More than half of the solar energy absorbed by land surfaces is currently used to evaporate water(1). Climate change is expected to intensify the hydrological cycle(2) and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land-a key diagnostic criterion of the effects of climate change and variability-remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network(3), meteorological and remote-sensing observations, and a machine-learning algorithm(4). In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface-models. Our results suggest that global annual evapotranspiration increased on average by 7.1 +/- 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Nino event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science
Increasing greenhouse gas concentrations are expected to enhance the interannual variability of summer climate in Europe and other mid-latitude regions, potentially causing more frequent heatwaves. Climate models consistently predict an increase in the variability of summer temperatures in these areas, but the underlying mechanisms responsible for this increase remain uncertain. Here we explore these mechanisms using regional simulations of recent and future climatic conditions with and without land-atmosphere interactions. Our results indicate that the increase in summer temperature variability predicted in central and eastern Europe is mainly due to feedbacks between the land surface and the atmosphere. Furthermore, they suggest that land-atmosphere interactions increase climate variability in this region because climatic regimes in Europe shift northwards in response to increasing greenhouse gas concentrations, creating a new transitional climate zone with strong land-atmosphere coupling in central and eastern Europe. These findings emphasize the importance of soil-moisture-temperature feedbacks (in addition to soil-moisture-precipitation feedbacks) in influencing summer climate variability and the potential migration of climate zones with strong land-atmosphere coupling as a consequence of global warming. This highlights the crucial role of land-atmosphere interactions in future climate change.
The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impacts of climate extremes on the terrestrial carbon cycle, and propose a pathway to improve our understanding of present and future impacts of climate extremes on the terrestrial carbon budget.
Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a 'compound event'. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.
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