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The article explores how habitability loss is as an important dimension of climate risk assessment with complex linkages to migration, and approaches that apply quantitative models using uniform methodologies of regional scales. Topics include privileging physical sciences over social science understandings of local vulnerability and adaptive capacity; and migration with adaptation responses with climate determinism minimizes potential for human agency to find creative social contexts.

Background Changing climates have been causing variations in the number of global ischemic heart disease and stroke incidences, and will continue to affect disease occurrence in the future. Objectives To project temperature-related mortality for acute ischemic heart disease, and ischemic and hemorrhagic stroke with concomitant climate warming. Methods We estimated the exposure-response relationship between daily cause-specific mortality and daily mean temperature in Beijing. We utilized outputs from 31 downscaled climate models and two representative concentration pathways (RCPs) for the 2020s, 2050s, and 2080s. This strategy was used to estimate future net temperature along with heat- and cold-related deaths. The results for predicted temperature-related deaths were subsequently contrasted with the baseline period. Results In the 2080s, using the RCP8.5 and no population variation scenarios, the net total number of annual temperature-related deaths exhibited a median value of 637 (with a range across models of 434–874) for ischemic stroke; this is an increase of approximately 100% compared with the 1980s. The median number of projected annual temperature-related deaths was 660 (with a range across models of 580–745) for hemorrhagic stroke (virtually no change compared with the 1980s), and 1683 (with a range across models of 1351–2002) for acute ischemic heart disease (a slight increase of approximately 20% compared with the 1980s). In the 2080s, the monthly death projection for hemorrhagic stroke and acute ischemic heart disease showed that the largest absolute changes occurred in summer and winter while the largest absolute changes for ischemic stroke occurred in summer. Conclusions We projected that the temperature-related mortality associated with ischemic stroke will increase dramatically due to climate warming. However, projected temperature-related mortality pertaining to acute ischemic heart disease and hemorrhagic stroke should remain relatively stable over time. [ABSTRACT FROM AUTHOR]

Background Climate change is projected to increase the frequency, intensity, and duration of heat waves while reducing cold extremes, yet few studies have examined the relationship between temperature and fetal health. Objectives We estimate the impacts of extreme temperatures on birth weight and gestational age in Manhattan, a borough in New York City, and explore differences by socioeconomic status (SES). Methods We combine average daily temperature from 1985 to 2010 with birth certificate data in Manhattan for the same time period. We then generate 33 downscaled climate model time series to project impacts on fetal health. Results We find exposure to an extra day where average temperature <25 °F and >85 °F during pregnancy is associated with a 1.8 and 1.7 g (respectively) reduction in birth weight, but the impact varies by SES, particularly for extreme heat, where teen mothers seem most vulnerable. We find no meaningful, significant effect on gestational age. Using projections of temperature from these climate models, we project average net reductions in birth weight in the 2070–2099 period of 4.6 g in the business-as-usual scenario. Conclusions Results suggest that increasing heat events from climate change could adversely impact birth weight and vary by SES. [ABSTRACT FROM AUTHOR]

The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized. [ABSTRACT FROM AUTHOR]

A partnership between Earth scientists and institutional stewards is helping the National Aeronautics and Space Administration (NASA) prepare for a changing climate and growing climate-related vulnerabilities. An important part of this partnership is an agency-wide Climate Adaptation Science Investigator (CASI) Workgroup. CASI has thus far initiated 1) local workshops to introduce and improve planning for climate risks, 2) analysis of climate data and projections for each NASA Center, 3) climate impact and adaptation toolsets, and 4) Center-specific research and engagement. Partnering scientists with managers aligns climate expertise with operations, leveraging research capabilities to improve decision-making and to tailor risk assessment at the local level. NASA has begun to institutionalize this ongoing process for climate risk management across the entire agency, and specific adaptation strategies are already being implemented. A case study from Kennedy Space Center illustrates the CASI and workshop process, highlighting the need to protect launch infrastructure of strategic importance to the United States, as well as critical natural habitat. Unique research capabilities and a culture of risk management at NASA may offer a pathway for other organizations facing climate risks, promoting their resilience as part of community, regional, and national strategies. [ABSTRACT FROM AUTHOR]

This paper describes a time-sensitive approach to climate change projections that was developed as part of New York City's climate change adaptation process and that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well versed in risk management, helped to preselect the climate variables most likely to impact urban infrastructure and requested a projection range rather than a single 'most likely' outcome. The climate projections approach is transferable to other regions and is consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 GCMs and three emissions scenarios to calculate monthly change factors based on 30-yr average future time slices relative to a 30-yr model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. On the basis of these methods, the current 1-in-10-year coastal flood is projected to occur more than once every 3 years by the end of the century and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme-event frequency are highly uncertain. [ABSTRACT FROM AUTHOR]

Humid heat presents a major societal challenge through its impacts on human health, energy demand, and economic productivity, underlined by the projected emergence of conditions beyond human tolerance. However, systematic assessment of what drives the most extreme humid heat worldwide has been lacking. Here, we investigate factors determining the location and magnitude of humid‐heat extremes, framing our analysis around the four regions with the highest values: the southern Persian Gulf, north‐central Pakistan, eastern South Asia, and the western Amazon. We find that strong boundary‐layer moisture fluxes, together with stability that inhibits moist convection, explain well the timing and location of near‐surface humid‐heat extremes. These favorable conditions are achieved through regionally distinct factors, including shallow sea breezes in the Persian Gulf and large‐scale subsidence in eastern South Asia. Our results demonstrate some of the principal controls on the most intense humid heat, both globally and for particular regions and heat events. Plain Language Summary: Combinations of high temperatures and high humidity are a primary threat of climate change because they can be not only uncomfortable but deadly, and are growing rapidly in frequency and intensity. In this study, we present a general theory for where the most extreme such events occur and describe the precise meteorological conditions that favor them. We are therefore able to state with new confidence the reasons why extreme humid heat events take place where they do, and why. Our results also highlight the regional distinctions in the factors (such as winds or ocean temperatures) that contribute to these events, increasing the strength of the evidence that some regions are much more sensitive to certain factors than others—information that can be used to guide better forecasts as well as climate‐change projections. Key Points: A systematic assessment of humid‐heat hotspots reveals the dual importance of vertical stability and low‐level moisture sourcesThese two conditions are achieved through markedly different meteorological processes and in markedly different geographical contextsUnderstanding the most extreme humid heat requires applying global principles to detailed regional analyses across space and time scales [ABSTRACT FROM AUTHOR]

The article discusses emergence of heat and humidity too severe for human tolerance. It mentions that exceedances of 35 degree Celsius in global maximum sea surface temperature provide further support for the validity of these dangerously high wet-bulb temperature (TW) values. It also mentions Generalized Extreme Value (GEV) analysis to estimate the amount of global warming from the preindustrial period until TW will regularly exceed 35 degree Celsius in the Persian Gulf area.

BACKGROUND: High temperatures have substantial impacts on mortality and, with growing concerns about climate change, numerous studies have developed projections of future heat-related deaths around the world. Projections of temperature-related mortality are often limited by insufficient information to formulate hypotheses about population sensitivity to high temperatures and fixture demographics. OBJECTIVES: The present study derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound influences on fixture health burdens. METHODS: We adopted a novel approach to modeling heat adaptation by incorporating an analysis of the observed population response to heat in New York City over the course of eight decades. This approach projected heat-related mortality until the end of the 21st century based on observed trends in adaptation over a substantial portion of the 20th century. In addition, we incorporated a range of new scenarios for population change until the end of the 21st century. We then estimated future heat-related deaths in New York City by combining the changing temperature -- mortality relationship and population scenarios with downscaled temperature projections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCPs). RESULTS: The median number of projected annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population change scenario, ranging from 167 to 3,331 in the 2080s compared with 638 heat-related deaths annually between 2000 and 2006. CONCLUSIONS: These findings provide a more complete picture of the range of potential future heat-related mortality risks across the 21st century in New York City, and they highlight the importance of both demographic change and adaptation responses in modifying future risks. CITATION: Petkova EP, Vink JK, Horton RM, Gasparrini A, Bader DA, Francis JD, Kinney PL. 2017. Towards more comprehensive projections of urban heat-related mortality: estimates for New York City under multiple population, adaptation, and climate scenarios. Environ Health Perspect 125:47-55; http://dx.doi.org/10.1289/EHPl66 [ABSTRACT FROM AUTHOR]

The impact of extreme heat on crop yields is an increasingly pressing issue given anthropogenic climate warming. However, some of the physical mechanisms involved in these impacts remain unclear, impeding adaptation-relevant insight and reliable projections of future climate impacts on crops. Here, using a multiple regression model based on observational data, we show that while extreme dry heat steeply reduced U.S. corn and soy yields, humid heat extremes had insignificant impacts and even boosted yields in some areas, despite having comparably high dry-bulb temperatures as their dry heat counterparts. This result suggests that conflating dry and humid heat extremes may lead to underestimated crop yield sensitivities to extreme dry heat. Rainfall tends to precede humid but not dry heat extremes, suggesting that multivariate weather sequences play a role in these crop responses. Our results provide evidence that extreme heat in recent years primarily affected yields by inducing moisture stress, and that the conflation of humid and dry heat extremes may lead to inaccuracy in projecting crop yield responses to warming and changing humidity. [ABSTRACT FROM AUTHOR]

Climate change necessitates a global effort to reduce greenhouse gas emissions while adapting to increased climate risks. This broader climate transition will involve largescale global interventions including renewable energy deployment, coastal protection and retreat, and enhanced space cooling, all of which will result in CO2 emissions from energy and materials use. Yet, the magnitude of the emissions embedded in these interventions remains unconstrained, opening the potential for underaccounting of emissions and conflicts or synergies between mitigation and adaptation goals. Here, we use a suite of models to estimate the CO2 emissions embedded in the broader climate transition. For a gradual decarbonization pathway limiting warming to 2 °C, selected adaptation-related interventions will emit ~1.3 GtCO2 through 2100, while emissions from energy used to deploy renewable capacity are much larger at ~95 GtCO2. Together, these emissions are equivalent to over 2 y of current global emissions and 8.3% of the remaining carbon budget for 2 °C. Total embedded transition emissions are reduced by ~80% to 21.2 GtCO2 under a rapid pathway limiting warming to 1.5 °C. However, they roughly double to 185 GtCO2 under a delayed pathway consistent with current policies (2.7 °C warming by 2100), mainly because a slower transition relies more on fossil fuel energy. Our results provide a holistic assessment of carbon emissions from the transition itself and suggest that these emissions can be minimized through more ambitious energy decarbonization. We argue that the emissions from mitigation, but likely much less so from adaptation, are of sufficient magnitude to merit greater consideration in climate science and policy. [ABSTRACT FROM AUTHOR]

Extreme humid heat events have seen rapid increases globally in recent decades, but regional changes and higher‐order temporal characteristics, such as interannual and intra‐annual clustering, have not been widely explored. Using ERA5 reanalysis data from 1979 to 2019, we find increasing trends of varying magnitudes in extreme wet‐bulb temperatures at the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) regional scale. In many locations, interannual variations in extremes show a strong relationship with the El Niño‐Southern Oscillation. The temporal proximity of precipitation events to humid heat days in arid regions suggests that local moisture effects may lead to clustering. Knowledge of these spatial and temporal patterns aids in understanding how potential heat stress is increasing, as well as facilitates the development of regionally specific adaptation and mitigation strategies for combating the associated societal impacts. Plain Language Summary: Extreme humid heat, or the combination of high temperature and humidity, poses a more severe threat to human health than does dry heat alone. Though extremes are particularly dangerous, even moderate levels of humid heat can lead to a variety of health and socioeconomic effects. Motivated by the growing demand for regional, decision‐relevant climate information, we calculate historical changes in the intensity of humid heat extremes in the regions used in the Intergovernmental Panel on Climate Change Sixth Assessment Report. Humid heat extremes have intensified in most regions, though some areas have experienced greater increases than others. The timing of extremes also affects their impacts, and thus we additionally analyze how humid heat extremes are distributed, both within the year and across all years. In many locations across the world, extreme humid heat is more common during strong El Niño episodes. In some typically dry regions, extremes tend to occur near each other within a given year and around the same time as rainfall events. Our results help advance the understanding of potential heat stress and the development of regionally specific strategies for combating its impacts. Key Points: From 1979 to 2019, extreme wet‐bulb temperatures intensified in most IPCC AR6 regions, though to varying degreesPatterns in interannual clustering of extreme humid heat show signals of the overall warming trend and the El Niño‐Southern OscillationIn some arid regions, extreme humid heat days often occur in close temporal proximity to one another and to precipitation events [ABSTRACT FROM AUTHOR]

Abstract: We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO2 concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors are reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields.Uncertainty around GCMs’ projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large interannual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the important uncertainties behind the selection of climate change metrics and their performance against more complex process-based crop model simulations, revealing a danger in relying only on long-term mean quantities for crop impact assessment. [Copyright &y& Elsevier]

Sea ice variability in the North Pacific and its associations with the east Asia–North Pacific winter climate were investigated using observational data. Two dominant modes of sea ice variability in the North Pacific were identified. The first mode features a dipole pattern between the Sea of Okhotsk and the Bering Sea. The second mode is characterized by more uniform ice changes throughout the North Pacific. Using the principal components of the two dominant modes as the indices (PC1 and PC2), analyses show that the positive phases of PC1 feature a local warming (cooling) in the Sea of Okhotsk (the Bering Sea), which is associated with the formation of the anomalous anticyclone extending from the northern Pacific to Siberia, accompanied by a weakening of the east Asian jet stream and trough. The associated anomalous southeasterlies/easterlies reduce the climatological northwesterlies/westerlies, leading to warm and wet conditions in northeast China and central Siberia. The positive phases of PC2 are characterized by a strong local warming in the northern Pacific that coincides with the anomalous cyclone occupying the entire North Pacific, accompanied by a strengthening of the east Asia jet stream and trough. The associated anomalous northerlies intensify the east Asian winter monsoon (EAWM), leading to cold and dry conditions in the east coast of Asia. The intensified EAWM also strengthens the local Hadley cell, which in turn strengthens the east Asian jet stream and leads to a precipitation deficit over subtropical east Asia. The linkages between PC1 and PC2 and large-scale modes of climate variability were also discussed. It is found that PC1 is a better indicator than the Arctic Oscillation of the recent Siberian warming, whereas PC2 may be a valuable predictor of EAWM. [ABSTRACT FROM AUTHOR]

Extreme heat research has largely focused on dry‐heat, while humid‐heat that poses a substantial threat to human‐health remains relatively understudied. Using hourly high‐resolution ERA5 reanalysis and HadISD station data, we provide the first spatially comprehensive, global‐scale characterization of the magnitude, seasonal timing, and frequency of dry‐ and wet‐bulb temperature extremes and their trends. While the peak dry‐ and humid‐heat extreme occurrences often coincide, their timing differs in climatologically wet regions. Since 1979, dry‐ and humid‐heat extremes have become more frequent over most land regions, with the greatest increases in the tropics and Arctic. Humid‐heat extremes have increased disproportionately over populated regions (∼5.0 days per‐person per‐decade) relative to global land‐areas (∼3.6 days per‐unit‐land‐area per‐decade) and population exposure to humid‐heat has increased at a faster rate than to dry‐heat. Our study highlights the need for a multivariate approach to understand and mitigate future harm from heat stress in a warming world. Plain Language Summary: Combined high temperature and humidity can be more dangerous to humans and wildlife relative to high temperature alone. There are known physiological limits to humid‐heat and adverse impacts on human‐health and performance can be felt well below those limits. Thus, it is important we understand their climatological characteristics and recent changes. Prior research on heat extremes has largely focused on dry‐heat. Using two high‐spatial resolution datasets, we provide a global‐scale characterization of the magnitude, seasonal timing, and frequency of dry‐ and humid‐heat extremes and their historical trends. While dry‐ and humid‐heat extremes occur at the same time of the year in most regions, their timing differs by multiple months in tropical regions with high rainfall. Over the past four decades, dry‐ and humid‐heat extremes have become more frequent over most land regions, with the greatest increases in the tropics and Arctic. Since 1979, each person, on average, has experienced an increase of approximately five additional extreme humid‐heat days per‐decade. These increases are concentrated over densely populated regions in the tropics and sub‐tropics, where humid‐heat levels are already high. Our results emphasize the increasing risk from dangerous heat stress, particularly in vulnerable regions of the world. Key Points: Global patterns and trends in magnitude, timing, and frequency of dry and humid‐heat extremes in ERA5 compare well with HadISD station dataLargest increases in frequency, intensity, and months of occurrence of dry‐ and humid‐heat extremes in tropical and Arctic regionsStronger trends in population exposure to extreme humid‐heat relative to dry‐heat and greater amplification during recent El Niños [ABSTRACT FROM AUTHOR]

Extreme heat research has largely focused on dry‐heat, while humid‐heat that poses a substantial threat to human‐health remains relatively understudied. Using hourly high‐resolution ERA5 reanalysis and HadISD station data, we provide the first spatially comprehensive, global‐scale characterization of the magnitude, seasonal timing, and frequency of dry‐ and wet‐bulb temperature extremes and their trends. While the peak dry‐ and humid‐heat extreme occurrences often coincide, their timing differs in climatologically wet regions. Since 1979, dry‐ and humid‐heat extremes have become more frequent over most land regions, with the greatest increases in the tropics and Arctic. Humid‐heat extremes have increased disproportionately over populated regions (∼5.0 days per‐person per‐decade) relative to global land‐areas (∼3.6 days per‐unit‐land‐area per‐decade) and population exposure to humid‐heat has increased at a faster rate than to dry‐heat. Our study highlights the need for a multivariate approach to understand and mitigate future harm from heat stress in a warming world. Plain Language Summary: Combined high temperature and humidity can be more dangerous to humans and wildlife relative to high temperature alone. There are known physiological limits to humid‐heat and adverse impacts on human‐health and performance can be felt well below those limits. Thus, it is important we understand their climatological characteristics and recent changes. Prior research on heat extremes has largely focused on dry‐heat. Using two high‐spatial resolution datasets, we provide a global‐scale characterization of the magnitude, seasonal timing, and frequency of dry‐ and humid‐heat extremes and their historical trends. While dry‐ and humid‐heat extremes occur at the same time of the year in most regions, their timing differs by multiple months in tropical regions with high rainfall. Over the past four decades, dry‐ and humid‐heat extremes have become more frequent over most land regions, with the greatest increases in the tropics and Arctic. Since 1979, each person, on average, has experienced an increase of approximately five additional extreme humid‐heat days per‐decade. These increases are concentrated over densely populated regions in the tropics and sub‐tropics, where humid‐heat levels are already high. Our results emphasize the increasing risk from dangerous heat stress, particularly in vulnerable regions of the world. Key Points: Global patterns and trends in magnitude, timing, and frequency of dry and humid‐heat extremes in ERA5 compare well with HadISD station dataLargest increases in frequency, intensity, and months of occurrence of dry‐ and humid‐heat extremes in tropical and Arctic regionsStronger trends in population exposure to extreme humid‐heat relative to dry‐heat and greater amplification during recent El Niños [ABSTRACT FROM AUTHOR]

Aim: Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose (Alces alces), a charismatic species of conservation and public interest. Location: The northeastern United States, along the trailing edge of the moose geographic range in North America. Methods: We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use. Results: We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times. Main conclusions: Our results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation. [ABSTRACT FROM AUTHOR]

The frequency of heat waves (defined as daily temperature exceeding the local 90th percentile for at least three consecutive days) during summer in the United States is examined for daily maximum and minimum temperature and maximum apparent temperature, in recent observations and in 10 CMIP5 models for recent past and future. The annual average percentage of days participating in a heat wave varied between approximately 2% and 10% in observations and in the model's historical simulations during 1979-2005. Applying today's temperature thresholds to future projections, heatwave frequencies rise to more than 20% by 2035-40. However, given the models' slight overestimation of frequencies and positive trend rates during 1979-2005, these projected heat-wave frequencies should be regarded cautiously. The models' overestimations may be associated with their higher daily autocorrelation than is found in observations. Heat-wave frequencies defined using apparent temperature, reflecting both temperature and atmospheric moisture, are projected to increase at a slightly (and statistically significantly) faster rate than for temperature alone. Analyses show little or no changes in the day-to-day variability or persistence (autocorrelation) of extreme temperature between recent past and future, indicating that the future heat-wave frequency will be due predominantly to increases in standardized (using historical period statistics) mean temperature and moisture content, adjusted by the local climatological daily autocorrelation. Using nonparametric methods, the average level and spatial pattern of future heat-wave frequency is shown to be approximately predictable on the basis of only projected mean temperature increases and local autocorrelation. These model-projected changes, even if only approximate, would impact infrastructure, ecology, and human well-being. [ABSTRACT FROM AUTHOR]

Abstract: Present and future freshwater availability and drought risks are physically tied to the responses of surface vegetation to increasing CO2. A single‐model large ensemble identifies the occurrence of colocated warming‐ and CO2‐induced leaf area index increases with summer soil moisture declines. This pattern of “greening” and “drying,” which occurs over 42% of global vegetated land area, is largely attributable to changes in the partitioning of precipitation at the land surface away from runoff and toward terrestrial vegetation ecosystems. Changes in runoff and ecosystem partitioning are inversely related, with changes in runoff partitioning being governed by changes in precipitation (mean and extremes) and ecosystem partitioning being governed by ecosystem water use and surface resistance to evapotranspiration (ET). Projections show that warming‐influenced and CO2‐enriched terrestrial vegetation ecosystems use water that historically would have been partitioned to runoff over 48% of global vegetated land areas, largely in Western North America, the Amazon, and Europe, many of the same regions with colocated greening and drying. These results have implications for how water available for people will change in response to anthropogenic warming and raise important questions about model representations of vegetation water responses to high CO2. [ABSTRACT FROM AUTHOR]

The northeastern United States has experienced a large increase in precipitation over recent decades. Annual and seasonal changes of total and extreme precipitation from station observations in the Northeast were assessed over multiple time periods spanning 1901-2014. Spatially averaged, both annual total and extreme precipitation across the Northeast increased significantly since 1901, with changepoints occurring in 2002 and 1996, respectively. Annual extreme precipitation experienced a larger increase than total precipitation; extreme precipitation from 1996 to 2014 is 53% higher than from 1901 to 1995. Spatially, coastal areas receive more total and extreme precipitation on average, but increases across the changepoints are distributed fairly uniformly across the domain. Increases in annual total precipitation across the 2002 changepoint are driven by significant total precipitation increases in fall and summer, while increases in annual extreme precipitation across the 1996 changepoint are driven by significant extreme precipitation increases in fall and spring. The ability of gridded observed and reanalysis precipitation data to reproduce station observations was also evaluated. Gridded observations perform well in reproducing averages and trends of annual and seasonal total precipitation, but extreme precipitation trends show significantly different spatial and domain-averaged trends than station data. The North American Regional Reanalysis generally underestimates annual and seasonal total and extreme precipitation means and trends relative to station observations, and also shows substantial differences in the spatial pattern of total and extreme precipitation trends within the Northeast. [ABSTRACT FROM AUTHOR]

The mountain regions of the northeastern United States are a critical socioeconomic resource for Vermont, New York State, New Hampshire, Maine, and southern Quebec. While global climate models (GCMs) are important tools for climate change risk assessment at regional scales, even the increased spatial resolution of statistically downscaled GCMs (commonly ~⅛°) is not sufficient for hydrologic, ecologic, and land-use modeling of small watersheds within the mountainous Northeast. To address this limitation, an ensemble of topographically downscaled, high-resolution (30″), daily 2-m maximum air temperature; 2-m minimum air temperature; and precipitation simulations are developed for the mountainous Northeast by applying an additional level of downscaling to intermediately downscaled (⅛°) data using high-resolution topography and station observations. First, observed relationships between 2-m air temperature and elevation and between precipitation and elevation are derived. Then, these relationships are combined with spatial interpolation to enhance the resolution of intermediately downscaled GCM simulations. The resulting topographically downscaled dataset is analyzed for its ability to reproduce station observations. Topographic downscaling adds value to intermediately downscaled maximum and minimum 2-m air temperature at high-elevation stations, as well as moderately improves domain-averaged maximum and minimum 2-m air temperature. Topographic downscaling also improves mean precipitation but not daily probability distributions of precipitation. Overall, the utility of topographic downscaling is dependent on the initial bias of the intermediately downscaled product and the magnitude of the elevation adjustment. As the initial bias or elevation adjustment increases, more value is added to the topographically downscaled product. [ABSTRACT FROM AUTHOR]

Background: A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships.Methods: We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100.Results: We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April - September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October-March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city.Conclusions: We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change. [ABSTRACT FROM AUTHOR]

Because heat-related health effects tend to become more serious at higher temperatures, there is an urgent need to determine the mortality projection of specific heat-sensitive diseases to provide more detailed information regarding the variation of the sensitivity of such diseases. In this study, the specific mortality of cardiovascular and respiratory disease in Beijing was initially projected under five different global-scale General Circulation Models (GCMs) and two Representative Concentration Pathways scenarios (RCPs) in the 2020s, 2050s, and 2080s compared to the 1980s. Multi-model ensembles indicated cardiovascular mortality could increase by an average percentage of 18.4%, 47.8%, and 69.0% in the 2020s, 2050s, and 2080s under RCP 4.5, respectively, and by 16.6%,73.8% and 134% in different decades respectively, under RCP 8.5 compared to the baseline range. The same increasing pattern was also observed in respiratory mortality. The heat-related deaths under the RCP8.5 scenario were found to reach a higher number and to increase more rapidly during the 21st century compared to the RCP4.5 scenario, especially in the 2050s and the 2080s. The projection results show potential trends in cause-specific mortality in the context of climate change, and provide support for public health interventions tailored to specific climate-related future health risks. [ABSTRACT FROM AUTHOR]

The Lake Champlain basin is a critical ecological and socioeconomic resource of the northeastern United States and southern Quebec, Canada. While general circulation models (GCMs) provide an overview of climate change in the region, they lack the spatial and temporal resolution necessary to fully anticipate the effects of rising global temperatures associated with increasing greenhouse gas concentrations. Observed trends in precipitation and temperature were assessed across the Lake Champlain basin to bridge the gap between global climate change and local impacts. Future shifts in precipitation and temperature were evaluated as well as derived indices, including maple syrup production, days above 32.2°C (90°F), and snowfall, relevant to managing the natural and human environments in the region. Four statistically downscaled, bias-corrected GCM simulations were evaluated from the Coupled Model Intercomparison Project phase 5 (CMIP5) forced by two representative concentration pathways (RCPs) to sample the uncertainty in future climate simulations. Precipitation is projected to increase by between 9.1 and 12.8 mm yr−1 decade−1 during the twenty-first century while daily temperatures are projected to increase between 0.43° and 0.49°C decade−1. Annual snowfall at six major ski resorts in the region is projected to decrease between 46.9% and 52.4% by the late twenty-first century. In the month of July, the number of days above 32.2°C in Burlington, Vermont, is projected to increase by over 10 days during the twenty-first century. [ABSTRACT FROM AUTHOR]

While the Arctic region has been warming strongly in recent decades, anomalously large snowfall in recent winters has affected large parts of North America, Europe, and east Asia. Here we demonstrate that the decrease in autumn Arctic sea ice area is linked to changes in the winter Northern Hemisphere atmospheric circulation that have some resemblance to the negative phase of the winter Arctic oscillation. However, the atmospheric circulation change linked to the reduction of sea ice shows much broader meridional meanders in midlatitudes and clearly different interannual variability than the classical Arctic oscillation. This circulation change results in more frequent episodes of blocking patterns that lead to increased cold surges over large parts of northern continents. Moreover, the increase in atmospheric water vapor content in the Arctic region during late autumn and winter driven locally by the reduction of sea ice provides enhanced moisture sources, supporting increased heavy snowfall in Europe during early winter and the northeastern and midwestern United States during winter. We conclude that the recent decline of Arctic sea ice has played a critical role in recent cold and snowy winters. [ABSTRACT FROM AUTHOR]

The article reports on the application of in situ measurements obtained from the Surface Heat Budget of the Arctic Ocean (SHEBA) as input values to four different snow/ice albedo parameterizations and evaluated the parameterized albedos against the SHEBA observed albedo. It shows that these parameterizations give very different representation of surface albedo. The impacts of systematic biases in the input values on the parameterized albedos are also assessed. It examined baseline sea ice characteristics and responses of sea ice to an external perturbation for the simulations of the albedo parameterizations using a stand-alone basin-scale dynamic sea ice model.