Research press release


Nature Communications

Climate science: 2018-2022 predicted to be anomalously warm



今回、Florian SevellecとSybren Drijfhoutは、自然変動を把握するために転送作用素を用いた統計的方法を開発した。これは、確立された統計分析法であり、系のカオス的挙動を合理的に説明できる。このシステムを用いれば、全球平均地上気温と海面水温に関して、信頼性の高い確率予報が得られる。そして、2018~2022年の予報では、自然変動を原因とする温暖化によって長期的な地球温暖化傾向が一時的に強化され、異常高温が生じる可能性が高まるとされる。


2018 to 2022 is predicted to be an anomalously warm period with an increased likelihood of extreme temperatures, according to a probabilistic forecast system reported in Nature Communications. The study presents a statistical model that produces predictions of global mean surface air temperature in a few hundredths of a second on a laptop, opening up the possibility of real-time probabilistic forecasting on personal devices.

Changes in global mean surface temperature can be attributed to external forcing (such as greenhouse gas emissions or aerosols, which follow particular socioeconomic scenarios) and to natural variability in the system, which is harder to predict. Therefore, improvements in predicting natural variability are required for more accurate interannual climate forecasts.

Florian Sevellec and Sybren Drijfhout develop a statistical approach based on transfer operators - an established statistical analysis method that rationalizes the chaotic behaviour of a system - that captures natural variability. This system provides reliable probabilistic predictions of global mean surface temperature and sea-surface temperature. A forecast for 2018-2022 indicates that warming owing to natural variability will temporarily reinforce the long-term global warming trend, leading to an increase in the likelihood of temperature extremes.

Although the system only forecasts one metric at a time, it can be adjusted to predict other measures, such as precipitation, and to focus on regional scales. In addition, the system can be run on a laptop, which could broaden access to climate forecasts to a wider scientific community.

doi: 10.1038/s41467-018-05442-8

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