Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Owing to incomplete data, it is difficult to establish tropical cyclone behaviour over long timescales. However, by considering the total released energy of individual cyclones, it is possible to establish changes of cyclone energy and their connection to climate change. The influence of climate variability and global warming on the occurrence of tropical cyclones is a controversial issue1,2,3,4,5,6,7,8,9,10. Existing historical databases on the subject are not fully reliable9,11,12,13, but a more fundamental hindrance is the lack of basic understanding regarding the intrinsic nature of tropical-cyclone genesis and evolution14. It is known that tropical cyclones involve more than a passive response to changing external forcing15, but it is not clear which dynamic behaviour best describes them. Here we present an approach based on the application of the power dissipation index, which constitutes an estimation of released energy3, to individual tropical cyclones. A robust law emerges for the statistics of power dissipation index, valid in four different ocean basins and over long time periods. In addition to suggesting a description of the physics of tropical cyclones in terms of critical phenomena16,17, the scaling law enables us to quantify their response to changing climatic conditions, with an increase in the largest power dissipation index values with sea surface temperature or the presence of El Niño phenomena, depending on the basin under consideration. In this way, we demonstrate that the recent upswing in North Atlantic hurricane activity does not involve tropical cyclones that are quantitatively different from those in other sustained high-activity periods before 1970.

Human society and natural systems are intrinsically adapted to the local climate mean and variability. Therefore, changes relative to the local expected variability are highly relevant for assessing impact and planning for adaptation as the climate changes. We analyse the emerging climate signal relative to the diagnosed internal variability (signal-to-noise ratio, S/N) of a set of recently published climate indices over Europe. We calculate the signal-to-noise ratio with respect to a recent baseline (1951–1983) which relates to recent societal experience. In this framework, we find that during the 2000–2016 period, many areas of Europe already experienced significant changes in climate extremes, even when compared to this recent period which is within living memory. In particular, the S/N of extreme temperatures is larger than 1 and 2 over 34% and 4% of Europe, respectively. We also find that about 15% of Europe is experiencing more intense winter precipitation events, while in summer, 7% of Europe is experiencing stronger drought-inducing conditions.

The most disastrous heatwaves are very extreme events with return periods of hundreds of years, but traditionally, climate research has focussed on moderate extreme events occurring every couple of years or even several times within a year. Here, we use three Earth System Model large ensembles to assess whether very extreme heat events respond differently to global warming than moderate extreme events. We find that the warming signal of very extreme heat can be amplified or dampened substantially compared to moderate extremes. This modulation is detectable already in mid-century projections. In the mid-latitudes, it can be explained by changes in event soil moisture-temperature coupling during the hottest day of the year. The changes depend on the interplay of present soil moisture and coupling during heat events as well as projected precipitation changes. This mechanism is robust across models, albeit with large spatial uncertainties. Our findings are highly relevant for climate risk assessments and adaptation planning.

Significance: Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications, from tourism to agriculture, water resource management, energy production, construction, and retail. However, dynamical model seasonal forecasts for European summers have very little skill. Here, we analyze atmosphere and ocean observations and identify evidence that a specific pattern of summertime atmospheric circulation over Western Europe is predictable from the previous spring North Atlantic sea-surface temperatures, and identify the mechanism involved. The atmospheric pattern has a particularly strong influence on rainfall in the British Isles and in the north coast of France, which we find can also be predicted months ahead with significant skill.