A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend.
A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend.
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DOI：
10.1038/s41467-018-05442-8
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发表时间：
2018-08-14
影响因子：
16.6
通讯作者：
Drijfhout SS
中科院分区：
文献类型：
--
作者：
Sévellec F;Drijfhout SS
在不断变化的气候中，社会对准确可靠的年际预测的需求不断增加。准确可靠的全球气温年际预测是确定与全球气温成比例的区域气候变化影响的关键，例如极端降水、严重干旱或强烈的飓风活动。然而，气候系统的混沌性质限制了这种时间尺度上的预测准确性。在这里，我们开发了一种新的方法来预测全球平均表面气温和海面温度，基于传输算子，它允许，通过设计，概率预报。预报精度与业务预报相当，可靠性高。1998年后的全球变暖中断是可以预测的。对于2018 - 2022年，概率预测表明，相对于强迫趋势，气温将高于正常水平。这将暂时加强长期的全球变暖趋势。即将到来的温暖时期与强烈到极端温度的可能性增加有关。该方法的重要数值效率（笔记本电脑上的百分之几秒）为在个人移动的设备上进行实时概率预测提供了可能性。为了确定气候变化的一些关键影响，需要对全球气温进行准确的近期预测。在这里，作者开发了一种新的概率预测系统，显示了未来几年极端变暖的风险增加的极端温暖的温度。
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. Accurate near-term predictions of global temperatures are required to determine some of the key impacts of climate change. Here the authors develop a novel probabilistic forecast system that shows anomalously warm temperatures for the next years with increased risk of extreme warming.
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影响因子：
5.2
作者：
Easterling, David R.;Wehner, Michael F.
通讯作者：
Wehner, Michael F.
影响因子：
5.2
作者：
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通讯作者：
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作者：
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通讯作者：
Asif, Muhammad
影响因子：
18.3
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通讯作者：
Knight, Jeff
影响因子：
8
作者：
Hawkins, Ed;Sutton, Rowan
通讯作者：
Sutton, Rowan