Changes in the hydrological conditions of the land surface have substantial impacts on society1, 2. Yet assessments of observed continental dryness trends yield contradicting results3, 4, 5, 6, 7. The concept that dry regions dry out further, whereas wet regions become wetter as the climate warms has been proposed as a simplified summary of expected8, 9, 10 as well as observed10, 11, 12, 13, 14 changes over land, although this concept is mostly based on oceanic data8, 10. Here we present an analysis of more than 300 combinations of various hydrological data sets of historical land dryness changes covering the period from 1948 to 2005. Each combination of data sets is benchmarked against an empirical relationship between evaporation, precipitation and aridity. Those combinations that perform well are used for trend analysis. We find that over about three-quarters of the global land area, robust dryness changes cannot be detected. Only 10.8% of the global land area shows a robust ‘dry gets drier, wet gets wetter’ pattern, compared to 9.5% of global land area with the opposite pattern, that is, dry gets wetter, and wet gets drier. We conclude that aridity changes over land, where the potential for direct socio-economic consequences is highest, have not followed a simple intensification of existing patterns

A recent interpretation of climate model projections concluded that ''warmer is more arid.'' In contrast, dust records and other evidence have led the geoscience community to conclude that ''warmer is less arid'' leading to an aridity paradox. The ''warmer is more arid'' interpretation is based on a projected increase in the vapour pressure deficit ( 7-9% K 21) that results in a projected increase in potential evaporation that greatly exceeds the projected increase in precipitation. However, the increase in potential evaporation does not result in an increase in (actual) evaporation which remains more or less constant in the model output. Projected changes in the long-term aridity can be assessed by directly interrogating the climate model output. To that end, we equate lack of precipitation with meteorological aridity and lack of runoff with hydrologic aridity. A third perspective, agro-ecological aridity, is not directly related to the water lost but rather to the carbon gain and is equated with the reduction in photosynthetic uptake of CO 2 . We reexamine the same climate model output and conclude that ''warmer is less arid'' from all perspectives and in agreement with the geological records. Future research will need to add the critical regional and seasonal perspectives to the aridity assessments described here.

SignificanceThe trace element selenium is essential for human health and is required in a narrow dietary concentration range. Insufficient selenium intake has been estimated to affect up to 1 billion people worldwide. Dietary selenium availability is controlled by soil–plant interactions, but the mechanisms governing its broad-scale soil distributions are largely unknown. Using data-mining techniques, we modeled recent (1980–1999) distributions and identified climate–soil interactions as main controlling factors. Furthermore, using moderate climate change projections, we predicted future (2080–2099) soil selenium losses from 58% of modeled areas (mean loss = 8.4%). Predicted losses from croplands were even higher, with 66% of croplands predicted to lose 8.7% selenium. These losses could increase the worldwide prevalence of selenium deficiency.

Water scarcity, a critical environmental issue worldwide, has primarily been driven by a significant increase in water extractions during the last century. In the coming decades, climate and societal changes are projected to further exacerbate water scarcity in many regions worldwide. Today, a major issue for the ongoing policy debate is to identify interventions able to address water scarcity challenges in the presence of large uncertainties. Here, we take a probabilistic approach to assess global water scarcity projections following feasible combinations of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) for the first half of the 21st century. We identify-alongside trends in median water scarcity-changes in the uncertainty range of anticipated water scarcity conditions. Our results show that median water scarcity and the associated range of uncertainty are generally on the increase worldwide, including many major river basins. Based on these results, we develop a general decision-making framework to enhance policymaking by identifying four representative clusters of specific water-policy challenges and needs.

Substantial changes in the hydrological cycle are projected for the 21st century, but these projections are subject to major uncertainties. In this context, the “dry gets drier, wet gets wetter” (DDWW) paradigm is often used as a simplifying summary. However, recent studies cast doubt on the validity of the paradigm and also on applying the widely used P − E (precipitation − evapotranspiration) metric over global land surfaces. Here we show in a comprehensive CMIP5‐based assessment that projected changes in mean annual P − E are generally not significant, except for high‐latitude regions showing wetting conditions until the end of the 21st century. Significant increases in aridity do occur in many subtropical and also adjacent humid regions. However, combining both metrics still shows that approximately 70% of all land area will not experience significant changes. Based on these findings, we conclude that the DDWW paradigm is generally not confirmed for projected changes in most land areas.

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Aridity is a complex concept that ideally requires a comprehensive assessment of hydroclimatological and hydroecological variables to fully understand anticipated changes. A widely used (offline) impact model to assess projected changes in aridity is the aridity index (AI) (defined as the ratio of potential evaporation to precipitation), summarizing the aridity concept into a single number. Based on the AI, it was shown that aridity will generally increase under conditions of increased CO 2 and associated global warming. However, assessing the same climate model output directly suggests a more nuanced response of aridity to global warming, raising the question if the AI provides a good representation of the complex nature of anticipated aridity changes. By systematically comparing projections of the AI against projections for various hydroclimatological and ecohydrological variables, we show that the AI generally provides a rather poor proxy for projected aridity conditions. Direct climate model output is shown to contradict signals of increasing aridity obtained from the AI in at least half of the global land area with robust change. We further show that part of this discrepancy can be related to the parameterization of potential evaporation. Especially the most commonly used potential evaporation model likely leads to an overestimation of future aridity due to incorrect assumptions under increasing atmospheric CO 2 . Our results show that AI-based approaches do not correctly communicate changes projected by the fully coupled climate models. The solution is to directly analyse the model outputs rather than use a separate offline impact model. We thus urge for a direct and joint assessment of climate model output when assessing future aridity changes rather than using simple index-based impact models that use climate model output as input and are potentially subject to significant biases.