The El Niño/Southern Oscillation (ENSO) has a pronounced influence on year-to-year variations in climate1. The response of fires to this forcing2 is complex and has not been evaluated systematically across different continents. Here we use satellite data to create a climatology of burned-area and fire-emissions responses, drawing on six El Niño and six La Niña events during 1997–2016.

 

A critical question for agricultural production and food security is how water demand for staple crops will respond to climate and carbon dioxide (CO2) changes, especially in light of the expected increases in extreme heat exposure. To quantify the trade-offs between the effects of climate and CO2 on water demand, we use a ‘sink-strength’ model of demand which relies on the vapour-pressure deficit (VPD), incident radiation and the efficiencies of canopy-radiation use and canopy transpiration; the latter two are both dependent on CO2.

Most climate change mitigation scenarios that are consistent with the 1.5–2 °C target rely on a large-scale contribution from biomass, including advanced (second-generation) biofuels. However, land-based biofuel production has been associated with substantial land-use change emissions. Previous studies show a wide range of emission factors, often hiding the influence of spatial heterogeneity. Here we introduce a spatially explicit method for assessing the supply of advanced biofuels at different emission factors and present the results as emission curves.

Mesoscale convective system (MCS)-organized convective storms with a size of ~100 km have increased in frequency and intensity in the USA over the past 35 years, causing fatalities and economic losses. However, their poor representation in traditional climate models hampers the understanding of their change in the future. Here, a North American-scale convection-permitting model which is able to realistically simulate MSCs is used to investigate their change by the end-of-century under RCP8.5.

The existence and magnitude of the recently suggested global warming hiatus, or slowdown, have been strongly debated. Although various physical processes have been examined to elucidate this phenomenon, the accuracy and completeness of observational data that comprise global average surface air temperature (SAT) datasets is a concern9,10. In particular, these datasets lack either complete geographic coverage or in situ observations over the Arctic, owing to the sparse observational network in this area.

In 2014 and 2015, post-monsoon extremely severe cyclonic storms (ESCS)—defined by the WMO as tropical storms with lifetime maximum winds greater than 46 m s−1—were first observed over the Arabian Sea (ARB), causing widespread damage. However, it is unknown to what extent this abrupt increase in post-monsoon ESCSs can be linked to anthropogenic warming, natural variability, or stochastic behaviour.

The Paris Agreement requires countries to articulate near-term emissions reduction strategies through to 2025 or 2030 by communicating nationally determined contributions (NDCs), as well as encouraging the formulation of long-term low-emission development strategies (Article 4.19). In response, many countries have either submitted or are preparing mid-century strategies.

States have historically been the primary drivers of climate change policy in the US, particularly with regard to emissions from power plants. States have implemented policies designed either to directly curb greenhouse gas (GHG) emissions from power plants, or to encourage energy efficiency and renewable energy growth. With the federal government withdrawing from the global climate agreement, understanding which state-level policies have successfully mitigated power-plant emissions is urgent.

Roadway design aims to maximize functionality, safety, and longevity. The materials used for construction, however, are often selected on the assumption of a stationary climate. Anthropogenic climate change may therefore result in rapid infrastructure failure and, consequently, increased maintenance costs, particularly for paved roads where temperature is a key determinant for material selection.

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms.

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