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As the climate warms, extended drought and heat events in the United States are driving an increase in acres burned and homes lost to wildfire. The most devastating wildfires happen when dry winds carry embers long distances, start spot fires and ignite homes. Burning homes then become the fuel that ignites other nearby homes, causing mass conflagrations. Today wildfire is largely approached as a problem that can be controlled through vegetation treatments and firefighting, but that strategy has not stopped the loss of homes and even entire communities. However, new observational and analytical tools have given firefighters, governments, and the public a better understanding of wildfire and how to prepare for it. By redefining the wildfire problem as a home ignition problem, communities can survive even extreme fires and can safely reintroduce fire to the land. [ABSTRACT FROM AUTHOR]

Hailstorms are analyzed across the United States using explicit hailstone size calculations from convection-permitting regional climate simulations for historical, mid-century, and end of twenty-first-century epochs. Near-surface hailstones <4 cm are found to decrease in frequency by an average of 25%, whereas the largest stones are found to increase by 15–75% depending on the greenhouse gas emissions pathway. Decreases in the frequency of near-surface severe hail days are expected across the U.S. High Plains, with 2–4 fewer days projected—primarily in summer. Column-maximum severe hail days are projected to increase robustly in most locations outside of the southern Plains, a distribution that closely mimics projections of thunderstorm days. Primary mechanisms for the changes in hailstone size are linked to future environments supportive of greater instability opposed by thicker melting layers. This results in a future hailstone size dichotomy, whereby stronger updrafts promote more of the largest hailstones, but significant decreases occur for a majority of smaller diameters due to increased melting. [ABSTRACT FROM AUTHOR]

In line with global warming, decarbonization of economies is a much-discussed topic in climate policies and economic forecasts. However, estimating the output cost of decarbonizing economies has not received attention. Therefore, this study examines the costs of decarbonization in the USA, the leading country in the global economy, by proposing a "Green Sacrifice Ratio" based on estimating the output costs of emission abatement policy. To do this, the study employs Structural Vector Autoregression analysis to measure the Green Sacrifice Ratio in the USA from 1973/Q1 to 2023/Q2. The empirical results show that a permanent 1% reduction in carbon emissions results in a cumulative loss of 0.0001% of output in the USA. The implication is that the cost of decarbonization in the USA can be lower than the economic burden of environmental pollution. Therefore, policymakers in the USA should take determined actions to prevent irreversible environmental degradation and avoid heavy economic costs in the future. [ABSTRACT FROM AUTHOR]

Near‐term projections of drought in the southwestern United States (SWUS) are uncertain. The observed decrease in SWUS precipitation since the 1980s and heightened drought conditions since the 2000s have been linked to a cooling sea surface temperature (SST) trend in the Equatorial Pacific. Notably, climate models fail to reproduce these observed SST trends, and they may continue doing so in the future. Here, we assess the sensitivity of SWUS precipitation projections to future SST trends using a Green's function approach. Our findings reveal that a slight redistribution of SST leads to a wetting or drying of the SWUS. A reversal of the observed cooling trend in the Central and East Pacific over the next few decades would lead to a period of wetting in the SWUS. It is critical to consider the impact of possible SST pattern trends on SWUS precipitation trends until we fully trust SST evolution in climate models. Plain Language Summary: Precipitation trends in the southwestern United States (SWUS) are sensitive to the pattern of sea surface temperature (SST) trends in the Tropical Pacific. Since the turn of the century, a decrease in SWUS precipitation has been linked to a cooling of the Central and Eastern Pacific (1990–2020). Notably, climate models are unable to simulate this observed cooling SST trend. In this study, we answer how SWUS precipitation projections may be impacted by potential error in the simulation of future SST trends by climate models. We first demonstrate that slight changes in the pattern of SST trends leads to either a wetting or drying of the SWUS. Second, if the current 30‐year cooling trend in the Central and East Pacific switches to a warming trend, the SWUS could experience a near‐term increase in precipitation. While climate models are the main tool to predict the global response to anthropogenic climate change, we must consider and account for their error in projections of global warming. Key Points: The observed Equatorial Pacific cooling trend, unpredicted by climate models, may have led to decreased precipitation in the southwestern USWith a sea surface temperature‐precipitation Green's function, we find that small changes in sea surface temperature can either wet or dry the southwestern USA reversal of the cooling trend in the Equatorial Pacific could lead to a wetting trend in the southwestern US [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are often built upon the "niche conservatism" assumption, such that they ignore the possibility of "evolutionary rescue" and may underestimate species' future range limits under climate change. We select aphids and ladybirds as model species and develop an eco‐evolutionary model to explore evolutionary rescue in a predator–prey system under climate change. We model the adaptive change of species' thermal performances, accounting for biotic interactions. Our study suggests that, without considering evolutionary adaptation, the warming climate will result in a reduction in aphid populations and the extinction of ladybirds in large parts of the United States. However, when incorporating evolutionary adaptation into the model, aphids can adapt to climate change, whereas ladybirds demonstrate geographic variation in their evolutionary rescue potential. Specifically, ladybirds in southern regions are more likely to be rescued than those in the north. In certain northern regions, ladybirds do not avoid extinction due to severe warming trends and seasonality of the climate. While higher warming trends do prompt stronger evolutionary changes in phenotype, they also lead to reduced aphid population abundance such that ecology constrains ladybird population growth. Higher seasonality induces an ecological effect by limiting the length of reproductive season, thereby reducing the capacity for evolutionary rescue. Together, these findings reveal the complex interplay between ecological and evolutionary dynamics in the context of evolutionary adaptation to climate change. [ABSTRACT FROM AUTHOR]

As climate change impacts increase, communicators must engage as many audiences as possible in climate action. One potentially underrated audience is video gamers. Two-thirds of Americans play video games, and video games are a potentially effective climate change communication tool. However, little research has examined whether video gamers have unique value as a target audience for climate communication, and if they do, what might be effective ways to reach them. To address this need, we use two surveys including self-identified video game players in the United States to measure their current engagement with climate change, including through video gaming. In Study 1, a nationally representative survey in the United States (N = 1,006), we found that being a video gamer was slightly positively associated with intentions to take collective action on global warming. In Study 2, restricted to gamers in the United States (N = 2,034), we found that having more friends and family who played video games, and/or being exposed to global warming content in gaming, were also positively associated with collective action intentions. These findings were consistent even after controlling for potential confounding variables such as age, political party, and global warming attitudes. Results suggest that video gamers are a worthwhile potential audience for future climate change communication, combatting the stereotype of video gamers as disengaged or antisocial, at least in the context of climate change. Our study also identifies several potential avenues for future communication with video gamers, particularly outreach to and engagement with gaming communities. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are crucial components of the hydrological cycle and often produce flash floods. Given their impact, it is important to understand how they will change under a warming climate. This study uses a satellite‐ and radar‐based MCS tracking algorithm on convection‐permitting climate model simulations and examines changes in MCS properties and precipitation structures between historical and future simulations. An underestimation in MCS total precipitation is evident in historical simulation compared to observations, due to model's depiction of MCS precipitation area and summertime occurrence frequency. Under pseudo‐global warming, increases in MCS frequency and total warm season precipitation are observed, most notably in the southern U.S. The precipitation intensity and precipitating area generated by future MCSs also rises and results in an increase in precipitation volume. MCS precipitation structures are further classified into convective core and stratiform regions to understand how change in these structures contributes to future rainfall changes. In a warmer climate, the stratiform region demonstrates minimal change in size, but increases in mean precipitation rate and mean maximum precipitation rate by 15% and 29% are noted, respectively. A more robust future response is observed in the convective core region, with its size, mean precipitation rate and mean maximum precipitation rate increasing significantly by 24%, 37% and 42%, respectively. Finally, by examining the environmental properties of MCS initial condition, future intensification of convective rain may be attributed to a combined effect of substantial increases in atmospheric instability and moisture availability. Plain Language Summary: Thunderstorms that group together and grow to hundreds of kilometers in size and persist for more than a few hours are called mesoscale convective systems. They play an important role in Earth's water cycle and are often responsible for causing flash flooding events. Given their impact, understanding how they will change due to a warming climate is crucial. By analyzing the outputs from climate models, this study reveals future changes in various aspects of mesoscale storms behaviors, such as their frequency and where they occur. In addition, the rainfall patterns from the present and future mesoscale storms are compared. Our findings show that in a warmer climate, these storms will probably occur more frequently and bring more rain, especially in the southern parts of the United States. Individual mesoscale storms are also expected to contain larger rain areas and release heavier rainfall, which would contribute to an overall increase in rain volume. A shift from lighter rain to more moderate/heavy rain during these storms is also noticed, implying a potential rise in intense mesoscale storm events and heightened chances of flash floods in the future. Key Points: An Mesoscale convective system (MCS) tracking algorithm is applied to regional climate models to examine the potential future changes in their rainfall characteristicsAn evaluation between observations and historical simulations shows that the model underestimates MCS total precipitationFuture MCSs may become more frequent, more intense and produce higher rain volume, primarily due to the large changes in the convective core [ABSTRACT FROM AUTHOR]

Water temperatures in mountain streams are likely to rise under future climate change, with negative impacts on ecosystems and water quality. However, it is difficult to predict which streams are most vulnerable due to sparse historical records of mountain stream temperatures as well as complex interactions between snowpack, groundwater, streamflow and water temperature. Minimum flow volumes are a potentially useful proxy for stream temperature, since daily streamflow records are much more common. We confirmed that there is a strong inverse relationship between annual low flows and peak water temperature using observed data from unimpaired streams throughout the montane regions of the United States' west coast. We then used linear models to explore the relationships between snowpack, potential evapotranspiration and other climate‐related variables with annual low flow volumes and peak water temperatures. We also incorporated previous years' flow volumes into these models to account for groundwater carryover from year to year. We found that annual peak snowpack water storage is a strong predictor of summer low flows in the more arid watersheds studied. This relationship is mediated by atmospheric water demand and carryover subsurface water storage from previous years, such that multi‐year droughts with high evapotranspiration lead to especially low flow volumes. We conclude that watershed management to help retain snow and increase baseflows may help counteract some of the streamflow temperature rises expected from a warming climate, especially in arid watersheds. [ABSTRACT FROM AUTHOR]

The public nuisance tort is now in a critical stage of development, mostly in the United States but also in other jurisdictions, including civil law systems. It is becoming ever more consequential in practice and, at the same time, widely misunderstood by courts and scholars. Our ambition is to defend a private law theory of public nuisance. Contrary to the view that the underlying rights protected by this tort contrast with private rights (say, to bodily integrity), we argue that these public rights are private rights like any other right in the law of torts since they protect private persons taken severally. And, yet, these private rights are also distinctively public in the sense that they protect the interests of private persons to use and enjoy the public sphere. In that, public nuisance imposes not merely ex post liability for undermining these interests but also, first and foremost, constructs a liberal public sphere. Our case for public nuisance shows that private law extends beyond the private sphere to capture entitlements and responsibilities that do not arise from, or attach to, ownership of land; it also resists the reduction of private law to rights of action and ex post determination of liabilities. More concretely, our reconstruction of public nuisance solves two key doctrinal challenges that the tort struggles with – concerning the standing to sue in public nuisance and the economic loss rule – and it also refines the potentially significant role of this tort in addressing the urgent threat posed by climate change. [ABSTRACT FROM AUTHOR]

Wildfires are a widespread phenomenon that affects every corner of the world with the warming climate. Wildfires burn tens of thousands of square kilometres of forests and vegetation every year in the United States alone with the past decade witnessing a dramatic increase in the number of wildfire incidents. This research aims to understand the regions of forests and vegetation across the US that are susceptible to wildfires using spatiotemporal kernel heat maps and, forecast these wildfires across the United States at country-wide and state levels on a weekly and monthly basis in an attempt to reduce the reaction time of the suppression operations and effectively design resource maps to mitigate wildfires. We employed the state-of-the-art Neural Basis Expansion Analysis for Time Series (N-BEATS) model to predict the total area burned by wildfires by several weeks and months into the future. The model was evaluated based on forecasting metrics including mean-squared error (MSE)., and mean average error (MAE). The N-BEATS model demonstrates improved performance compared to other state-of-the-art (SOTA) models, obtaining MSE values of 116.3, 38.2, and 19.0 for yearly, monthly, and weekly forecasting, respectively. [ABSTRACT FROM AUTHOR]

The public nuisance tort is now in a critical stage of development, mostly in the United States but also in other jurisdictions, including civil law systems. It is becoming ever more consequential in practice and, at the same time, widely misunderstood by courts and scholars. Our ambition is to defend a private law theory of public nuisance. Contrary to the view that the underlying rights protected by this tort contrast with private rights (say, to bodily integrity), we argue that these public rights are private rights like any other right in the law of torts since they protect private persons taken severally. And, yet, these private rights are also distinctively public in the sense that they protect the interests of private persons to use and enjoy the public sphere. In that, public nuisance imposes not merely ex post liability for undermining these interests but also, first and foremost, constructs a liberal public sphere. Our case for public nuisance shows that private law extends beyond the private sphere to capture entitlements and responsibilities that do not arise from, or attach to, ownership of land; it also resists the reduction of private law to rights of action and ex post determination of liabilities. More concretely, our reconstruction of public nuisance solves two key doctrinal challenges that the tort struggles with – concerning the standing to sue in public nuisance and the economic loss rule – and it also refines the potentially significant role of this tort in addressing the urgent threat posed by climate change. [ABSTRACT FROM AUTHOR]

Nonresidential and mid- to high-rise multifamily residential structures in the United States currently use little wood per unit floor area installed, because earlier building codes lacked provisions for structural wood use in those types of buildings. However, revisions to the International Building Code allow for increased wood use in the form of mass timber, as structural and fire safety concerns have been addressed through new science-based design standards and through newly specified construction materials and measures. This study used multiple models to describe alternative futures for new construction, mass timber adoption rates, and the associated carbon benefits in higher than three-story buildings in the United States. The use of mass timber, in place of traditional constructions (i.e., structures dominated by concrete and steel), in projected new higher than three-story buildings was shown to provide combined carbon benefits (i.e., global warming mitigation benefits), including avoided embodied carbon emissions due to the substitution of non-wood alternatives and additional biogenic carbon storage in mass timber materials, of between 9.9 and 16.5 million t CO2e/yr spanning 50 years, 2020 to 2070. These carbon benefits equate to 12% to 20% of the total U.S. harvested wood products carbon storage for 2020. Future research is needed to understand how greater mass timber adoption leads to changes in forest product markets, land use, and total forest sector carbon. [ABSTRACT FROM AUTHOR]

Drought has affected much of the western United States since about the year 2000, including the Upper Colorado River Basin (UCRB). Using a time series of UCRB streamflow derived from a tree‐ring based reconstruction of UCRB streamflow for the years 1 CE through 1905 CE, together with naturalized UCRB streamflow values for 1906 CE through 2021 CE, we identify 51 drought events, including the 2000–2021 drought. Although the recent 2000–2021 drought has been relatively severe, it is not the most severe of the UCRB drought events we identified. Results also indicate that natural variability combined with projected climate warming can result in UCRB drought events that are more severe than any drought since 1 CE. Plain Language Summary: A long and severe drought has affected much of the western United States since about the year 2000 CE, including the Upper Colorado River Basin (UCRB). Comparing this drought to past UCRB droughts (during 1 CE through 2021 CE), we find that the 2000–2021 drought is not the most severe UCRB drought. The results also suggest that natural variability combined with projected climate warming could result in UCRB drought events that are more severe than any drought since 1 CE. Key Points: We identify 51 drought events for the years 1 CE through 2021 CE for the Upper Colorado River Basin (UCRB)Twelve of the 51 UCRB droughts we identify were more severe than the 2000–2021 droughtNatural variability and/or a 1°C temperature increase can trigger UCRB droughts that are more severe than the 2000–2021 drought [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) that undergo rapid intensification (RI) before landfall are notoriously difficult to predict and have caused tremendous damage to coastal regions in the United States. Using downscaled synthetic TCs and physics‐based models for storm tide and rain, we investigate the hazards posed by TCs that rapidly intensify before landfall under both historical and future mid‐emissions climate scenarios. In the downscaled synthetic data, the percentage of TCs experiencing RI is estimated to rise across a significant portion of the North Atlantic basin. Notably, future climate warming causes large increases in the probability of RI within 24 hr of landfall. Also, our analysis shows that RI events induce notably higher rainfall hazard levels than non‐RI events with equivalent TC intensities. As a result, RI events dominate increases in 100‐year rainfall and storm tide levels under climate change for most of the US coastline. Plain Language Summary: Tropical cyclones (TCs) that rapidly intensify (RI) before hitting land are typically hard to predict and cause immense destruction. We used synthetic TCs downscaled from global climate models and physics‐based hazard models to examine the dangers posed by these RI storms in historical and future climates. The TC simulation shows that, as the climate warms, the number of TCs undergoing rapid intensification could rise substantially in the North Atlantic region. Additionally, the likelihood of rapid intensification within 24 hr of landfall significantly increases. These TCs are much riskier, particularly in terms of heavy rainfall, even when compared to equally strong TCs that did not rapidly intensify. Consequently, 100‐year rainfall and storm tide levels will greatly increase under climate change, largely due to the increase of RI events in the future. Key Points: Future climate warming causes large increases in the probability of rapid intensification (RI) within 24 hr of landfallRI events show notably higher rainfall hazard levels than non‐RI events even with equivalent TC intensityChanges in RI events dominate future increases in 100‐year rainfall and storm tide levels for most of the US coastline [ABSTRACT FROM AUTHOR]

Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate. [ABSTRACT FROM AUTHOR]

In this study, we investigated the translation speed and intensity change characteristics for landfalling North American tropical cyclones (TCs) from 1971 to 2020. We calculated three variables—intensity change, mean translation speed, and translation speed change—prior to each TC landfall and investigated the climatology of these variables for seven coastal segments. We found that lower-latitude segments generally had greater positive intensity changes prior to landfall, and higher-latitude segments had greater translation speeds. Longitude primarily influenced translation speed changes, with landfalling TCs along the Atlantic coast of the United States notably accelerating prior to landfall. Temporal trends in each of these variables were inconsistent geographically, but most segments showed an increase in positive intensity changes over time, demonstrating the increasing likelihood of intensifying TCs before landfall in recent years. We defined extreme intensification and extreme weakening as the 90th and 10th percentile of all landfalling TC intensity changes, respectively. We found that extreme intensification and weakening have been increasing and decreasing in frequency, respectively. Results from this study can be used in a variety of future applications, including in operational forecasting and model production, and provide a baseline for climate attribution studies investigating extreme intensity change events. Significance Statement: Landfalling tropical cyclones pose significant hazards to life and property in coastal regions across North America. This study develops a comprehensive climatology of intensity change and translation speed of tropical cyclones during the final 36 h prior to landfall. We found that incidences of extreme intensification and weakening of landfalling North American tropical cyclones have increased and decreased, respectively, since 1971. We also identify lower-latitude coastal segments tend to average faster translation speeds that higher-latitude segments, while segments on the east coast of the United States tended to average a greater acceleration. These results show the importance of looking at tropical cyclone characteristics regionally and provide a useful baseline to assess how tropical cyclone risk is changing in a warming climate. [ABSTRACT FROM AUTHOR]

The host‐generalist two‐spotted spider mite [Tetranychus urticae (Acari: Tetranychidae); TSM] and host‐specialist Banks grass mite [Oligonychus pratensis (Acari: Tetranychidae); BGM] are common pests of corn (Zea mays L.) in the arid western United States. Climate warming and decreased precipitation may promote conditions favoured by these spider mites. However, rapid evolution of spider mite resistance to commercially available acaricides is driving the need for alternative solutions for managing outbreaks. Planting of drought‐tolerant corn hybrids has been proposed to be a dual‐purpose strategy for mitigating water deficits for irrigation and reducing leaf conditions favourable for BGM outbreaks. However, understanding of the mechanisms responsible for reducing the BGM in the field is lacking and determining whether outbreaks of the TSM can also be averted using drought‐tolerant corn is a pressing concern. We conducted a 2‐year field study testing a drought‐tolerant corn hybrid and an analogous drought‐susceptible hybrid under water‐stress, with artificially infested spider mite populations. Drought‐tolerant corn had larger stem diameter, more massive cobs, and greater leaf water mass compared to the drought‐susceptible corn under water stress. We also found that the BGM populations were reduced on drought‐tolerant plants under water‐stress, as expected, but we found an opposite trend in the TSM. Lastly, water‐stressed leaves were warmer, transpired less, and had higher carbon concentration, which contributed to larger investment in eggs and growth in the BGM. We anticipate that further evaluation of irrigation and crop drought‐tolerance in management of agriculture systems for multiple pest species will be increasingly impactful in arid regions. [ABSTRACT FROM AUTHOR]

High‐resolution regional climate model (RCM) simulations of global warming consistently predict larger percentage increases in precipitation in the lee of midlatitude mountain ranges than on their windward slopes, indicating a weakening of the orographic rain shadow. This redistribution of precipitation could have profound consequences for water resources and ecosystems, but its underlying mechanisms are unknown. Here we show that rain‐shadow weakening is just one manifestation of a more general decrease in the influence of orography on precipitation under global warming. We introduce a simple model of precipitation change based on this principle, and find that it agrees well with an ensemble of high‐resolution simulations performed over the western United States. We argue that diminished orographic influence can be explained by the unique vertical structure of orographically forced ascent, which tends to maximize in the lower atmosphere where condensation is thermodynamically less sensitive to warming. Plain Language Summary: Mountains supply about half of the fresh water used by humans globally and often regulate the seasonal cycle of stream flows by accumulating snowpack during the wet season and releasing it over the dry season. Regional simulations tend to predict large future changes in the spatial pattern of precipitation in mountainous regions, but the reasons for these changes are not well understood. Here we show that the predicted patterns of precipitation change in the western US can be explained by a simple mechanism that causes the influence of mountains to weaken with increasing temperatures. We introduce a simple model of precipitation change based on this effect, and show that its predictions closely match those of far more sophisticated regional simulations of future warming over the western US. Key Points: Orographic influence on precipitation is reduced in simulations of global warmingFractional precipitation change scaled by warming is reproducible with a simple model [ABSTRACT FROM AUTHOR]

Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitation P and temperature T footprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonal P and T (e.g., R2 = 0.50 for May–September T). These were disaggregated to monthly values, which were then routed through a water balance model to generate "indirectly" reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r = 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change. Significance Statement: We show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems help mitigate global warming by sequestering atmospheric carbon dioxide (CO2) through plant photosynthesis, the rate of which is affected by surface ozone (O3) and aerosols under simultaneous impacts of climate change and rising CO2. While the changes in anthropogenic emissions perturb atmospheric components, their consequent impacts on ecosystem productivity in the future climate remain unclear. Here, we apply a fully coupled climate‐chemistry‐vegetation model, ModelE2‐YIBs, to explore the effects of O3 and aerosols from anthropogenic emissions on global gross primary productivity (GPP) under different emission scenarios at 2060. At the present day, anthropogenic air pollutants induce a GPP loss of −1.67 Pg[C] (−4%) in boreal summer with the contributions of −2.18 Pg[C] by O3 and +0.52 Pg[C] by aerosols. At 2060, the detrimental effect of air pollutants on GPP is exacerbated to −1.85 Pg[C] under a high emissions scenario but alleviated to −0.59 Pg[C] under a low emission scenario. The mitigated GPP loss in the latter scenario is owing to the effective control of anthropogenic emissions that on average reduces surface O3 concentrations by 8.14 ppbv globally relative to 2010. Although the CO2 fertilization effect is weaker in the low emission scenario, the strong decline in air pollutants brings additional GPP gains compared to the high scenario. Regionally, such GPP amelioration is close to or even overweighs the CO2 fertilization effect in eastern China and United States, suggesting that the deep cut of anthropogenic emissions can effectively promote future ecosystem productivity over the nowadays polluted regions. Plain Language Summary: Terrestrial ecosystems play a crucial role in reducing global warming through plant photosynthesis. However, this process is sensitive to the changes in environmental factors such as climate, CO2, and air pollutants. Here, we use a climate‐chemistry‐vegetation coupled model to project global ecosystem productivity by the 2060, taking into account impacts of surface ozone and aerosols under simultaneous impacts of climate change and rising CO2. We found that air pollutants result in a 4% loss of global plant productivity during the boreal summer mainly due to the detrimental effects of ozone. By the year 2060, this negative effect could worsen under a high emission scenario but improve under a low emission scenario. The better outcome in the low emission scenario is largely due to a significant reduction in ozone levels, which results from effective control of human‐caused emissions. Regionally, the pollution‐induced improvement in plant productivity shows the highest gains in eastern China and the United States. It suggests that the deep cut of human emissions helps increase ecosystem carbon uptake in the top two carbon emitter countries even with weakened CO2 fertilization effects under the carbon neutrality. Key Points: Anthropogenic ozone and aerosols reduce summertime GPP by 4% at present dayThis GPP loss can be significantly decreased with the deep cut of anthropogenic emissionsThe GPP recovery by air pollution control is comparable to CO2 fertilization in China and United States [ABSTRACT FROM AUTHOR]

Climate warming, land use change, and altered fire regimes are driving ecological transformations that can have critical effects on Earth's biota. Fire refugia—locations that are burned less frequently or severely than their surroundings—may act as sites of relative stability during this period of rapid change by being resistant to fire and supporting post‐fire recovery in adjacent areas. Because of their value to forest ecosystem persistence, there is an urgent need to anticipate where refugia are most likely to be found and where they align with environmental conditions that support post‐fire tree recruitment. Using biophysical predictors and patterns of burn severity from 1180 recent fire events, we mapped the locations of potential fire refugia across upland conifer forests in the southwestern United States (US) (99,428 km2 of forest area), a region that is highly vulnerable to fire‐driven transformation. We found that low pre‐fire forest cover, flat slopes or topographic concavities, moderate weather conditions, spring‐season burning, and areas affected by low‐ to moderate‐severity fire within the previous 15 years were most commonly associated with refugia. Based on current (i.e., 2021) conditions, we predicted that 67.6% and 18.1% of conifer forests in our study area would contain refugia under moderate and extreme fire weather, respectively. However, potential refugia were 36.4% (moderate weather) and 31.2% (extreme weather) more common across forests that experienced recent fires, supporting the increased use of prescribed and resource objective fires during moderate weather conditions to promote fire‐resistant landscapes. When overlaid with models of tree recruitment, 23.2% (moderate weather) and 6.4% (extreme weather) of forests were classified as refugia with a high potential to support post‐fire recruitment in the surrounding landscape. These locations may be disproportionately valuable for ecosystem sustainability, providing habitat for fire‐sensitive species and maintaining forest persistence in an increasingly fire‐prone world. [ABSTRACT FROM AUTHOR]

Climate change mitigation depends on actions that affect the public interest and lead to widespread changes in public attitudes and behavior. With the global outbreak of the COVID-19 pandemic, humanity faced a more imminent threat to its well-being and viability. This retrospective cross-sectional study examines how public interest in climate change was attenuated by the severity of the COVID-19 pandemic using Google Trends Search Volume Index (SVI), weather, and climate data on a United States state-level basis during the first two years of the pandemic from 2020 to 2022. To identify channels through which the COVID-19 pandemic affected information demand on climate change, a novel fixed effect regression model of public climate change interest was developed. The measure captures changes in the climate change SVI independent of weather and climate conditions, comprising pandemic-related changes in living circumstances such as COVID-19-related cases and deaths, mask mandates, and the proportion of the vaccinated population. Our results indicate that public interest in climate change was systematically attenuated by the severity of the COVID-19 pandemic. In addition, this study provides an approach for identifying drivers of public interest in climate change. [ABSTRACT FROM AUTHOR]

Continued climate warming, together with the overall evaluation and implementation of a range of climate mitigation and adaptation approaches, has prompted increasing research into proposed solar climate intervention methods, such as stratospheric aerosol injection (SAI). SAI would use aerosols to reflect a small amount of incoming solar radiation away from Earth to stabilize or reduce future warming due to increasing greenhouse gas concentrations. Research into the possible risks and benefits of SAI relative to the risks from climate change is emerging. There is not yet, however, an adequate understanding of how SAI might impact human and natural systems. For instance, little to no research to date has examined how SAI might impact environmental conditions critical to the formation of severe convective weather over the United States (US). This study uses ensembles of Earth system model simulations of future climate change, with and without hypothetical SAI deployment, to examine possible future changes in thermodynamic and kinematic parameters critical to the formation of severe weather during convectively active seasons over the US Results show that simulated forced changes in thermodynamic parameters are significantly reduced under SAI relative to a climate change (SSP2‐4.5) world, while simulated changes in kinematic parameters are more difficult to distinguish. Also, unforced internal climate variability is likely to significantly modulate the projected forced climate changes over large regions of the US. Plain Language Summary: Human‐caused climate warming is projected to increase occurrences of environmental conditions which favor the formation of severe weather, such as thunderstorms. Stratospheric aerosol injection (SAI) is a form of climate intervention which aims to cool the planet by injecting sunlight‐reflecting particles into the stratosphere, a part of the upper atmosphere. This study investigates how SAI might impact future projections of the environmental conditions which favor the formation of severe weather. One set of climate models simulations show that future increases of the occurrence of temperature driven environmental characteristics that favor the formation of severe weather could be avoided if SAI were to be implemented. These simulations also show that future projections of environmental characteristics that favor the formation of severe weather that are dynamically driven may not be significantly impacted by the implementation of SAI. Climate variability that is not human‐driven may also significantly impact future projections of the environmental conditions which favor severe weather formation, whether or not SAI has been implemented. Key Points: Thermodynamic parameters relevant to severe weather formation are projected to increase in magnitude over the US due to climate changeStratospheric aerosol injection may prevent many of these projected increasesInternal decadal‐scale climate variability is likely to impact future projections of regional changes in convective weather environments [ABSTRACT FROM AUTHOR]

The frequency and intensity of heat extremes over the United States have increased since the mid‐20th century and are projected to increase with additional anthropogenic greenhouse gas forcing. We define heat extremes as summertime (June–August) daily maximum 2m temperatures that exceed historical records. We examine characteristics of historical and near‐future heat extremes using observations and past and future projections using 100 ensemble members from three coupled global climate models large ensemble simulations. We find that the large ensembles capture the trend and variability of heat extremes over the period 2006–2020 relative to the 1991–2005 climatology but overestimate the frequency at which the heat extremes occur. In future warming scenarios, heat extremes continue to increase over the next 30 years, with high amplitude records in the Northwest and Central US. After 2050, we find there is a spread in the frequency of heat extremes that is dependent on the emissions scenario, with a high emissions until mid‐century followed by a high mitigation scenario showing a decrease in heat extremes by the end of the century. Although the frequency of future heat extremes is likely overestimated in the large ensembles, they are still a powerful tool for researching extreme temperatures in the climate system. Plain Language Summary: Heat extremes have been increasing around the world and the United States, driven largely by human‐caused global warming. With additional warming projected, heat extremes are likely to increase. It is important to understand how heat extremes will change in the future since heat has many societal impacts, especially on human health as it causes more fatalities than any other weather‐related hazard in the US. In this study we use 100 ensemble members from three global climate models simulating past and future climate to evaluate characteristics of record breaking maximum daily temperature records from June to August. We find that the models capture the observed trend and variability of past heat extremes but appear to overestimate the frequency that they occur. The models project an increase in heat extremes in the next 30 years, with high amplitude extremes projected in the Northwest and Central US, and high frequency extremes in the Southwest and Mountain West. The amount of warming directly impacts the frequency of heat extremes past year 2050. In a scenario with rapid reduction of greenhouse emissions after 2040 the frequency of heat extremes declines toward the end of the century. We find that while the frequency of future heat extremes is likely overestimated in the models, the ensembles are nevertheless a powerful tool for researching extreme temperatures in the climate system. Key Points: Large ensembles of climate model simulations capture the observed variability and trend of heat extremes but overestimate the frequency and amplitudeHeat extremes are projected to increase in the next 30 years with additional warming due to greenhouse gas forcingThe frequency of heat extremes toward the end of the century is highly dependent on the emissions scenario and extent of warming [ABSTRACT FROM AUTHOR]

The potential environmental and nutritional benefits of plant-based dietary shifts require thorough investigation to outline suitable routes to achieve these benefits. Whereas dietary consumption is usually in composite forms, sustainable healthy diet assessments have not adequately addressed composite diets. In this study, we build on available data in the Food4HealthyLife calculator to develop 3 dietary concepts (M) containing 24 model composite diet scenarios (S) assessed for their environmental and nutritional performances. The Health Nutritional Index (HENI) and Food Compass scoring systems were used for nutritional quality profiling and estimates of environmental impact were derived from previously reported midpoint impact values for foods listed in the What We Eat in America database. The diets were ranked using the Kruskal‒Wallis nonparametric test, and a dual-scale data chart was employed for a trade-off analysis to identify the optimal composite diet scenario. The results showcased a distinct variation in ranks for each scenario on the environment and nutrition scales, describing an inherent nonlinear relationship between environmental and nutritional performances. However, trade-off analysis revealed a diet with 10% legumes, 0.11% red meat, 0.28% processed meat and 2.81% white meat could reduce global warming by 54.72% while yielding a diet quality of 74.13 on the Food Compass Scoring system. These observations provide an interesting forecast of the benefits of transitioning to an optimal plant- and animal-based dieting pattern, which advances global nutritional needs and environmental stewardship among consumers. [ABSTRACT FROM AUTHOR]

Globally, insects have been impacted by climate change, with bumble bees in particular showing range shifts and declining species diversity with global warming. This suggests heat tolerance is a likely factor limiting the distribution and success of these bees. Studies have shown high intraspecific variance in bumble bee thermal tolerance, suggesting biological and environmental factors may be impacting heat resilience. Understanding these factors is important for assessing vulnerability and finding environmental solutions to mitigate effects of climate change. In this study, we assess whether geographic range variation in bumble bees in the eastern United States is associated with heat tolerance and further dissect which other biological and environmental factors explain variation in heat sensitivity in these bees. We examine heat tolerance by caste, sex, and rearing condition (wild/lab) across six eastern US bumble bee species, and assess the role of age, reproductive status, body size, and interactive effects of humidity and temperature on thermal tolerance in Bombus impatiens. We found marked differences in heat tolerance by species that correlate with each species' latitudinal range, habitat, and climatic niche, and we found significant variation in thermal sensitivity by caste and sex. Queens had considerably lower heat tolerance than workers and males, with greater tolerance when queens would first be leaving their natal nest, and lower tolerance after ovary activation. Wild bees tended to have higher heat tolerance than lab reared bees, and body size was associated with heat tolerance only in wild‐caught foragers. Humidity showed a strong interaction with heat effects, pointing to the need to regulate relative humidity in thermal assays and consider its role in nature. Altogether, we found most tested biological conditions impact thermal tolerance and highlight the stages of these bees that will be most sensitive to future climate change. [ABSTRACT FROM AUTHOR]

Predicting future climate change over a region of complex terrain, such as the western United States (U.S.), remains challenging due to the low resolution of global climate models (GCMs). Yet climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality predictions. Here, we present an ensemble of dynamically downscaled simulations over the western U.S. from 1980-2100 at 9-km grid spacing, driven by sixteen latest-generation GCMs. This dataset is titled the Western U.S. Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography: (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven intensified local atmospheric updrafts tied to topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western U.S. climate. [ABSTRACT FROM AUTHOR]

Introduction: Sclerotinia sclerotiorum is a necrotrophic fungal pathogen causing disease and economic loss on numerous crop plants. This fungus has a broad host range and can infect over 400 plant species, including important oilseed crops such as soybean, canola, and sunflower. S. sclerotiorum isolates vary in aggressiveness of lesion formation on plant tissues. However, the genetic basis for this variation remains to be determined. The aims of this study were to evaluate a diverse collection of S. sclerotiorum isolates collected from numerous hosts and U.S. states for aggressiveness of stem lesion formation on sunflower, to evaluate the population characteristics, and to identify loci associated with isolate aggressiveness using genome-wide association mapping. Methods: A total of 219 S. sclerotiorum isolates were evaluated for stem lesion formation on two sunflower inbred lines and genotyped using genotyping-bysequencing. DNA markers were used to assess population differentiation across hosts, regions, and climatic conditions and to perform a genome-wide association study of isolate aggressiveness. Results and discussion: We observed a broad range of aggressiveness for lesion formation on sunflower stems, and only a moderate correlation between aggressiveness on the two lines. Population genetic evaluations revealed differentiation between populations from warmer climate regions compared to cooler regions. Finally, a genome-wide association study of isolate aggressiveness identified three loci significantly associated with aggressiveness on sunflower. Functional characterization of candidate genes at these loci will likely improve our understanding of the virulence strategies used by this pathogen to cause disease on a wide array of agriculturally important host plants. [ABSTRACT FROM AUTHOR]

This study empirically estimates the effects of climate on land‐use change across the conterminous United States and uses the empirical model to simulate the effects of a range of future climate change scenarios on the allocation of land to forestry, agriculture, and development. Ricardian estimation linking climate with the net returns to land production is integrated with a discrete‐choice estimation of plot‐level land‐use change. Comparing projected land‐use changes across scenarios, we find that drier and warmer climate scenarios favor forest land, wetter and cooler climate scenarios favor developed land, and wetter and warmer climate scenarios favor crop lands. [ABSTRACT FROM AUTHOR]

Climate change, especially in the form of precipitation and temperature changes, can alter the transformation and delivery of nitrogen on the land surface and to aquatic systems, impacting the trophic states of downstream water bodies. While the expected impacts of changes in precipitation have been explored, a quantitative understanding of the impact of temperature on nitrogen loading is lacking at landscape scales. Here, using several decades of nitrogen loading observations, we quantify how individual and combined future changes in precipitation and temperature will affect riverine nitrogen loading. We find that, contrary to recent decades, rising temperatures are likely to offset or even reverse previously reported impacts of future increases in total and extreme precipitation on nitrogen runoff across the majority of the contiguous United States. These findings highlight the multifaceted impacts of climate change on the global nitrogen cycle. [ABSTRACT FROM AUTHOR]

Summer streamflow predictions are critical for managing water resources; however, warming‐induced shifts from snow to rain regimes impact low‐flow predictive models. Additionally, reductions in snowpack drive earlier peak flows and lower summer flows across the western United States increasing reliance on groundwater for maintaining summer streamflow. However, it remains poorly understood how groundwater contributions vary interannually. We quantify recession limb groundwater (RLGW), defined as the proportional groundwater contribution to the stream during the period between peak stream flow and low flow, to predict summer low flows across three diverse western US watersheds. We ask (a) how do snow and rain dynamics influence interannual variations of RLGW contributions and summer low flows?; (b) which watershed attributes impact the effectiveness of RLGW as a predictor of summer low flows? Linear models reveal that RLGW is a strong predictor of low flows across all sites and drastically improves low‐flow prediction compared to snow metrics at a rain‐dominated site. Results suggest that strength of RLGW control on summer low flows may be mediated by subsurface storage. Subsurface storage can be divided into dynamic (i.e., variability saturated) and deep (i.e., permanently saturated) components, and we hypothesize that interannual variability in dynamic storage contribution to streamflow drives RLGW variability. In systems with a higher proportion of dynamic storage, RLGW is a better predictor of summer low flow because the stream is more responsive to dynamic storage contributions compared to deep‐storage‐dominated systems. Overall, including RLGW improved low‐flow prediction across diverse watersheds. Plain Language Summary: Water managers across the western United States depend on accurate streamflow prediction models for water planning and allocation during summer months. Historically, these models use snow metrics to predict summer flows, but increasing temperatures across the western US are decreasing snow input and accumulation and increasing early snow melt rates leading to changes in streamflow generation mechanisms. Here, we seek to understand how stream flows will respond under warmer climates in three watersheds with distinct climate and underlying bedrock in the western US. We expanded upon commonly used low‐flow model snow metrics to include snow and streamflow metrics from the previous year as well as groundwater dynamics during the annual recession curve. We found that including variables outside of commonly used snow parameters in the models produced more accurate predictions of summer low flows. We provide a framework for future analysis of streamflow response to warming across the western US. Key Points: Recession limb groundwater proportion is a strong predictor of summer low flowsRecession limb dynamics are especially important for improving low‐flow prediction at rain‐dominated sitesRecession limb groundwater may be a better predictor of low flow at sites where dynamic storage exceeds deep storage [ABSTRACT FROM AUTHOR]

Mortality due to extreme temperatures is one of the most worrying impacts of climate change. In this analysis, we use historic mortality and temperature data from 106 cities in the United States to develop a model that predicts deaths attributable to temperature. With this model and projections of future temperature from climate models, we estimate temperature‐related deaths in the United States due to climate change, changing demographics, and adaptation. We find that temperature‐related deaths increase rapidly as the climate warms, but this is mainly due to an expanding and aging population. For global average warming below 3°C above pre‐industrial levels, we find that climate change slightly reduces temperature‐related mortality in the U.S. because the reduction of cold‐related mortality exceeds the increase in heat‐related deaths. Above 3°C warming, whether the increase in heat‐related deaths exceeds the decrease in cold‐related deaths depends on the level of adaptation. Southern U.S. cities are already well adapted to hot temperatures and the reduction of cold‐related mortality drives overall lower mortality. Cities in the Northern U.S. are not well adapted to high temperatures, so the increase in heat‐related mortality exceeds the reduction in cold‐related mortality. Thus, while the total number of climate‐related mortality may not change much, climate change will shift mortality in the U.S. to higher latitudes. Plain Language Summary: Deaths due to extreme temperatures is one of the most important impacts of climate change. Here we estimate future temperature related deaths in the US using climate projection, population projection, and adaptation assumptions. We find that in 3°C of global warming level, temperature‐related deaths will increase by a factor of five, mostly due to aging and increasing population. Below 3°C warming, impact of climate change slightly decreases temperature‐related deaths, because the decrease in cold‐related deaths exceeds the increase in heat‐related deaths. Above 3°C warming, impact of climate change depends on the level of adaptation. Furthermore, we find that temperature‐related mortality shifts Northward. This is due to increase of heat‐related deaths in Northern cities, which are currently poorly adapted to heat. Key Points: Temperature‐related deaths in the U.S. will increase by a factor of 5 with 3°C of warming, mostly due to aging and increasing populationImpact of climate change is not significant until 3°C of global warming, and it depends on the level of adaptation beyond that pointTemperature‐related deaths will shift Northward, due to increasing heat‐related deaths in poorly heat‐adapted Northern cities [ABSTRACT FROM AUTHOR]

Increasing temperature and water cycle changes due to warming climate may increase the frequency and intensity of wildfires. Fire emission projections are useful for informing strategies for adaptation and mitigation of fire impacts on societies and ecosystems. Here, we construct a neural network (NN) model explained by the Shapley Additive explanation to predict fire PM2.5 emissions change and understand their drivers over the contiguous US (CONUS) in the mid‐21st century under a high greenhouse gas emissions scenario (SSP5‐8.5). Using future meteorology and leaf area index (LAI) simulated by eight global climate models from the Coupled Model Intercomparison Project Phase 6, future population density, and present‐day land use and land cover (LULC) as input to the NN model, the total fire PM2.5 emissions over CONUS are projected to increase by 4%–75% (model spread). Among different regions, fire emissions in the western US are projected to increase more significantly in June‐July‐August than in other seasons and regions, with the median ratios of future to present‐day fire emissions ranging from 1.67 to 2.86. The increases in fire emissions are mainly driven by increasing normalized temperature (23%–29%) and decreasing soil moisture (2%–10%) in the future. When future LULC change is considered, the projected fire emissions further increase by 58%–83% over the western US compared to projections without LULC change because of future increases in vegetation fraction. The results highlight the important role of warmer temperature, decreasing soil moisture, and LULC change in increasing fire emissions in the future. Plain Language Summary: Climate change has increased fire frequency and size in the United States, particularly in the western US, causing property damage, threats to human life, and degraded air quality. Frequent drought, enhanced fuel aridity, and increased fuel accumulation may cause larger and more frequent fires and emissions in the coming decades. Using explainable artificial intelligence and outputs from global climate models, we show that total fire PM2.5 emissions over the contiguous US will be around 1.38 times the present‐day emissions by the mid‐21st century under a high greenhouse gas emissions scenario. The fire PM2.5 emissions will double in the western US during summer, mainly driven by drying trends in the soil along with increasing temperatures. When the future change of land use and land cover is also considered, the fire emissions in the western US will increase further by 50%, due to the increased vegetation fractions in a warmer climate. Key Points: Using explainable AI and Coupled Model Intercomparison Project Phase 6 outputs, total fire PM2.5 emissions over the US are projected to increase by 4%–75% by mid‐centuryFire emissions are projected to increase by ∼67%–186% in the western US in summer, due to reduced soil moisture and warmer temperatureLand use and land cover change adds an extra ∼50% increase of future fire emissions, driven by increased vegetation in the western US [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are the dominant rainfall producer over the United States during the warm season, causing natural disasters and severe weather every year. Global climate models have large uncertainty in projecting precipitation changes in the future climate. Here, a simple Lagrangian parcel model is used to investigate the impact of global warming on MCS initiation and growth. The single-column parcel model projects a mean precipitation decrease over the central United States and an increase to its east, in agreement with the CMIP5 model projection. It also highlights the crucial role of current climate mean-state model bias in exaggerating the change in future mean precipitation projection by 25%. As for convective population, the model captures the decreased occurrence frequency of weak to moderate convection and increased frequency of strong convection due to the increased CAPE and CIN, in agreement with convection-permitting regional simulations. Novel parameterizations of gust-front propagation speed and subsidence strength are developed as guided by cloud-resolving simulations. The multicolumn parcel model employing those parameterizations captures readily the cold pool–induced upscale growth feature. It simulates smaller mesoscale clusters over the central United States under global warming due to gust-front slowdown and subsidence strength enhancement, which are further attributed to land aridity–induced weakening of initial accumulated precipitation and strengthening of updraft speed, respectively. That said, mesoscale clusters could become bigger under more favorable conditions in future climate, including boundary layer moistening, convection lifetime lengthening, and cold pool mechanical-lifting enhancement, which require further investigations to improve mechanistic understanding of future MCS changes. [ABSTRACT FROM AUTHOR]

The article discusses lessons from French and European Union (EU) wine laws that can be applied in American wine regulatory development. It provides a general background on wine and wine production, then compares the American Viticulture Area (AVA) regulatory scheme with French and EU wine regulation. It recommends changes to the AVA that could advance U.S. wine in global markets while avoiding global warming-related challenges facing other regulatory regimes.

Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of late‐successional forests have prompted efforts to restore old‐growth forest structure. One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old‐growth structure may reduce the extent and number of CCR. We used remotely sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old‐growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old‐growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this chapter is to investigate the relationship between corporate governance and greenhouse gas (GHG) disclosures using evidence from the United States. Design/Methodology/Approach: The study is based on a sample of 168 firms listed on the New York Stock Exchange (NYSE) in the United States. Panel data are used covering a period from 2017 to 2020 involving 672 observations. Findings: The results indicate that board size has a positive and significant effect on GHG disclosures while the effect of ownership concentration and insider ownership is negative and significant. The proportion of non-executive directors is not significant. In terms of control variables, firm size and financial slack have a positive effect on GHG disclosures. Originality/Value: The study results add evidence to the already existing literature on the relationship between corporate governance and GHG disclosures using evidence from the United States. [ABSTRACT FROM AUTHOR]

Overseeding alfalfa (Medicago sativa L.) into grass swards increases forage nutritive value and reduces N fertilizer requirement. In warm climates, establishing and maintaining alfalfa in mixtures with vigorous C4 grasses is challenging, which makes adjustment of defoliation management critical. The objective of this 2‐year study was to determine optimal harvest stubble height (SH; 5, 10, and 15 cm) and cutting interval (CI; 2, 4, and 6 weeks) for two alfalfa genotypes ("Bulldog 805," and breeding line UF Alf Pers 2015 [UF 2015‐AP]) in mixture with "Tifton 85" bermudagrass (Cynodon spp.). When statistical differences occurred, shorter SH resulted in greater mixture forage accumulation (FA), with this effect generally more pronounced for UF 2015‐AP than Bulldog 805, and for CI of 6 weeks than 2 or 4 weeks. Genotype did not affect alfalfa FA, but alfalfa FA was least for the 2‐week CI for all SH levels, and greatest for the 5‐cm SH when CI was 4 weeks, and for the 5‐ and 10‐cm SH when CI was 6 weeks. Alfalfa percent cover was generally greater for longer CI, regardless of SH. Mixture crude protein and digestibility were minimally affected by treatments because the expected negative effects of long CI on nutritive value were offset by greater alfalfa proportion in the mixture for these treatments. In this environment, CI was generally the most important factor affecting alfalfa persistence in alfalfa–bermudagrass mixtures. A short SH in combination with longer CI (4–6 weeks) resulted in the greatest mixture and alfalfa FA. Core Ideas: Two alfalfa genotypes responded similarly to intercropping with Tifton 85 bermudagrass.Longer cutting intervals in combination with shorter stubble heights produced greater forage accumulation.The expected nutritive value decline with longer cutting intervals was limited by greater alfalfa presence.Optimizing alfalfa–bermudagrass defoliation management increases likelihood of mixture success. [ABSTRACT FROM AUTHOR]

The persistence of future forests depends on the success of tree seedlings which are experiencing increasing physiological stress from changing climate and air pollution. Although the moss layer can serve as an important substrate for tree seedlings, its potential for reducing environmental stress and enhancing the establishment of seedlings remains poorly understood. We tested if the moss layer decreased environmental stress and increased the abundance of balsam fir seedlings dominant in high-elevation forests of northeastern United States that are sensitive to changing climate and mercury deposition. We surveyed balsam fir seedling density by substrate (moss, litter, other) on 120 quadrats (1 × 1 m) in two contrasting canopy environments (in gaps and under canopies), measured seedling stress, and quantified mercury content in seedlings and substrates. We observed that, in both canopy environments, tree seedlings established on moss exhibited (i) increased density, (ii) decreased physiological stress, and (iii) higher potential to recruit into larger size classes, compared to seedlings established in litter. Regardless of canopy environment, seedling foliar mercury levels did not correspond to substrate mercury despite large differences in substrate mercury concentrations (relative to moss, litter concentrations were ~ 4-times greater and soil concentrations were ~ 6-times greater), likely reflecting the dominance of foliar over root uptake of mercury. Because the moss layer appeared to mitigate seedling drought stress, and to increase seedling establishment and recruitment compared to other substrates, these microsite effects should be considered in models predicting forest regeneration and dynamics under increased drought stress associated with the ongoing climate warming. [ABSTRACT FROM AUTHOR]

In October 2011, the Halloween Nor'easter produced unusually early and heavy snowfall while leaves were still on the trees, causing extensive damage throughout the northeastern United States. This storm is an example of winter weather whiplash, in which an abrupt, back-and-forth swing in winter weather affects coupled human and natural systems. Research on the social-ecological drivers and impacts of winter weather whiplash is scarce because most studies only consider meteorological causes and consequences of extreme events. In this study, we used publicly available data of snowfall accumulation, vegetation phenology, road density, and per capita income to predict storm impacts, which we estimated with textual analysis of Halloween Nor'easter newspaper coverage. We demonstrated that a combination of meteorological, natural, and human system drivers was better able to predict the impact of the storm than meteorological drivers alone. Although we focused on the Halloween Nor'easter, our work highlights the necessity of understanding how multiple drivers and hazards can intersect to create rare and possibly novel conditions that may become more common as the climate warms and becomes more variable. [ABSTRACT FROM AUTHOR]

In recent decades, the United States has experienced changing patterns of extreme temperature. Although much progress has been made, delineating the change in synoptic surface temperature variability (SSTV) and understanding its potential causes remain to be pursued. In this study, we seek to provide a quantitative description of the change in SSTV in the past seven decades across the US and its potential relevant physical factors. To achieve this goal, we develop a spatiotemporally local analysis method based on the ensemble empirical mode decomposition that bypasses the stationary assumption and makes it possible to continuously track the change in SSTV in the spatiotemporal domain. We have found that the change in SSTV across the US is spatially inhomogeneous and temporally non-uniform. The change in the SSTV amplitude ranges from −36% to 39% across the continental United States, Northern Mexico, and surrounding oceans. Higher altitudes and surrounding regions generally see an increase in variability, while elsewhere over land, a reduction is observed, creating a three-band zonal structure across the continental United States. Generally, increases in variability are observed in the subtropics. The shape of the spatiotemporal evolution of SSTV implies that the topography of the United States may play an important role in altering synoptic-scale variability. [ABSTRACT FROM AUTHOR]

Observed surface organic aerosols (OA) concentrations slightly increased in the western US (WUS) but significantly decreased in the eastern US (EUS) in summer, and continuously decreased in winter over the US region. To understand the driving factors for the long‐term surface OA trend, we apply a revised version of the Community Atmosphere Model version 6 with comprehensive tropospheric and stratospheric chemistry representation, considering the heterogeneous formation of isoprene‐epoxydiol‐derived secondary organic aerosols (SOAIE) and fast photolysis rate of monoterpene‐derived secondary organic aerosols (MTSOA) to diagnose the OA evolution in 1988–2019. Compared to older versions, the revised model better reproduces the climatology, seasonal cycle, and long‐term trend of surface OA as evaluated against the Interagency Monitoring of Protected Visual Environments measurements. We find the decrease in EUS summertime OA is likely attributed to the interplay between SOAIE and MTSOA. With anthropogenic emissions reduction, primary organic aerosols (POA) declined, SOAIE decreased along with sulfate, while MTSOA increased along with biogenic emissions driven by a warming climate. POA from wildfires with a significant trend of 2.9% yr−1 and considerable interannual variation of 62.8% drive the statistically insignificant but increasing WUS summertime OA, while anthropogenic POA dominates the decreasing wintertime OA in the US. Through sensitivity experiments, we find MTSOA show linear responses to the increasing monoterpenes emissions and negligible responses to NOx emissions reduction due to the mutual offsets between MTSOA components from different oxidation pathways. This study reveals the increasingly important role of MTSOA in summertime OA under a warming climate. Plain Language Summary: As the major components of fine particles, organic aerosols (OA) increased in the western United States and decreased in the eastern United States in the summer, and kept decreasing in the winter in the past decades. The driving factors for the long‐term trend of OA and their components remain unclear and are investigated by conducting a series of long‐term simulations. We find the isoprene‐epoxydiol‐derived secondary organic aerosols decrease with sulfate emission controls, which is partly offset by the increasing monoterpene‐derived secondary organic aerosols (MTSOA) under global warming and the statistically insignificant increase of primary organic aerosols driven by wildfires in summer. In winter, anthropogenic emissions dominate the declining surface OA. We also find MTSOA are more sensitive to increasing biogenic emissions than anthropogenic emissions reduction. Our results reveal the important role of MTSOA in total summertime OA under a warming climate. Key Points: Monoterpene‐derived and isoprene‐epoxydiol‐derived secondary organic aerosols (SOA) contribute to the descending surface summertime organic aerosols (OA) in the eastern USPrimary organic aerosols (POA) from wildfires drive the statistically insignificant but increasing trend of surface summertime OA in the western USMonoterpene‐derived SOA linearly respond to increasing monoterpenes emissions but negligibly respond to NOx emissions reduction [ABSTRACT FROM AUTHOR]

Climate change is driving widespread changes in ecological communities. Warming temperatures often shift community composition toward more heat-tolerant taxa. The factors influencing the rate of this "thermophilization" process remain unclear. Using 10-y census data from an extensive forest plot network, we show that mature tree communities of the western United States have undergone thermophilization. The mean magnitude of climate warming over the 10-y study interval was 0.32 °C, whereas the mean magnitude of thermophilization was 0.039 °C. Differential tree mortality was the strongest demographic driver of thermophilization, rather than growth or recruitment. Thermophilization rates are associated with recent changes in temperature and hydrologic variables, as well as topography and disturbance, with insect damage showing the strongest standardized effect on thermophilization rates. On average, thermophilization occurred more rapidly on cool, north-facing hillslopes. Our results demonstrate that warming temperatures are outpacing the composition of western US forest tree communities, and that climate change may erode biodiversity patterns structured by topographic variation. [ABSTRACT FROM AUTHOR]

Climate change has arrived. The next decade will provide critical opportunities to avoid the most devastating impacts of climate change. The decisions we take over the next ten years will be the difference between moderate levels of warming and warming that will cause catastrophic changes to the planet. To avoid the most devastating impacts of climate change, the United States must rapidly transition the energy sector to almost entirely renewable energy. Notwithstanding the rapid growth of renewable energy over the past decade, the United States must add renewable capacity at an unprecedented rate. To meet this challenge, many states have set aggressive renewable energy targets for their electricity sectors. In the push for a transition to renewable energy, the question remains: where will it all go? Many people like the idea of clean energy in their state but would prefer that the facilities not be located near them. Thus, in response to the push for clean energy, many local governments and municipalities have enacted laws restricting the siting of renewable energy projects. Left unchecked, these local restrictions may prevent states from reaching their renewable energy targets. State-level renewable energy siting programs offer centralized decisionmaking for renewable energy projects and can preempt local laws that are overly restrictive. This Note focuses on using state preemption of local laws to promote the development of new renewable energy projects and identifying legal features that make these programs successful, looking to New York as a case study. [ABSTRACT FROM AUTHOR]

Drought is a recurring natural hazard that has substantial human and environmental impacts. Given continued global warming and associated climate change, there is concern that droughts could become more severe and longer lasting. To better monitor and understand drought development and persistence, it is helpful to understand the development and climatic drivers of past droughts. In this study we use monthly runoff percentiles to identify five major drought events in the conterminous United States (CONUS) from 1901 through 2020. For each drought event we examined spatial patterns of departures of mean monthly precipitation, temperature, soil moisture storage, and runoff for 2,107 hydrologic units (HUs) across the CONUS. Results indicated that precipitation deficits have been the primary driver of past major‐drought events and temperature a secondary driver, even of the most recent drought event (September 1999 through September 2015) when positive temperature anomalies occurred over most of the CONUS. Additionally, negative soil moisture storage departures were more negative than runoff departures during the five drought events we examined, which emphasizes the importance of measuring both runoff and soil moisture to monitor drought conditions. We also examined the use of statistical persistence to develop short‐term (i.e., 1 month) forecasts of runoff drought conditions in the CONUS by developing autoregressive integrated moving average (ARIMA) models for each HU. Results indicated that persistence can be used to predict short‐term changes in the spatial pattern of drought and the areal extent of drought, but that predictions of runoff magnitude for any particular site are often poor. [ABSTRACT FROM AUTHOR]

This study uses Global Historical Climate Network (GHCN) data in each season to identify the days with the most extreme precipitation ("EP days") in the mid-Atlantic and northeast United States between 1979 and 2019. These days are sorted according to the fraction of extreme precipitation attributed to tropical cyclone (TC), atmospheric river (AR), and extreme integrated vapor transport (IVT) influences. In winter and spring, there have been increases in seasonal precipitation from the most extreme days, associated with a combination of frequency and intensity changes. These increasing trends come primarily from atmospheric rivers. In summer and fall, there have also been large increases in precipitation on extreme days, in this case due entirely to increased event frequency. These changes come from a combination of AR, TC, and extreme IVT influences. Synoptic characteristics of AR-related EP days in winter and spring have changed significantly. In winter, there has been an amplification of the Atlantic ridge and a deepening of the upstream trough over the upper Great Plains, as well as enhanced AR detection and IVT on these days. The composite low has shifted north and intensified. In spring, the trough has weakened and 1000–500-hPa thickness has increased broadly to the south. These changes are related to changes in the large-scale flow. In winter and spring, the North Atlantic subtropical high (NASH) has strengthened and shifted west, leading to increased southwesterly IVT over the mid-Atlantic and Northeast United States. In summer, southerly IVT along the east coast has increased, and 1000–500-hPa climatological thickness has increased broadly in all seasons. Significance Statement: This paper studies the days with the most extreme precipitation over the mid-Atlantic and Northeast United States in each season and finds that there have been large changes in the frequency, intensity, and characteristics of some of these days. Extreme days associated with atmospheric rivers (ARs) and tropical cyclones (TCs) have become more frequent. Precipitation on AR-related days has also become more intense in some areas. On winter extreme days associated with ARs, the pattern has become more amplified and moisture fluxes have become stronger; these changes are likely associated with strengthened high pressure over the Atlantic. Throughout all seasons, there is evidence of warming on extreme days. This is important because it adds to our understanding of how total and AR-related extreme precipitation is changing in a warming climate. [ABSTRACT FROM AUTHOR]

Global warming is likely to provoke extreme storms in the eastern United States (eUS), ultimately affecting the probabilistic distribution of the dates of daily maximum precipitation. In this study, probabilistic properties of timing of annual maximum precipitation (AMP) were studied using circular statistics at 583 sites in the eUS (1950–2019). A kernel circular density method was applied to examine distributional modes of timing of AMP. The results of circular median show that seasonality is pronounced across the eUS with many locations having their median date of occurrence in summer, and AMP seasonality is strong in the East North Central region. Similarly, results of circular density method applied to the distribution of AMP timing shows that around 90% of the sites have two or three modes of AMP seasonality in the eUS. Comparison of seasonality between two historical records of equal length (1950–1984 and 1985–2019) shows great spatial variability across the eUS. Temporal changes in seasonal modes for AMP dates revealed four different cases of seasonality changes: (i) weakening of seasonality, (ii) strengthening of seasonality, (iii) strong seasonality for both the old and recent periods, (iv) or uniform or no preferred seasonality for both periods. While a spatial coherence of seasonality changes was not observed, majority of sites showed strong seasonality (case iii) for old and recent periods mainly during summer and fall seasons. [ABSTRACT FROM AUTHOR]

Continued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt‐derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100‐m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo‐global‐warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45%) and mid elevations (−14%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30%–42%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation‐dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow‐dominated regions. Plain Language Summary: Snowpack water storage has historically functioned as a reliable extension of manmade reservoir storage. Loss of this storage has consequences for water resource management, ecological communities, and natural hazards including wildfire. We modeled snow accumulation and melt at high spatial resolution in the Upper Colorado River Basin to assess patterns in the timing and magnitude of snow storage and snowmelt for historical and future scenarios. We analyze these patterns in relation to existing snow monitoring station coverage, and ask how this coverage may need to change in future decades to better represent water availability. Our results indicate widespread future snow storage losses at lower elevations, but limited change at higher elevations that will likely remain conducive to seasonal snow accumulation and melt for decades to come. Peak snow storage and peak snowmelt occurred earlier for all elevations in future years, with increased peak surface water input noted at all elevations. A greater fraction of future snow storage will be in currently unmonitored high elevations. Projected elevation dependent changes from this study have implications for other dry, snow dominated regions, and additional work is needed to evaluate combined effects of widespread snow loss and earlier, flashier input on coordinated water management. Key Points: Projections show lower peak snow water equivalent (SWE) below 3,000 m and earlier peak SWE, peak surface water input (SWI) at all elevationsGreater future peak SWI and reduced annual snow‐derived SWI for all elevations, with a more even SWI distribution throughout the yearA greater fraction of future SWE will be in high elevations that are currently unmonitored [ABSTRACT FROM AUTHOR]

Examination of climatic and oceanographic changes through the Holocene (11.75 ka–present) allows for an improved understanding and contextualization of modern climate change. Climate records of the Holocene can be utilized as a "baseline" from which to compare modern climate and can also provide insights into how environments experience and recover from change. However, individual studies on Holocene climate in the literature tend to focus on a distinct geographic location, a specific proxy record, or a certain aspect of climate (e.g., upwelling or precipitation), resulting in localized, record-specific trends rather than a comprehensive view of climate variability through the Holocene. Here we synthesize the major oceanographic and terrestrial changes that have occurred in the Western United States (bounded by 30 to 52 ∘ N and 115 to 130 ∘ W) through the most recent 11.75 kyr and explore the impacts of these changes on marine and terrestrial ecosystems. We present a novel spatiotemporal analysis of Holocene marine and terrestrial temperature, hydroclimate, and fire activity across the Early, Middle, and Late Holocene using a coded analysis of over 40 published studies. Following coded analysis of temperature, hydroclimate, and fire activity in the paper, we include a broader literature review of environmental change through the Holocene, including an examination of the impacts of multi-millennial climate trends on ecological communities. We find that the Early Holocene is characterized by warming relative to pre-Holocene conditions, including warm sea surface conditions, a warm and dry Pacific Northwest, a warm and wet Southwest, and overall spatial and temporal stability. In the Middle Holocene, these patterns reverse; this interval is characterized by cool sea surface temperatures, a cool and wet Pacific Northwest and warm and dry Southwest. The Late Holocene is the most variable interval, both spatially and temporally, and a novel spatial trend appears in terrestrial climate with warmer coastal areas and cooler inland areas. Human communities interacted with the environment throughout the entire Holocene, as evidenced in archeological and paleoenvironmental records, yet the recent Era of Colonization (1850–present) represents an unprecedented environmental interval in many records. Broadly, our analysis shows linkages between terrestrial and oceanographic conditions, distinct environmental phases through time, and emphasizes the importance of local factors in controlling climate through the dynamic Holocene. [ABSTRACT FROM AUTHOR]

In this study, the authors identify and describe factors that have contributed to an acrimonious political divide in the United States. Informed by a developmental perspective, the authors first establish the universal motive for group belonging. Next, they describe how group forces have organized citizens into hostile groups built around these variables: expansion of technology, global warming, rising immigration, cultish leader/follower dynamics, religion, national attitudes toward the pandemic, and characteristics of the national leader. The authors propose several solutions to the current divide, including the elevation of the school to the pinnacle of the civic public square. [ABSTRACT FROM AUTHOR]