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Abstract Previous research has examined individual factors contributing to wildfire risk, but the compounding effects of these factors remain underexplored. Here, we introduce the “Integrated Human-centric Wildfire Risk Index (IHWRI)” to quantify the compounding effects of fire-weather intensification and anthropogenic factors—including ignitions and human settlement into wildland—on wildfire risk. While climatic trends increased the frequency of high-risk fire-weather by 2.5-fold, the combination of this trend with wildland-urban interface expansion led to a 4.1-fold increase in the frequency of conditions conducive to extreme-impact wildfires from 1990 to 2022 across California. More than three-quarters of extreme-impact wildfires—defined as the top 20 largest, most destructive, or deadliest events on record—originated within 1 km from the wildland-urban interface. The deadliest and most destructive wildfires—90% of which were human-caused—primarily occurred in the fall, while the largest wildfires—56% of which were human-caused—mostly took place in the summer. By integrating human activity and climate change impacts, we provide a holistic understanding of human-centric wildfire risk, crucial for policy development. 

Abstract GRACE (Gravity Recovery and Climate Experiment) has been widely used to evaluate terrestrial water storage (TWS) and groundwater storage (GWS). However, the coarse‐resolution of GRACE data has limited the ability to identify local vulnerabilities in water storage changes associated with climatic and anthropogenic stressors. This study employs high‐resolution (1 km²) GRACE data generated through machine learning (ML) based statistical downscaling to illuminate TWS and GWS dynamics across twenty sub‐regions in the Indus Basin. Monthly TWS and GWS anomalies obtained from a geographically weighted random forest (RF_gw) model maintained good consistency with original GRACE data at the 25 km²grid scale. The downscaled data at 1 km²resolution illustrate the spatial heterogeneity of TWS and GWS depletion within each sub‐region. Comparison with in‐situ GWS from 2,200 monitoring wells shows that downscaling of GRACE data significantly improves agreement with in‐situ data, evidenced by higher Kling‐Gupta Efficiency (0.50–0.85) and correlation coefficients (0.60–0.95). Hotspots with the highest TWS and GWS decline rate between 2002 and 2023 were Dehli Doab (−442, −585 mm/year), BIST Doab (−367, −556 mm/year), Rajasthan (−242, −381 mm/year), and BARI (−188, −333 mm/year). Based on a general additive model, 47%–83% of the TWS decline was associated with anthropogenic stressors mainly due to increasing trends of crop sown area, water consumption, and human settlements. The decline rate of TWS and GWS anomalies was lower (i.e., −25 to −75 mm/year) in upstream sub‐regions (e.g., Yogo, Gilgit, Khurmong, Kabul) where climatic factors (downward shortwave radiations, air temperature, and sea surface temperature) explained 72%–91% of TWS/GWS changes. The relative influences of climatic and anthropogenic stressors varied across sub‐regions, underscoring the complex interplay of natural‐human activities in the basin. These findings inform place‐based water resource management in the Indus Basin by advancing the understanding of local vulnerabilities. 

Although half of Earth’s population resides in the wildland-urban interface, human exposure to wildland fires remains unquantified. We show that the population directly exposed to wildland fires increased 40% globally from 2002 to 2021 despite a 26% decline in burned area. Increased exposure was mainly driven by enhanced colocation of wildland fires and human settlements, doubling the exposure per unit burned area. We show that population dynamics accounted for 25% of the 440 million human exposures to wildland fires. Although wildfire disasters in North America, Europe, and Oceania have garnered the most attention, 85% of global exposures occurred in Africa. The top 0.01% of fires by intensity accounted for 0.6 and 5% of global exposures and burned area, respectively, warranting enhanced efforts to increase fire resilience in disaster-prone regions. 

ABSTRACT China's pursuit of carbon neutrality targets hinges on a profound shift towards low-carbon energy, primarily reliant on intermittent and variable, yet crucial, solar and wind power sources. In particular, low-solar-low-wind (LSLW) compound extremes present a critical yet largely ignored threat to the reliability of renewable electricity generation. While existing studies have largely evaluated the impacts of average climate-induced changes in renewable energy resources, comprehensive analyses of the compound extremes and, particularly, the underpinning dynamic mechanisms remain scarce. Here we show the dynamic evolution of compound LSLW extremes and their underlying mechanisms across China via coupling multi-model simulations with diagnostic analysis. Our results unveil a strong topographic dependence in the frequency of compound LSLW extremes, with a national average frequency of 16.4 (10th–90th percentile interval ranges from 5.3 to 32.6) days/yr, when renewable energy resources in eastern China are particularly compromised (∼80% lower than that under an average climate). We reveal a striking increase in the frequency of LSLW extremes, ranging from 12.4% under SSP126 to 60.2% under SSP370, primarily driven by both renewable energy resource declines and increasingly heavily-tailed distributions, resulting from weakened meridional temperature (pressure) gradient, increased frequency of extremely dense cloud cover and additional distinctive influence of increased aerosols under SSP370. Our study underscores the urgency of preparing for significantly heightened occurrences of LSLW events in a warmer future, emphasizing that such climate-induced compound LSLW extreme changes are not simply by chance, but rather projectable, thereby underscoring the need for proactive adaptation strategies. Such insights are crucial for countries navigating a similar transition towards renewable energy. 

The continuous escalation of carbon dioxide (CO2) emissions into the atmosphere is recognized as the primary catalyst for anthropogenic climate change. In 2021, CO2 emerged as the predominant contributor to the warming effect of all human-made greenhouse gases (GHGs), accounting for two-thirds of their global heating impact. While the primary anthropogenic source of increased atmospheric CO2 concentration is the combustion of fossil fuels, the largest terrestrial source of CO2 emissions is soil where 80% of the total terrestrial carbon is stored. Approximately 62% of soil carbon is in organic form and readily released as CO2, while the remaining is made up of inorganic carbon (SIC). Here, we postulate that there is an amplifying feedback loop between drought, soil desiccation cracking, and CO2 emission in a warming climate – a critical aspect that has been overlooked in the existing literature. Further, we argue that the postulated feedback loop affects the emissions of other GHGs, such as methane (CH4) and nitrous oxide (N2O), from soils. The urgent need to recognize and characterize this exacerbating feedback loop is twofold. Firstly, it is widely acknowledged that drought accelerates the oxidation of soil organic carbon (SOC) and, thus, increases CO2 emissions into the atmosphere. Drought-induced soil moisture deficits differentially affect plant processes; while photosynthesis rates may be reduced in plants, leading to decreased carbon uptake, respiration rates can vary. Initially, drought may cause a slight increase in respiration, despite a decline in photosynthesis, leading to increased carbon emissions from the soil. These effects can differ based on ecosystem types, highlighting the complex interplay between drought, photosynthesis, and respiration. Secondly, drought triggers soil desiccation cracking, substantially increasing the permeability of the soil and the interfacial exchange area between the atmosphere and the soil, which, in turn, can considerably increase CO2 efflux in soil by exposing deeper and older stores of soil carbon. Desiccation cracking threatens earthen infrastructure systems and the natural environment. The problems associated with desiccation cracks are becoming more prevalent as anthropogenic climate change exacerbates the severity and frequency of droughts, heatwaves, and drought-heavy precipitation cycles (4). As the warming trends continue, more (and possibly older) CO2 is released from the soil, which can further contribute to global warming. Thus, a chain of events happens in a cascading manner. Failure to consider the hypothesized feedback loop can result in significant inaccuracies when modeling and predicting GHG emissions from soil. It may also lead to underestimating the overall impact of climate change on critical aspects such as soil health, crop production, and the structural integrity of earthen infrastructure. 

Globally, land subsidence (LS) often adversely impacts infrastructure, humans, and the environment. As climate change intensifies the terrestrial hydrologic cycle and severity of climate extremes, the interplay among extremes (e.g., floods, droughts, wildfires, etc.), LS, and their effects must be better understood since LS can alter the impacts of extreme events, and extreme events can drive LS. Furthermore, several processes causing subsidence (e.g., ice‐rich permafrost degradation, oxidation of organic matter) have been shown to also release greenhouse gases, accelerating climate change. Our review aims to synthesize these complex relationships, including human activities contributing to LS, and to identify the causes and rates of subsidence across diverse landscapes. We primarily focus on the era of synthetic aperture radar (SAR), which has significantly contributed to advancements in our understanding of ground deformations around the world. Ultimately, we identify gaps and opportunities to aid LS monitoring, mitigation, and adaptation strategies and guide interdisciplinary efforts to further our process‐based understanding of subsidence and associated climate feedbacks. We highlight the need to incorporate the interplay of extreme events, LS, and human activities into models, risk and vulnerability assessments, and management practices to develop improved mitigation and adaptation strategies as the global climate warms. Without consideration of such interplay and/or feedback loops, we may underestimate the enhancement of climate change and acceleration of LS across many regions, leaving communities unprepared for their ramifications. Proactive and interdisciplinary efforts should be leveraged to develop strategies and policies that mitigate or reverse anthropogenic LS and climate change impacts.