There is a tremendous desire to attribute causes to weather and climate events that is often challenging from a physical standpoint. Headlines attributing an event solely to either human-induced climate change or natural variability can be misleading when both are invariably in play. The conventional attribution framework struggles with dynamically driven extremes because of the small signal-to-noise ratios and often uncertain nature of the forced changes. Here, we suggest that a different framing is desirable, which asks why such extremes unfold the way they do.

Diatoms are responsible for ~40% of marine primary productivity, fuelling the oceanic carbon cycle and contributing to natural carbon sequestration in the deep ocean. Diatoms rely on energetically expensive carbon concentrating mechanisms (CCMs) to fix carbon efficiently at modern levels of CO2. How diatoms may respond over the short and long term to rising atmospheric CO2 remains an open question.

Policymakers need to know what factors are most important in determining local vulnerability to facilitate effective adaptation to climate change. Quantitative vulnerability indices are helpful in this endeavour but are limited in their ability to capture subtle yet important aspects of vulnerability such as social networks, knowledge and access to resources. Working with three African American communities on Maryland’s Eastern Shore, we systematically elicit local cultural knowledge on climate change and connect it with a scientific vulnerability framework.

Many studies have implied significant effects of global climate change on marine life. Setting these alterations into the context of historical natural change has not been attempted so far, however. Here, using a theoretical framework, we estimate the sensitivity of marine pelagic biodiversity to temperature change and evaluate its past (mid-Pliocene and Last Glacial Maximum (LGM)), contemporaneous (1960–2013) and future (2081–2100; 4 scenarios of warming) vulnerability.

Increasing evidence indicates that species throughout the world are responding to climate change by shifting their geographic distributions. Although shifts can be directionally heterogeneous, they often follow warming temperatures polewards and upslope. Montane species are of particular concern in this regard, as they are expected to face reduced available area of occupancy and increased risk of extinction with upslope movements. However, this expectation hinges on the assumption that surface area decreases monotonically as species move up mountainsides.

Global tropical cyclone climate has been investigated with indicators of frequency, intensity and activity. However, a full understanding of global warming’s influence on tropical cyclone climate remains elusive because of the incomplete nature of these indicators. Here we form a complete three-dimensional variability space of tropical cyclone climate where the variabilities are continuously linked and find that global ocean warmth best explains the out-of-phase relationship between intensity and frequency of global tropical cyclones.

Extreme heat events are likely to become more frequent in the coming decades owing to climate change. Exposure to extreme heat depends not only on changing climate, but also on changes in the size and spatial distribution of the human population. Here we provide a new projection of population exposure to extreme heat for the continental United States that takes into account both of these factors.

Demand-side management (DSM) is a key aspect of many future energy system scenarios. DSM refers to a range of technologies and interventions designed to create greater efficiency and flexibility on the demand-side of the energy system. Examples include the provision of more information to users to support efficient behaviour and new ‘smart’ technologies that can be automatically controlled. Key stated outcomes of implementing DSM are benefits for consumers, such as cost savings and greater control over energy use.

Climate change includes not only changes in mean climate but also in weather extremes. For a few prominent heatwaves and heavy precipitation events a human contribution to their occurrence has been demonstrated. Here we apply a similar framework but estimate what fraction of all globally occurring heavy precipitation and hot extremes is attributable to warming.

European continental shelf seas have experienced intense warming over the past 30 years. In the North Sea, fish have been comprehensively monitored throughout this period and resulting data provide a unique record of changes in distribution and abundance in response to climate change. We use these data to demonstrate the remarkable power of generalized additive models (GAMs), trained on data earlier in the time series, to reliably predict trends in distribution and abundance in later years.