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California has experienced enhanced extreme wildfire behaviour in recent years1–3, leading to substantial loss of life and property4,5. Some portion of the change in wildfire behaviour is attributable to anthropogenic climate warming, but formally quantifying this contribution is difficult because of numerous confounding factors6,7 and because wildfires are below the grid scale of global climate models. Here we use machine learning to quantify empirical relationships between temperature (as well as the influence of temperature on aridity) and the risk of extreme daily wildfire growth (>10,000 acres) in California and find that the influence of temperature on the risk is primarily mediated through its influence on fuel moisture. We use the uncovered relationships to estimate the changes in extreme daily wildfire growth risk under anthropogenic warming by subjecting historical fires from 2003 to 2020 to differing background climatological temperatures and aridity conditions. ....
Earth system models and various climate proxy sources indicate global warming is unprecedented during at least the Common Era1. However, tree-ring proxies often estimate temperatures during the Medieval Climate Anomaly (950–1250 ce) that are similar to, or exceed, those recorded for the past century2,3, in contrast to simulation experiments at regional scales4. This not only calls into question the reliability of models and proxies but also contributes to uncertainty in future climate projections5. Here we show that the current climate of the Fennoscandian Peninsula is substantially warmer than that of the medieval period. This highlights the dominant role of anthropogenic forcing in climate warming even at the regional scale, thereby reconciling inconsistencies between reconstructions and model simulations. We used an annually resolved 1,170-year-long tree-ring record that relies exclusively on tracheid anatomical measurements from Pinus sylvestris trees, provi ....
Human activities greatly impact surface water quality, while being reliant upon it for water supply. Surface water quality is expected to change in the future as a result of alterations to pollutant loadings, surface water withdrawals and hydrological regimes, driven by both climate change and socio-economic developments. Here we use a high-resolution global surface water quality model to project water temperature and indicators of salinity (total dissolved solids), organic (biological oxygen demand) and pathogen (fecal coliform) pollution until 2100. The results show that while surface water quality, as indicated by these pollutants, will improve in most advanced economies, the outlook for poorer nations is bleak. The proportion of the global population exposed to salinity, organic and pathogen pollution by the end of the century ranges from 17 to 27%, 20 to 37% and 22 to 44%, respectively, with poor surface water quality disproportionately affecting people living in developing countr ....
Observational evidence shows the ubiquitous presence of ocean-emitted short-lived halogens in the global atmosphere1–3. Natural emissions of these chemical compounds have been anthropogenically amplified since pre-industrial times4–6, while, in addition, anthropogenic short-lived halocarbons are currently being emitted to the atmosphere7,8. Despite their widespread distribution in the atmosphere, the combined impact of these species on Earth’s radiative balance remains unknown. Here we show that short-lived halogens exert a substantial indirect cooling effect at present (−0.13 ± 0.03 watts per square metre) that arises from halogen-mediated radiative perturbations of ozone (−0.24 ± 0.02 watts per square metre), compensated by those from methane (+0.09 ± 0.01 watts per square metre), aerosols (+0.03 ± 0.01 watts per square metre) and stratospheric water vapour (+0.01 ....
Controlling bioenergy-induced land-use-change emissions is key to exploiting bioenergy for climate change mitigation. However, the effect of different land-use and energy sector policies on specific bioenergy emissions has not been studied so far. Using the global integrated assessment model REMIND-MAgPIE, we derive a biofuel emission factor (EF) for different policy frameworks. We find that a uniform price on emissions from both sectors keeps biofuel emissions at 12 kg CO2 GJ−1. However, without land-use regulation, the EF increases substantially (64 kg CO2 GJ−1 over 80 years, 92 kg CO2 GJ−1 over 30 years). We also find that comprehensive coverage (>90%) of carbon-rich land areas worldwide is key to containing land-use emissions. Pricing emissions indirectly on the level of bioenergy consumption reduces total emissions by cutting bioenergy demand but fails to reduce the average EF. In the absence of compreh ....