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Accumulating evidence on the impact of climate change on droughts, highlights the necessity for developing effective adaptation and mitigation strategies. Changes in future drought risk and severity in Australia are quantified by analyzing nine Coupled Model Intercomparison Project Phase 6 climate models. Historic conditions (1981–2014) and projections for mid-century (2015–2050) and end-century (2051–2100) from four shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are examined. Drought events are identified using both the standardized precipitation index and the standardized precipitation evapotranspiration index. The spatial-temporal evolution of droughts is addressed by quantifying the areal extent of regions under moderate, severe and extreme drought from historic to end-century periods. Drought characteristics derived from the models are used to develop severity–duration–frequency curves using an extreme value analysis method based on ordinary events. Under SSP5-8.5, a tenfold increase in the area subject to extreme droughts is projected by the end of the century, while a twofold increase is projected under SSP1-2.6. Increase in extreme droughts frequency is found to be more pronounced in the southern and western regions of Australia. For example, frequency analysis of 12 month duration droughts for the state of South Australia indicates that, under SSP5-8.5, drought severities currently expected to happen on average only once in 100 years could happen as often as once in 3 years by the end of the century, with a 33 times higher risk (from 1% to 33%), while under SSP1-2.6, the increase is fivefold (1%–5%). The significant difference in the increase of drought risk between the two extreme scenarios highlights the urge to reduce greenhouse gases emission in order to avoid extreme drought conditions to become the norm by the end of the century.

 

Biodiversity contributes to the ecological and climatic stability of the Amazon Basin1,2, but is increasingly threatened by deforestation and fire3,4. Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079–189,755 km2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3–85.2% of species that are listed as threatened in this region5. The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253–10,343 km2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon. 

Water resources reanalysis (WRR) can be used as a numerical tool to advance our understanding of hydrological processes where in situ observations are limited. However, WRR products are associated with uncertainty that needs to be quantified to improve usability of such products in water resources applications. In this study, we evaluate estimates of water cycle components from 18 state-of-the-art WRR datasets derived from different land surface/hydrological models, meteorological forcing, and precipitation datasets. The evaluation was conducted at three spatial scales in the upper Blue Nile basin in Ethiopia. Precipitation, streamflow, evapotranspiration (ET), and terrestrial water storage (TWS) were evaluated against in situ daily precipitation and streamflow measurements, remote sensing–derived ET, and the NASA Gravity Recovery and Climate Experiment (GRACE) product, respectively. Our results highlight the current strengths and limitations of the available WRR datasets in analyzing the hydrological cycle and dynamics of the study basins, showing an overall underestimation of ET and TWS and overestimation of streamflow. While calibration improves streamflow simulation, it results in a relatively poorer performance in terms of ET. In addition, we show that the differences in the schemes used in the various land surface models resulted in significant differences in the estimation of the water cycle components from the respective WRR products, while we noted small differences among the products related to precipitation forcing. We did not identify a single product that consistently outperformed others; however, we found that there are specific WRR products that provided accurate representation of a single component of the water cycle (e.g., only runoff) in the area.