In response to the important benefits forests provide, there is a growing effort to reforest the world. Past policies and current commitments indicate that many of these forests will be plantations. Since plantations often replace more carbon-rich or biodiverse land covers, this approach to forest expansion may undermine objectives of increased carbon storage and biodiversity. We use an econometric land use change model to simulate the carbon and biodiversity impacts of subsidy driven plantation expansion in Chile between 1986 and 2011. A comparison of simulations with and without subsidies indicates that payments for afforestation increased tree cover through expansion of plantations of exotic species but decreased the area of native forests. Chile’s forest subsidies probably decreased biodiversity without increasing total carbon stored in aboveground biomass. Carefully enforced safeguards on the conversion of natural ecosystems can improve both the carbon and biodiversity outcomes of reforestation policies.

Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from fire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the US. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the US, a number increasing by 1 million houses every 3 years. Using a statistical model that links satellite-based fire and smoke data to pollution monitoring stations, we estimate that wildfires have accounted for up to 25% of PM_2.5 in recent years across the US, and up to half in some Western regions. We then show that ambient exposure to smoke-based PM_2.5 does not follow traditional socioeconomic exposure gradients. Finally, using stylized scenarios, we show that fuels management interventions have large but uncertain impacts on health outcomes, and that future health impacts from climate-change-induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change. We draw lessons for research and policy.

Floods and other climate hazards pose a widespread and growing threat to housing and infrastructure around the world. By incorporating climate risk into asset prices, markets can discourage excessive development in hazardous areas. However, the extent to which markets actually price these risks remains poorly understood. Here we measure the effect of information about flood risk on residential property values in the United States. Using multiple empirical approaches and two decades of sales data covering the universe of homes in the US, we find little evidence that housing markets fully price information about flood risk in aggregate. However, the price penalty for flood risk is larger for commercial buyers and in states where sellers must disclose information about flood risk to potential buyers, suggesting that policies to improve risk communication could influence market outcomes. Our findings indicate that floodplain homes in the US are currently overvalued by a total of $34B, raising concerns about the stability of real estate markets as climate risks become more salient and severe.

California has experienced devastating autumn wildfires in recent years. These autumn wildfires have coincided with extreme fire weather conditions during periods of strong offshore winds coincident with unusually dry vegetation enabled by anomalously warm conditions and late onset of autumn precipitation. In this study, we quantify observed changes in the occurrence and magnitude of meteorological factors that enable extreme autumn wildfires in California, and use climate model simulations to ascertain whether these changes are attributable to human-caused climate change. We show that state-wide increases in autumn temperature (~1 ˚C) and decreases in autumn precipitation (~30%) over the past four decades have contributed to increases in aggregate fire weather indices (+20%). As a result, the observed frequency of autumn days with extreme (95th percentile) fire weather – which we show are preferentially associated with extreme autumn wildfires – has more than doubled in California since the early 1980s. We further find an increase in the climate model-estimated probability of these extreme autumn conditions since ~1950, including a long-term trend toward increased same-season co-occurrence of extreme fire weather conditions in northern and southern California. Our climate model analyses suggest that continued climate change will further amplify the number of days with extreme fire weather by the end of this century, though a pathway consistent with the UN Paris commitments would substantially curb that increase. Given the acute societal impacts of extreme autumn wildfires in recent years, our findings have critical relevance for ongoing efforts to manage wildfire risks in California and other regions.

Independent verification of anthropogenic influence on specific extreme climate events remains elusive. This study presents a framework for such verification. This framework reveals that previously published results based on a 1961–2005 attribution period frequently underestimate the influence of global warming on the probability of unprecedented extremes during the 2006–2017 period. This underestimation is particularly pronounced for hot and wet events, with greater uncertainty for dry events. The underestimation is reflected in discrepancies between probabilities predicted during the attribution period and frequencies observed during the out-of-sample verification period. These discrepancies are most explained by increases in climate forcing between the attribution and verification periods, suggesting that 21st-century global warming has substantially increased the probability of unprecedented hot and wet events. Hence, the use of temporally lagged periods for attribution—and, more broadly, for extreme event probability quantification—can cause underestimation of historical impacts, and current and future risks.

Researchers including David Lobell analyze how human-caused climate change has impacted a water deficit in Southern Africa and might contribute to a rising food security crisis in the region.

Many mountainous and high‐latitude regions have experienced more precipitation as rain rather than snow due to warmer winter temperatures. Further decreases in the annual snow fraction are projected under continued global warming, with potential impacts on flood risk. Here, we quantify the size of streamflow peaks in response to both seasonal and event‐specific rain‐fraction using stream gage observations from watersheds across the western United States. Across the study watersheds, the largest rainfall‐driven streamflow peaks are >2.5 times the size of the largest snowmelt‐driven peaks. Using a panel regression analysis of individual precipitation and snowmelt events, we show that the empirical streamflow response grows approximately exponentially as the liquid precipitation input increases, with rain‐dominated runoff leading to proportionately larger streamflow increases than snowmelt or mixed rain‐and‐snow runoff. We find that the response to changes in rain percentage is largest in the wettest watersheds, where wet antecedent conditions are important for increasing runoff efficiency. Similarly, the effect of rain percentage is larger across watersheds in the Northwest and West regions compared to watersheds in the Northern Rockies and Southwest regions. Overall, as a higher percentage of precipitation falls as rain, increases in the size of rainfall‐driven and “rain‐on‐snow”‐driven floods have the potential to more than offset decreases in the size of snowmelt‐driven floods.

Efficient responses to climate change require accurate estimates of both aggregate damages and where and to whom they occur. While specific case studies and simulations have suggested that climate change disproportionately affects the poor, large-scale direct evidence of the magnitude and origins of this disparity is lacking. Similarly, evidence on aggregate damages, which is a central input into the evaluation of mitigation policy, often relies on country-level data whose accuracy has been questioned. Here we assemble longitudinal data on economic output from over 11,000 districts across 37 countries, including previously nondigitized sources in multiple languages, to assess both the aggregate and distributional impacts of warming temperatures. We find that local-level growth in aggregate output responds non-linearly to temperature across all regions, with output peaking at cooler temperatures (<10°C) than estimated in earlier country analyses and declining steeply thereafter. Long difference estimates of the impact of longer-term (decadal) trends in temperature on income are larger than estimates from an annual panel model, providing additional evidence for growth effects. Impacts of a given temperature exposure do not vary meaningfully between rich and poor regions, but exposure to damaging temperatures is much more common in poor regions. These results indicate that additional warming will exacerbate inequality, particularly across countries, and that economic development alone will be unlikely to reduce damages, as commonly hypothesized. We estimate that since 2000, warming has already cost both the US and the EU at least $4 trillion in lost output, and tropical countries are >5% poorer than they would have been without this warming.

Understanding the causes of economic inequality is critical for achieving equitable economic development. To investigate whether global warming has affected the recent evolution of inequality, we combine counterfactual historical temperature trajectories from a suite of global climate models with extensively replicated empirical evidence of the relationship between historical temperature fluctuations and economic growth. Together, these allow us to generate probabilistic country-level estimates of the influence of anthropogenic climate forcing on historical economic output. We find very high likelihood that anthropogenic climate forcing has increased economic inequality between countries. For example, per capita gross domestic product (GDP) has been reduced 17–31% at the poorest four deciles of the population-weighted country-level per capita GDP distribution, yielding a ratio between the top and bottom deciles that is 25% larger than in a world without global warming. As a result, although between-country inequality has decreased over the past half century, there is ∼90% likelihood that global warming has slowed that decrease. The primary driver is the parabolic relationship between temperature and economic growth, with warming increasing growth in cool countries and decreasing growth in warm countries. Although there is uncertainty in whether historical warming has benefited some temperate, rich countries, for most poor countries there is >90% likelihood that per capita GDP is lower today than if global warming had not occurred. Thus, our results show that, in addition to not sharing equally in the direct benefits of fossil fuel use, many poor countries have been significantly harmed by the warming arising from wealthy countries’ energy consumption.