国布雷斯特大学的Florian Sevellec和Sybren Drijfhout开发了一种基于变换算子的统计方法来描绘自然变率，这是一种可以解释系统混沌行为的成熟统计分析方法。该系统可以提供可靠的全球平均表面气温和海面温度的概率预测。对2018年至2022年的预测表明，由自然变率导致的气候变暖将暂时强化长期的全球变暖趋势，导致极端温度出现的可能性上升。

图1：观测到全球平均表面气温(GMT) 和海面温度（SST）的归因图源：Sevellec et al.

尽管该系统一次只预测一个度量，但经过调整后也可以预测其它度量（如降水量），并且可以进行区域尺度的预测。此外，由于该系统可以在笔记本电脑上运行，因而有望使气候预测为FC碰碰胡老虎机法典-提高赢钱机率的下注技巧的科研人员所用。

摘要：In a changing climate, there is an ever-increasing societal demand for accurate and reliable interannual predictions. Accurate and reliable interannual predictions of global temperatures are key for determining the regional climate change impacts that scale with global temperature, such as precipitation extremes, severe droughts, or intense hurricane activity, for instance. However, the chaotic nature of the climate system limits prediction accuracy on such timescales. Here we develop a novel method to predict global-mean surface air temperature and sea surface temperature, based on transfer operators, which allows, by-design, probabilistic forecasts. The prediction accuracy is equivalent to operational forecasts and its reliability is high. The post-1998 global warming hiatus is well predicted. For 2018–2022, the probabilistic forecast indicates a warmer than normal period, with respect to the forced trend. This will temporarily reinforce the long-term global warming trend. The coming warm period is associated with an increased likelihood of intense to extreme temperatures. The important numerical efficiency of the method (a few hundredths of a second on a laptop) opens the possibility for real-time probabilistic predictions carried out on personal mobile devices.

阅读论文全文请访问：https://www.nature.com/articles/s41467-018-05442-8?utm_source=Other_website&utm_medium=Website_links&utm_content=RenLi-Nature-Nature_Comms-Atmospheric_Science/Climate-China&utm_campaign=NATCOMMS_USG_JRCN_RL_sciencenet_warm_4th_Aug

来源：科学网