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Indigenous Peoples globally are among those who are most acutely experiencing the mental health impacts of climate change; however, little is known about the ways in which Indigenous Peoples globally experience climate-sensitive mental health impacts and outcomes, and how these experiences may vary depending on local socio-cultural contexts, geographical location, and regional variations in climate change. Thus, the goal of this study was to examine the extent, range, and nature of published research investigating the ways in which global Indigenous mental health is impacted by meteorological, seasonal, and climatic changes. Following a systematic scoping review protocol, three electronic databases were searched. To be included, articles had to be empirical research published since 2007 (i.e. since the Intergovernmental Panel on Climate Change's Fourth Assessment Report); explicitly discuss Indigenous Peoples and describe factors related to climatic variables and mental health. Descriptive data from relevant articles were extracted, and the articles were thematically analyzed. Fifty articles were included for full review. Most primary research articles described research in Canada (38%), Australia (24%), and the United States of America (10%), with the number of articles increasing over time. Mental health outcomes such as strong emotional responses, suicide, depression, and anxiety were linked to changes in meteorological factors, seasonality, and exposure to both acute and chronic weather events. The literature also reported on the ways in which the emotional and psychological impacts of climate were connected to changing place attachment, disrupted cultural continuity, altered food security and systems, forced human mobility, and intangible loss and damages. This review highlights global considerations for Indigenous mental health in relation to climate change, which can support Indigenous-driven initiatives and decision-making to enhance mental wellness in a changing climate.

The Clean Development Mechanism (CDM) has been the major international offset mechanism within the broader world of carbon finance. It was designed with two goals in mind: to lead to significant emission reductions that will help reduce the cost of climate mitigation in countries with commitments as well as contribute to sustainable development in the host countries. However, there has been significant discussion about the degree to which these projects fulfilled their dual mission of emissions reductions and sustainable development, particularly with respect to fostering local community co-benefits as part of broader sustainable development outcomes. In this paper, we review literature on the co-benefits delivered by the CDM at the local or community level, based on a group of 84 peer-reviewed articles and other reports. While perspectives on co-benefits are diverse, most sources argue or acknowledge that even with more recent procedural improvements, the CDM has not consistently delivered significant co-benefits to local communities. It appears likely that the situation has improved somewhat in recent years as CDM procedures have been refined, and there may be more opportunities for enhancing procedures to favor such benefits. There is overall variability in delivering co-benefits depending on the technology type, design features and the country context.

Grasslands and savannas across the globe have undergone a dramatic transition over the past century. Historical overgrazing has set in motion a cascade of events ranging from desertification in arid climates to woody plant encroachment (WPE) in semiarid and subhumid climates. In recent decades, grazing pressure on many of these landscapes has declined significantly, and where rainfall is sufficient (as in most semiarid and subhumid settings), herbaceous vegetation in intercanopy areas will recover. An important question is, how has this transition altered ecohydrological connectivity (overland flow and runoff–runon dynamics)? A woody-plant-encroached, subhumid savanna site in South Texas with a history of heavy grazing (but ungrazed since 1981) was used as a model landscape to address this question. Overland flow, soil moisture, and field saturated hydraulic conductivity (K_fs) were measured along a catena extending from the upland savanna-parkland areas to the downslope, more densely wooded areas. For comparison, K_fs and infiltrability were also measured at a moderately grazed upland site 14 km east of our study site, selected as a surrogate for past conditions at our site. In contrast to the prevailing hypothesis that the downslope areas ('drainage-woodlands') at our study site have continued to be supported by runoff generated from the upland areas, our measurements yielded no evidence for the redistribution of water from the uplands to the drainage areas under the current ungrazed conditions. Further, K_fs at the ungrazed study site was two orders of magnitude higher than that at the grazed site and infiltrability was twice as high at the ungrazed site than the grazed site. These findings, coupled with historical information from the site, strongly suggest that historical overgrazing amplified the runoff–runon process, resulting in significant subsidies of water from the uplands to the drainage areas. Then, with the relaxation of grazing pressure and subsequent landscape recovery, redistribution of water via surface runoff was relatively rare. We believe that our results are generalizable for savannas that have recovered from overgrazing. When these savannas are heavily grazed, ecohydrological connectivity is greatly increased; but if grazing pressure relaxes, ecohydrological connectivity will collapse. These changes in ecohydrological connectivity have important, but not always well understood, ecological consequences.

The idea of modifying cirrus clouds to directly counteract greenhouse gas warming has gained momentum in recent years, despite disputes over its physical feasibility. Previous studies that analyzed modifications of cirrus clouds by seeding of ice nucleating particles showed large uncertainties in both cloud and surface climate responses, ranging from no effect or even a small warming to a globally averaged cooling of about 2.5 °C. We use two general circulation models that showed very different responses in previous studies, ECHAM6-HAM and CESM-CAM5, to determine which radiative and climatic responses to cirrus cloud seeding in a 1.5 × CO₂ world are common and which are not. Seeding reduces the net cirrus radiative effect for −1.8 W m⁻² in CESM compared with only −0.8 W m⁻² in ECHAM. Accordingly, the surface temperature decrease is larger in CESM, counteracting about 70% of the global mean temperature increase due to CO₂ and only 30% in ECHAM. While seeding impacts on mean precipitation were addressed in past studies, we are the first to analyze extreme precipitation responses to cirrus seeding. Seeding decreases the frequency of the most extreme precipitation globally. However, the extreme precipitation events occur more frequently in the Sahel and Central America, following the mean precipitation increase due to a northward shift of the Intertropical Convergence Zone. In addition, we use a quadratic climate damage metric to evaluate the amount of CO₂-induced damage cirrus seeding can counteract. Seeding decreases the damage by about 50% in ECHAM, and by 85% in CESM over the 21 selected land regions. Climate damage due to CO₂ increase is significantly reduced as a result of seeding in all of the considered land regions.

We estimate the climate value of offshore wind energy with a highly flexible, forward-looking method that estimates the value in a consistent manner under a range of policies, including carbon caps and taxes. Backward looking methods measure the damages avoided due to emissions reductions attributed to renewable energy under an existing policy structure. Under a carbon cap, however, the climate value of offshore wind energy comes entirely from reducing the cost of meeting the cap. Our method for estimating the prospective climate value compares both climate damages and abatement costs in cases with and without offshore wind energy. This climate value can be compared to the costs of reducing barriers to new technologies, such as streamlining approval processes. The climate value depends on the cost of offshore wind technology, the climate policy under consideration, the severity of damages from climate change, and the discount rate. In the absence of a binding climate policy, the climate value of offshore wind energy ranges from $246 billion to $2.5 trillion under central assumptions about damages and discount rate, and can reach over $30 trillion under certain assumptions (low discount rate, high damages, low technology costs). The value of technical change—of moving from the highest cost to lowest cost assumptions about the technology—is estimated to be $300 billion even under the most unfavorable assumptions, dwarfing worldwide R&D investment in all wind energy technology. Using this method, we find that new low carbon technologies can provide a hedge against uncertainty and error in climate policies.

The 'hot spot-hot moment' concept is a long-standing and popular framework often invoked to explain spatially or temporally variable rates of biogeochemical cycling. However, this concept has been rarely extended to ecosystem fluxes such as gross primary productivity (GPP), in part due to the lack of a quantitative definition of hot moments that can be applied to large flux datasets. Here, we develop a general statistical framework for quantifying hot moments in GPP and identify their spatial patterns and climatic drivers. Using 308 site-years of eddy covariance data from the FLUXNET2015 dataset spanning 32 U.S. sites, we found hot moments in GPP to comprise a disproportionate percentage of annual carbon (C) uptake relative to the frequency of their occurrence. For example, at five sites over 12% of annual C uptake occurred during the ∼2% most extreme half-hourly or hourly observations of GPP. Hot moments were most quantitatively important for the C cycle in short-stature, arid ecosystem such as grasslands, woody savannas, and open shrublands, where these positive anomalies in GPP were caused by increases in moisture availability. In contrast, hot moments were less important for annual C uptake in more mesic ecosystems, where their occurrence was largely determined by high temperature and light availability. Our results point to a need to consider how short-term spikes in environmental conditions exert an outsized influence on annual GPP, and how future shifts in these conditions could impact the terrestrial C cycle.

This study investigates the future changes in dangerous extreme precipitation event in South America, using the multi-model ensemble simulations from the HAPPI experiments. The risks of dangerous extreme precipitation events occurrence, and changes in area and population exposure are quantified. Our results show that the likelihood of dangerous extreme precipitation increases in large parts of South America under future warming; changes in extreme precipitation are nonlinear with increasing global mean temperatures; and exposure plays a minor role compared to hazard. In all the models, limiting warming to 1.5 °C as opposed to 2 °C shows a general reduction in both area and population exposure to dangerous extreme precipitation throughout South America. The southeast region of South America exhibited the highest multi-model median percentage of avoided area exposure at 13.3%, while the southwest region shows the lowest percentage at 3.1%. Under all shared socioeconomic pathways, South America Monsoon region and southern South America region yielded the highest multi-model median percentage of avoided population exposure (>10%). The strong spatial heterogeneity in projected changes in all the models highlights the importance of considering location-specific information when designing adaptation measures and investing in disaster preparedness.

The heavily populated highlands of Ethiopia are currently at low risk for malaria transmission, but global warming may change the risk level significantly. The inhabitants of the Ethiopian Highlands are highly vulnerable to this potential hazard due to their lack of immunity. Here, we identify hotspots within the Highlands where projected warming towards the end of the 21st century will increase the risk of malaria transmission significantly. Based on projected temperature changes, we conclude that about a third of the region's population and roughly 14% of its land area will become at high risk for malaria transmission within a century under the high-emissions-no-mitigation baseline scenario for future climate change. Our analysis combines dynamically down-scaled regional climate projections, high resolution satellite observations of temperature, and a village-scale malaria transmission model that was developed based on climatic, environmental, entomological, and medical data collected by our group in comprehensive multi-year field surveys of villages in this region. The projected impacts of global warming on malaria transmission in Africa have been controversial. We propose a framework that reconciles seemingly contradictory conclusions, and informs strategies for climate adaptation not only over the Ethiopian Highlands but broadly over Africa, where more than 90% of malaria deaths occur every year.

In the western United States, mountain pine beetles (MPBs) have caused tree mortality across 7% of the forested area over the past three decades, leading to concerns of increased fire activity in MPB-affected landscapes. While fire behavior modeling suggests MPB-associated changes in fuels may influence fire behavior, retrospective studies have generally found negligible or weak effects of pre-fire MPB outbreak on fire activity. This apparent disagreement may arise from differences in fire weather, fuels, or scale and highlights the need for empirical studies that examine the influence of MPB outbreak on fire activity at finer spatiotemporal scales. Here we use a novel combination of geospatial data and firefighter observations to test the relative influences of red and gray stage MPB outbreak on two measures of daily wildfire activity—daily area burned (DAB) and observed fire behavior. We analyzed 2766 large wildfires that burned in the West over the 2003–2012 period. We found 329 fires that intersected prior MPB outbreak, however most burned in areas affected by MPB for only a few days (median = 4 d). We modeled DAB and the occurrence of observation of high-extreme fire behavior in 57 large (>1140 ha) wildfire events that burned for long time periods (>10 d) in landscapes affected by MPB. Under these conditions, we found no effect of red or gray stage MPB outbreak on either DAB or observed fire behavior. Instead, greater DAB and observations of high-extreme fire behavior occurred during warmer, drier, and windier weather conditions and where pre-outbreak fuels were characterized by lower canopy base heights and greater canopy bulk densities. The overriding influence of weather and pre-outbreak fuel conditions on daily fire activity observed here suggest that efforts to reduce the risk of extreme fire activity should focus on societal adaption to future warming and extreme weather.

Frequent cloud cover in the tropics significantly affects the observation of the surface by satellites. This has enormous implications for current approaches that estimate greenhouse gas (GHG) emissions from fires or map fire scars. These mainly employ data acquired in the visible to middle infrared bands to map fire scars or thermal data to estimate fire radiative power and consequently derive emissions. The analysis here instead explores the use of microwave data from the operational Sentinel-1A (S-1A) in dual-polarisation mode (VV and VH) acquired over Central Kalimantan during the 2015 fire season. Burnt areas were mapped in three consecutive periods between August and October 2015 using the random forests machine learning algorithm. In each mapping period, the omission and commission errors of the unburnt class were always below 3%, while the omission and commission errors of the burnt class were below 20% and 5% respectively. Summing the detections from the three periods gave a total burnt area of ∼1.6 million ha, but this dropped to ∼1.2 million ha if using only a pair of pre- and post-fire season S-1A images. Hence the ability of Sentinel-1 to make frequent observations significantly increases fire scar detection. Comparison with burnt area estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area product at 5 km scale showed poor agreement, with consistently much lower estimates produced by the MODIS data-on average 14%–51% of those obtained in this study. The method presented in this study offers a way to reduce the substantial errors likely to occur in optical-based estimates of GHG emissions from fires in tropical areas affected by substantial cloud cover.

A stronger than global mean warming trend is projected over Central Asia in the coming century. Based on the historical simulations and projections under four combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) provided by 15 models from the Sixth Phase of Coupled Model Intercomparison Project (CMIP6), we show a comprehensive picture of the future changes in precipitation over Central Asia under rapid warming and investigate possible mechanisms. At the end of the twenty-first century, robust increase of annual mean precipitation under all the scenarios is found (4.23 [2.60 to 7.36] %, 10.52 [5.05 to 13.36] %, 14.51 [8.11 to 16.91] %, 14.41 [9.58 to 21.26] % relative to the present-day for SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, respectively). The response of precipitation to increasing global mean temperature shows similar spatial patterns for the four scenarios with stronger changes over Tianshan mountain and the northern part of Central Asia. Further analysis reveals a wetting trend in spring and a drying trend in summer in both the north of Central Asia (NCA) and south of Central Asia (SCA). The wetting trend in spring is balanced by the increase of evaporation, while the drying trend in summer is mainly contributed by the decrease of vertical moisture advection. The thermodynamic effects associated with humidity changes contribute to the drying trends in both the two domains, while the dynamic effects favor for the drying trend in NCA and offset the drying trend in SCA. The response of precipitation to increasing temperature results in enhanced seasonalities for SCA and NCA, and an advancing of the first peak from summer to spring in the NCA.

Outdoor watering of lawns accounts for about half of single-family residential potable water demand in the arid southwest United States. Consequently, many water utilities in the region offer customers cash rebates to replace lawns with drought tolerant landscaping. Here we present a parcel-scale analysis of water savings achieved by a 'cash-for-grass' program offered to 60 000 homes in Southern California. The probability a resident will participate in the program, and the lawn area they replace with drought tolerant landscaping, both increase with a home's outdoor area. The participation probability is also higher if a home is occupied by its owner. From these results we derive and test a simple and generalizable probabilistic framework for upscaling water conservation behavior at the parcel-scale to overall water savings at the city- or water provider-scale, accounting for the probability distribution of parcel outdoor areas across a utility's service area, climate, cultural drivers of landscape choices, conservation behavior, equity concerns, and financial incentives.

Growth of high-elevation forests is generally temperature-limited and thus sensitive to warming. The Tibetan Plateau has experienced fast warming rates associated with decreased summer monsoon rainfall over the last century. However, whether such warming and monsoon-induced drought could offset a potential warming-driven enhancement of forest growth has not been examined. Here, we have compiled high-elevation forest growth data at 40 sites over the monsoonal Tibetan Plateau (MTP), and combined them in a high-elevation forest growth index (HEFGI) spanning 1567–2010. Tree growth in this region was significantly and positively correlated with July–October minimum temperatures during 1950–2010 (R² = 0.53 P < 0.001), and insignificantly coherent with soil moisture and precipitation. The HEFGI of MTP reaches its highest values from the 2000s onwards. This result suggests that the mean HEFGI of MTP has not been negatively affected by the current drying trend and responded positively to increased temperatures.

Solid waste management represents one of the largest anthropogenic methane emission sources. However, precise quantification of landfill and composting emissions remains difficult due to variety of site-specific factors that contribute to landfill gas generation and effective capture. Remote sensing is an avenue to quantify process-level emissions from waste management facilities. The California Methane Survey flew the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) over 270 landfills and 166 organic waste facilities repeatedly during 2016–2018 to quantify their contribution to the statewide methane budget. We use representative methane retrievals from this campaign to present three specific findings where remote sensing enabled better landfill and composting methane monitoring: (1) Quantification of strong point source emissions from the active face landfills that are difficult to capture by in situ monitoring or landfill models, (2) emissions that result from changes in landfill infrastructure (design, construction, and operations), and (3) unexpected large emissions from two organic waste management methods (composting and digesting) that were originally intended to help mitigate solid waste emissions. Our results show that remotely-sensed emission estimates reveal processes that are difficult to capture in biogas generation models. Furthermore, we find that airborne remote sensing provides an effective avenue to study the temporally changing dynamics of landfills. This capability will be further improved with future spaceborne imaging spectrometers set to launch in the 2020s.

Climate model projections for the 21st century predict an elongated dry season in the Amazon basin, potentially reducing the discharge into the equatorial Atlantic Ocean. In order to understand the climatic role of Amazon runoff into the ocean, sensitivity experiments were carried out using the Community Earth System Model (CESM). Without Amazon runoff, the Atlantic Meridional Overturning Circulation (AMOC) strengthens and the associated increase in northward heat transport induces a positive temperature anomaly in the North Atlantic Ocean with a spatial structure similar to the positive phase of the Atlantic Multidecadal Variability (AMV). A positive phase of AMV developed in the absence of Amazon runoff triggers a bipolar seesaw in SST across the thermal equator with warming to the north and cooling to the south. The boreal summer rainfall in the tropical Atlantic Ocean sector responds to this change in SST by displacing the intertropical convergence zone (ITCZ) to the north of its mean position. An alternate experiment by doubling the Amazon runoff shows a weakening of AMOC and AMV and a southward shift in the summer–time ITCZ. In both the experiments, we find that the largest change in rainfall is exhibited over the region where the AMV–induced decadal variability in rainfall is prominent, confirming the source of rainfall variability. Based on sensitivity experiments by varying the runoff, we propose that the Amazon discharge can affect the multidecadal variabilities, the AMOC and AMV, and thereby the low–frequency variability of rainfall over the tropical North Atlantic Ocean and northwest Africa. We conclude that the freshwater input from the Amazon plays a significant role in the sustained wet and dry climatic phases of rainfall events over the tropical North Atlantic Ocean and West African nations and thus have an impact on the regional hydrological cycle and economy.

On short (15-year) to mid-term (30-year) time-scales how the Earth's surface temperature evolves can be dominated by internal variability as demonstrated by the global-warming pause or 'hiatus'. In this study, we use six single model initial-condition large ensembles (SMILEs) and the Coupled Model Intercomparison Project 5 (CMIP5) to visualise the role of internal variability in controlling possible observable surface temperature trends in the short-term and mid-term projections from 2019 onwards. We confirm that in the short-term, surface temperature trend projections are dominated by internal variability, with little influence of structural model differences or warming pathway. Additionally we demonstrate that this result is independent of the model-dependent estimate of the magnitude of internal variability. Indeed, and perhaps counter intuitively, in all models a lack of warming, or even a cooling trend could be observed at all individual points on the globe, even under the largest greenhouse gas emissions. The near-equivalence of all six SMILEs and CMIP5 demonstrates the robustness of this result to the choice of models used. On the mid-term time-scale, we confirm that structural model differences and scenario uncertainties play a larger role in controlling surface temperature trend projections than they did on the shorter time-scale. In addition we show that whether internal variability still dominates, or whether model uncertainties and internal variability are a similar magnitude, depends on the estimate of internal variability, which differs between the SMILEs. Finally we show that even out to thirty years large parts of the globe (or most of the globe in MPI-GE and CMIP5) could still experience no-warming due to internal variability.

A cold tongue mode (CTM) formed in the 1980s as a La Niña-like stepwise response to recent global warming; however, a consensus has not been reached on the mechanism underlying the CTM formation. Here, we attribute the CTM to the enhanced deep convection of the warm pool regions over the western Pacific and south of North America. Increases in the sea surface temperatures in the two Pacific warm pool regions that occurred due to global warming exceeded the threshold of deep convection after the 1980s, which resulted in two opposite anomalous vertical circular circulation patterns and induced the CTM via the intensification, contraction, and westward shift of the Walker circulation and the uplift of the thermocline. Our results provide a novel explanation of the La Niña-like response under recent global warming.

Wind stilling has been observed in many regions across the Northern Hemisphere; however, the related mechanisms are not well understood. Analyses of the wind speed variations in South Korea during 1993–2015 in this study reveal that the annual-mean surface wind speeds at rural stations have increased by up to 0.41 m s⁻¹ decade⁻¹, while those at urban stations have decreased by up to −0.63 m s⁻¹ decade⁻¹. The local wind speed variations are found to be negatively correlated with the population density at the corresponding observation sites. Gustiness analyses show the increase in local surface roughness due to urbanization can explain the observed negative wind speed trends at urban stations as the urbanization effect overwhelms the positive wind speed trend due to climate change. The observed negative wind speed trend in urban areas are not found in the regional climate model simulations in the Coordinated Regional Climate Downscaling Experiment—East Asia (CORDEX-EA) as these models do not take into account the impact of urbanization on wind variations during the period. This study suggests that urbanization can play an important role in the recent wind stilling in rapidly developing regions such as South Korea. Our results suggest that future climate projections in CORDEX-EA may overestimate wind speeds in urban areas, and that future regional climate projections need to consider the effects of urbanization for a more accurate projection of wind speeds.

Background: Extreme heat is associated with increased morbidity but most studies examine this relationship in warm seasons. In Southern California, Santa Ana winds (SAWs) are associated with high temperatures during the fall, winter and spring, especially in the coastal region. Objectives: Our aim was to examine the relationship between hospitalizations and extreme heat events in the fall, winter and spring, and explore the potential interaction with SAWs. Methods: Hospitalizations from 1999–2012 were obtained from the Office of Statewide Health Planning and Development Patient Discharge Data. A time-stratified case crossover design was employed to investigate the association between off-season heat and hospitalizations for various diagnoses. We examined the additive interaction of SAWs and extreme heat events on hospitalizations. Results: Over 1.5 million hospitalizations occurred in the Southern California coastal region during non-summer seasons. The 99th percentile-based thresholds that we used to define extreme heat events varied from a maximum temperature of 22.8 °C to 35.1 °C. In the fall and spring, risk of hospitalization increased for dehydration (OR: 1.23, 95% CI: 1.04, 1.45 and OR: 1.47 95% CI: 1.25, 1.71, respectively) and acute renal failure (OR: 1.35, 95% CI: 1.15, 1.58 and OR: 1.39, 95% CI: 1.19, 1.63, respectively) during 1-day extreme heat events. We also found an association between 1-day extreme heat events and hospitalization for ischemic stroke, with the highest risk observed in December. The results indicate that SAWs correspond to extreme heat events, particularly in the winter. Finally, we found no additive interaction with SAWs. Discussion: Results suggest that relatively high temperatures in non-summer months are associated with health burdens for several hospitalization outcomes. Heat action plans should consider decreasing the health burden of extreme heat events year-round.

In summer 2018, an extraordinary heat wave with record-breaking high temperatures hit Northeast Asia. However, the contribution of atmospheric circulation to this heat wave remains unknown. In this study, we quantify the contribution of circulation by using the flow analogue method. It is found that Northeast China, Korea and Japan were the most affected areas by the heat event, from daily to monthly timescales. The persistent high temperature was associated with an anticyclonic anomaly over Northeast Asia, related to the record-breaking northward shift of the western Pacific subtropical high (WPSH). The persistent anomalous anticyclone played a dominant role in this heat event, explaining half of the magnitude of the heat event. Both thermodynamical change and dynamical change in recent decades have increased the probability of occurrence of this kind of heat event over Northeast Asia. Specifically, the change in dynamical flow explains a fraction of less than 20% of the increases in probability of heat events. The contribution of thermodynamical changes to heat events generally increases with the rarity of the extreme event.

Despite the gravity of the climate threat, governments around the world have struggled to pass and implement climate policies. Today, politicians and advocates are championing a new idea: linking climate policy to other economic and social reforms. Will this approach generate greater public support for climate action? Here, we test this coalition-building strategy. Using two conjoint experiments on a representative sample of 2,476 Americans, we evaluate the marginal impact of 40 different climate, social, and economic policies on support for climate reforms. Overall, we find climate policy bundles that include social and economic reforms such as affordable housing, a $15 minimum wage, or a job guarantee increase US public support for climate mitigation. Clean energy standards, regardless of which technologies are included, also make climate policy more popular. Linking climate policy to economic and social issues is particularly effective at expanding climate policy support among people of color.

Climate projections for the 21st century for CMIP6 are warmer than those for CMIP5 despite nominally identical instantaneous radiative forcing. Many climate modeling groups attribute the stronger warming in the CMIP6 projections to the higher climate sensitivity of the new generation of climate models, but here we demonstrate that also changes in the forcing datasets can play an important role, in particular the prescribed concentrations of greenhouse gases (GHG) that are used to force the models. In the EC-Earth3-Veg model the effective radiative forcing (ERF) is reduced by 1.4 W m⁻² when the GHG concentrations from SSP5-8.5 (used in CMIP6) are replaced by the GHG concentrations from RCP8.5 (used in CMIP5), and similar yet smaller reductions are seen for the SSP2-4.5/RCP4.5 and SSP1-2.6/RCP2.6 scenario pairs. From the reduced ERF we can estimate the temperature at the end of the century in a full climate simulation with the CMIP6 version of the EC-Earth model but using CMIP5 GHG concentrations instead. For the new SSP5-8.5 and SSP2-4.5 scenarios we find that 50% or more of the temperature increase from CMIP5 to CMIP6 at the end of the century is due to changes in the prescribed GHG concentrations. The implication is that CMIP5 and CMIP6 projections for the 21st century are difficult to compare with each other not only as models differ but also as the forcing conditions are not equal. Therefore, the communication of CMIP6 results to the impact, mitigation and adaptation communities has to be carefully formulated, taking into account the role of the updated GHG concentrations when interpreting the warmer climate projections for the 21st century.

Lakes play a crucial role in retaining water and altering biogeochemical processes on floodplains. Existing strategies and algorithms for estimation of water storage are insufficient for dynamic floodplain lakes due to the scarcity of available observations. Combining a time series of open water area with a fine spatial-temporal resolution by integrating Landsat and MODIS observations of Poyang Lake (China) with digital elevation models, and limited gauge data, generated water storage estimates as a function of surface hydrological connectivity. Despite possessing a relatively small portion of Poyang Lake's water volume, the floodplain lakes occupy a large part of the surface water area, especially in the low water period. Floodplain lakes, in particular, those distributed in the upper delta contribute to relieving drought conditions in Poyang Lake.

Previous research indicates that the effects of climate warming, including shrub expansion and increased fire frequency may lead to declining lichen abundance in arctic tundra and northern alpine areas. Lichens are important forage for caribou (Rangifer tarandus), whose populations are declining throughout most of North America. To clarify how lichen cover might affect caribou resource selection, ecologists require better data on the spatial distribution and abundance of lichen. Here, we use a combination of field data and satellite imagery to model lichen cover for a 583 200 km² area that fully encompasses nine caribou ranges in interior Alaska and Yukon. We aggregated data from in situ vegetation plots, aerial survey polygons and unmanned aerial vehicle (UAV) imagery to align with 30 m resolution Landsat pixels. We used these data to train a random forest model with a suite of environmental and spectral predictors to estimate lichen cover. We validated our lichen cover model using reserved training data and existing external datasets, and found that reserved data from aerial survey polygons (R² = 0.77) and UAV imagery (R² = 0.71) provided the best fit. We used our lichen cover map to evaluate the influence of estimated lichen cover on caribou resource selection in the Fortymile Herd from 2012 to 2018 during summer and winter. In both seasons, caribou avoided lichen-poor areas (0%–5% lichen cover) and showed stronger selection as lichen cover increased to ∼30%, above which selection leveled off. Our results suggest that terrestrial lichen cover is an important factor influencing caribou resource selection in northern boreal forests across seasons. Our lichen cover map goes beyond existing maps of lichen abundance and distribution because it incorporates extensive field data for model training and validation and estimates lichen cover over a much larger spatial extent. We expect our landscape-scale map will be useful for understanding trends in lichen abundance and distribution, as well as for caribou research, management and conservation.

A range of in situ, satellite and reanalysis products on a common daily 1° × 1° latitude/longitude grid were extracted from the Frequent Rainfall Observations on Grids database to help facilitate intercomparison and analysis of precipitation extremes on a global scale. 22 products met the criteria for this analysis, namely that daily data were available over global land areas from 50°S to 50°N since at least 2001. From these daily gridded data, 10 annual indices that represent aspects of extreme precipitation frequency, duration and intensity were calculated. Results were analysed for individual products and also for four cluster types: (i) in situ, (ii) corrected satellite, (iii) uncorrected satellite and (iv) reanalyses. Climatologies based on a common 13-year period (2001–2013) showed substantial differences between some products. Timeseries (which ranged from 13 years to 67 years) also highlighted some substantial differences between products. A coefficient of variation showed that the in situ products were most similar to each other while reanalysis products had the largest variations. Reanalyses however agreed better with in situ observations over extra-tropical land areas compared to the satellite clusters, although reanalysis products tended to fall into 'wet' and 'dry' camps overall. Some indices were more robust than others across products with daily precipitation intensity showing the least variation between products and days above 20 mm showing the largest variation. In general, the results of this study show that global space-based precipitation products show the potential for climate scale analyses of extremes. While we recommend caution for all products dependent on their intended application, this particularly applies to reanalyses which show the most divergence across results.

National forests in the United States are undergoing a spatially and temporally uneven governance transition in response to Congressional policies, agency mandates, and social and economic pressures, with many moving from a wholly state-led 'dominant federal' model to a more collaborative networked governance model which we refer to as 'social forestry'. While the broad contours of this transition have been observed and studied previously, there have been few attempts to characterize it using quantitative, qualitative, or geospatial methods. Here, we combine a novel remote sensing-based method with qualitative social science research to understand the emergence of social forestry and its implications for land use/land cover change associated with implementation of the Northwest Forest Plan (NWFP) in the Western Cascades of Oregon. We linked time-series satellite data with forest inventory data to track patterns of timber harvest at scales commensurate with timber management decision-making. We then compared these patterns to policy-based expectations. We found a significant disconnect between NWFP policy and actual timber harvest patterns, raising questions about the effectiveness of the NWFP land use allocation system and the 'land sparing' approach to managing tensions between conservation and production. Qualitative research, including semi-structured interviews with federal agency personnel and local stakeholders, shed light on the causal mechanisms and reciprocal relationships driving spatial patterns of timber harvesting, which we discuss in terms of the emergence of social forestry involving complex, place-based negotiations between the federal government and local veto actors advocating for conservation. Findings have implications for US Forest Service public engagement strategies and efforts to establish zones of agreement regarding timber harvesting, as well as broader discussions about the agency's future.