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The use of species distribution as a climate proxy for ecological forecasting is thought to be acceptable for invasive species. Kudzu (Pueraria montana var. lobata) is an important invasive whose northern distribution appears to be limited by winter survival; however, kudzu’s cold tolerance thresholds are uncertain. Here, we used biogeographic evidence to hypothesize that exposure to − 20 °C is lethal for kudzu and thus determines its northern distribution limit. We evaluated this hypothesis using survival tests and electrolyte leakage to determine relative conductivity, a measure of cell damage, on 14 populations from eastern North America. Relative conductivity above 36% was lethal. Temperatures causing this damage averaged − 19.6 °C for northern and − 14.4 °C for southern populations, indicating kudzu acclimates to winter cold. To assess this, we measured relative conductivity of above- and belowground stems, and roots collected throughout the winter at a kudzu population in southern Ontario, Canada. Consistent with acclimation, the cold tolerance threshold of aboveground stems at the coldest time of year was − 26 °C, while stems insulated from cold extremes survived to − 17 °C—colder than the survival limits indicated by kudzu’s biogeographic distribution. While these results do not rule out alternative cold limitations, they indicate kudzu can survive winters north of its current distribution. For kudzu, biogeography is not a proxy for climatic tolerance and continued northward migration is possible. Efforts to limit its spread are therefore prudent. These results demonstrate that physiological constraints inform predictions of climate-related changes in species distribution and should be considered where possible. [ABSTRACT FROM AUTHOR]

Annual precipitation in the largely agricultural South-Central United States is characterized by a primary wet season in May and June, a mid-summer dry period in July and August, and a second precipitation peak in September and October. Of the 22 CMIP5 global climate models with sufficient output available, 16 are able to reproduce this bimodal distribution (we refer to these as 'BM' models), while 6 have trouble simulating the mid-summer dry period, instead producing an extended wet season ('EW' models). In BM models, the timing and amplitude of the mid-summer westward extension of the North Atlantic Subtropical High (NASH) are realistic, while the magnitude of the Great Plains Lower Level Jet (GPLLJ) tends to be overestimated, particularly in July. In EW models, temporal variations and geophysical locations of the NASH and GPLLJ appear reasonable compared to reanalysis but their magnitudes are too weak to suppress mid-summer precipitation. During warm-season droughts, however, both groups of models reproduce the observed tendency towards a stronger NASH that remains over the region through September, and an intensification and northward extension of the GPLLJ. Similarly, future simulations from both model groups under a +1 to +3 °C transient increase in global mean temperature show decreases in summer precipitation concurrent with an enhanced NASH and an intensified GPLLJ, though models differ regarding the months in which these decreases are projected to occur: early summer in the BM models, and late summer in the EW models. Overall, these results suggest that projected future decreases in summer precipitation over the South-Central region appear to be closely related to anomalous patterns of large-scale circulation already observed and modeled during historical dry years, patterns that are consistently reproduced by CMIP5 models. [ABSTRACT FROM AUTHOR]

Among papers stating a position on anthropogenic global warming (AGW), 97 % endorse AGW. What is happening with the 2 % of papers that reject AGW? We examine a selection of papers rejecting AGW. An analytical tool has been developed to replicate and test the results and methods used in these studies; our replication reveals a number of methodological flaws, and a pattern of common mistakes emerges that is not visible when looking at single isolated cases. Thus, real-life scientific disputes in some cases can be resolved, and we can learn from mistakes. A common denominator seems to be missing contextual information or ignoring information that does not fit the conclusions, be it other relevant work or related geophysical data. In many cases, shortcomings are due to insufficient model evaluation, leading to results that are not universally valid but rather are an artifact of a particular experimental setup. Other typical weaknesses include false dichotomies, inappropriate statistical methods, or basing conclusions on misconceived or incomplete physics. We also argue that science is never settled and that both mainstream and contrarian papers must be subject to sustained scrutiny. The merit of replication is highlighted and we discuss how the quality of the scientific literature may benefit from replication. [ABSTRACT FROM AUTHOR]

Empirical statistical downscaling (ESD) methods seek to refine global climate model (GCM) outputs via processes that glean information from a combination of observations and GCM simulations. They aim to create value-added climate projections by reducing biases and adding finer spatial detail. Analysis techniques, such as cross-validation, allow assessments of how well ESD methods meet these goals during observational periods. However, the extent to which an ESD method's skill might differ when applied to future climate projections cannot be assessed readily in the same manner. Here we present a 'perfect model' experimental design that quantifies aspects of ESD method performance for both historical and late 21st century time periods. The experimental design tests a key stationarity assumption inherent to ESD methods - namely, that ESD performance when applied to future projections is similar to that during the observational training period. Case study results employing a single ESD method (an Asynchronous Regional Regression Model variant) and climate variable (daily maximum temperature) demonstrate that violations of the stationarity assumption can vary geographically, seasonally, and with the amount of projected climate change. For the ESD method tested, the greatest challenges in downscaling daily maximum temperature projections are revealed to occur along coasts, in summer, and under conditions of greater projected warming. We conclude with a discussion of the potential use and expansion of the perfect model experimental design, both to inform the development of improved ESD methods and to provide guidance on the use of ESD products in climate impacts analyses and decision-support applications. [ABSTRACT FROM AUTHOR]

We evaluate the ability of global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to reproduce observed seasonality and interannual variability of temperature over the Caribbean, and compare these with simulations from atmosphere-only (AMIP5) and previous-generation CMIP3 models. Compared to station and gridded observations, nearly every CMIP5, CMIP3 and AMIP5 simulation tends to reproduce the primary inter-regional features of the Caribbean annual temperature cycle. In most coupled model simulations, however, boreal summer temperature lags observations by about 1 month, with a similar lag in the simulated annual cycle of sea surface temperature (SST), and a systematic cold bias in both climatological annual mean air temperature and SST. There is some improvement from CMIP3 to CMIP5 but the bias is still marked compared to AMIP5 and observations, implying that biases in the annual temperature cycle may originate in the ocean component of the coupled models. This also suggests a tendency for models to over-emphasize the influence of SSTs on near-surface temperature, a bias that may be exacerbated by model tendency to over-estimate ocean mixed layer depth as well. In contrast, we find that both coupled and atmosphere-only models tend to reasonably simulate the response of observed temperature to global temperature, to regional and large-scale variability across the Caribbean region and the Gulf of Mexico, and even to more remote Atlantic and Pacific influences. These findings contribute to building confidence in the ability of coupled models to simulate the effect of global-scale change on the Caribbean. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the mean and variability of future spring and summer drought and wet conditions during the twenty-first century across North America, as characterized by the Standardized Precipitation Index (SPI). Based on Coupled Model Intercomparison Project phase 5 simulations, statistically significant increases are projected in mean spring SPI over the northern part of the continent, and drier conditions across the southwest. Dry conditions in summer also increase, particularly throughout the central Great Plains. By end of century, greater changes are projected under a higher radiative forcing scenario (RCP 8.5) as compared to moderate (RCP 6.0) and lower (RCP 4.5). Analysis of projected changes standardized to a range of global warming thresholds from +1 to +4 °C reveals a consistent spatial pattern of wetter conditions in the northern and drier conditions in the southwestern part of the continent in spring that intensifies under increased warming, suggesting that the magnitude of projected changes in wetness and drought may scale with global temperature. For many regions, SPI interannual variability is also projected to increase (even for regions that are projected to become drier), indicating that climate may become more extreme under greater warming, with increased frequency of both extreme dry and wet seasons. Quantifying the direction and magnitude of projected future trends from global warming is key to informing strategies to mitigate human influence on climate and help natural and managed resources adapt. [ABSTRACT FROM AUTHOR]

We assess the ability of Global Climate Models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) to simulate observed annual precipitation cycles over the Caribbean. Compared to weather station records and gridded observations, we find that both CMIP3 and CMIP5 models can be grouped into three categories: (1) models that correctly simulate a bimodal distribution with two rainfall maxima in May-June and September-October, punctuated by a mid-summer drought (MSD) in July-August; (2) models that reproduce the MSD and the second precipitation maxima only; and (3) models that simulate only one precipitation maxima, beginning in early summer. These categories appear related to model simulation of the North Atlantic Subtropical High (NASH) and sea surface temperature (SST) in the Caribbean Sea and Gulf of Mexico. Specifically, models in category 2 tend to anticipate the westward expansion of the NASH into the Caribbean in early summer. Early onset of NASH results in strong moisture divergence and MSD-like conditions at the time of the May-June observed precipitation maxima. Models in category 3 tend to have cooler SST across the region, particularly over the central Caribbean and the Gulf of Mexico, as well as a weaker Caribbean low-level jet accompanying a weaker NASH. In these models, observed June-like patterns of moisture convergence in the central Caribbean and the Central America and divergence in the east Caribbean and the Gulf of Mexico persist through September. This analysis suggests systematic biases in model structure may be responsible for biases in observed precipitation variability over the Caribbean and more confidence may be placed in the precipitation simulated by the GCMs that are able to correctly simulate seasonal cycles of SST and NASH. [ABSTRACT FROM AUTHOR]

Past heavy precipitation events in the Chicago metropolitan area have caused significant flood-related economic and environmental damages. A key component in flood management policies and actions is determining flood magnitudes for specified return periods. This is a particularly difficult task in areas with a complex and changing climate and land-use, such as the Chicago metropolitan area. The standard design storm methodology based on the NOAA Atlas 14 and ISWS Bulletin 70 has been used in the past to estimate flood hydrographs with variable return periods in this region. In a changing climate, however, these publications may not be accurate. This study presents and illustrates a methodology for diagnostic analysis of future climate scenarios in the framework of urban flooding, and assesses the corresponding uncertainties. First, the design storms are calculated using data downscaled by a regional climate model (RCM) at 30-km spacing for the present and 2050s under the IPCC A1Fi (high) and B1 (low) emissions scenarios. Next, the corresponding flood discharges at six watersheds in suburban Chicago are estimated using a hydrologic event model. The resulting scenarios in flood frequency were first assessed through a set of diagnostic tests for precipitation timing and frequency. The study did not reveal any significant changes in the 2050s in the average timing of heavy storms, but their regularity decreased. The average timing did not exhibit any significant spatial variability throughout the region. The precipitation frequency analysis revealed distinct differences between the northern and southeastern subregions of the Chicago metropolitan area. The quantiles in the northern subregion averaged for 2-year, 5-year, and 10-year return periods exhibited a 20% and 16% increase in daily precipitation for scenarios B1 and A1Fi, respectively. The southeastern subregion, however, exhibited a decrease of 12% for scenario B1 and a minor increase of 3% for scenario A1Fi. The hydrologic effects of changing precipitation on the flood quantiles were illustrated using six small watersheds in the region. The relative increases or decreases in precipitation translated into even larger relative increases or decreases in flood peaks, due to the nonlinear nature of the rainfall-runoff process. Simulations using multiple climate models, for longer periods, finer spatio-temporal resolution, and larger areal coverage could be used to more accurately account for numerous uncertainties in the precipitation and flood projections. [ABSTRACT FROM AUTHOR]

Potential changes in summertime hydroclimatology over the northeastern (NE) region of the USA induced by increases in greenhouse gas (GHG) concentrations are investigated using a state-of-the-art regional climate modeling system. Results for a higher emissions scenario illustrate changes that may occur if dependence on fossil fuels continues over the coming century. Summertime precipitation is projected to decrease across much of the central NE, but increase over the southernmost and northernmost portions of the domain. Evaporation is expected to increase across the entire domain. The balance between these two results in a decrease in soil moisture content across most of the domain (by approximately 10 mm) and an increase in the summertime soil-moisture depletion rate (by approximately 10 mm/month). At the same time, an increase in both atmospheric near-surface specific and saturation specific humidity is projected, resulting in an increase in relative humidity across the southern portion of the domain, with slight decreases over the northern portion. Combined with an average increase in summer temperatures of 3.5°C, the projected increase in relative humidity results in a marked increase in the average daily maximum heat index for the region on the order of 3.9°C, as well as a 350–400% increase in the number of days with heat index values exceeding 32.2°C (90°F)—the level of “extreme caution”. Taken together, these high-resolution, dynamically-generated projections confirm the potential for significant summertime climate change impacts on the NE over the coming century as suggested by previous studies. [ABSTRACT FROM AUTHOR]

Climate projections at relevant temporal and spatial scales are essential to assess potential future climate change impacts on climatologically diverse regions such as the northeast United States. Here, we show how both statistical and dynamical downscaling methods applied to relatively coarse-scale atmosphere-ocean general circulation model output are able to improve simulation of spatial and temporal variability in temperature and precipitation across the region. We then develop high-resolution projections of future climate change across the northeast USA, using IPCC SRES emission scenarios combined with these downscaling methods. The projections show increases in temperature that are larger at higher latitudes and inland, as well as the potential for changing precipitation patterns, particularly along the coast. While the absolute magnitude of change expected over the coming century depends on the sensitivity of the climate system to human forcing, significantly higher increases in temperature and in winter precipitation are expected under a higher as compared to lower scenario of future emissions from human activities. [ABSTRACT FROM AUTHOR]

Global climate change has already affected the abundances, range limits, and interactions of many species. The hemlock woolly adelgid (Adelges tsugae), an invasive insect introduced to eastern North America from Japan, has decimated stands of eastern hemlock (Tsuga canadensis) and Carolina hemlock (T. caroliniana) from Georgia to Connecticut. However, its spread across central and northern New England has been slowed substantially by its inability to tolerate cold winter temperatures. Using data from previous lab and field studies collected over the past 17 years, including adelgid spread and overwintering mortality, we first characterize the temperature conditions that may limit adelgid spread. We then show how, in the future, rising winter temperatures due to climate change are likely to remove the conditions currently limiting adelgid spread, and facilitate the northward expansion as more suitable habitat becomes available. [ABSTRACT FROM AUTHOR]

Most prior climate change assessments for U.S. agriculture have focused on major world food crops such as wheat and maize. While useful from a national and global perspective, these results are not particularly relevant to the Northeastern U.S. agriculture economy, which is dominated by dairy milk production, and high-value horticultural crops such as apples (Malus domestica), grapes (Vitis vinifera), sweet corn (Zea mays var. rugosa), cabbage (Brassica oleracea var. capitata), and maple syrup (sugar maple, Acer saccharum). We used statistically downscaled climate projections generated by the HadCM3 atmosphere-ocean general circulation model, run with Intergovernmental Panel on Climate Change future emissions scenarios A1fi (higher) and B1 (lower), to evaluate several climate thresholds of direct relevance to agriculture in the region. A longer (frost-free) growing season could create new opportunities for farmers with enough capital to take risks on new crops (assuming a market for new crops can be developed). However, our results indicate that many crops will have yield losses associated with increased frequency of high temperature stress, inadequate winter chill period for optimum fruiting in spring, increased pressure from marginally over-wintering and/or invasive weeds, insects, or disease, or other factors. Weeds are likely to benefit more than cash crops from increasing atmospheric carbon dioxide. Projections of thermal heat index values for dairy cows indicate a substantial potential negative impact on milk production. At the higher compared to lower emissions scenario, negative climate change effects will occur sooner, and impact a larger geographic area within the region. Farmer adaptations to climate change will not be cost- or risk-free, and the impact on individual farm families and rural communities will depend on commodity produced, available capital, and timely, accurate climate projections. [ABSTRACT FROM AUTHOR]

This study focused on how climate change-induced effects on weather will translate into changes in wildland fire severity and outcomes in California, particularly on the effectiveness of initial attack at limiting the number of fires that escape initial attack. The results indicate that subtle shifts in fire behavior of the sort that might be induced by the climate changes anticipated for the next century are of sufficient magnitude to generate an appreciable increase in the number of fires that escape initial attack. Such escapes are of considerable importance in wildland fire protection planning, given the high cost to society of a catastrophic escape like those experienced in recent decades in the Berkeley-Oakland, Santa Barbara, San Diego, or Los Angeles areas. However, at least for the three study areas considered, it would appear that relatively modest augmentations to existing firefighting resources might be sufficient to compensate for change-induced changes in wildland fire outcomes. [ABSTRACT FROM AUTHOR]

California's coastal observations and global model projections indicate that California's open coast and estuaries will experience rising sea levels over the next century. During the last several decades, the upward historical trends, quantified from a small set of California tide gages, have been approximately 20 cm/century, quite similar to that estimated for global mean sea level. In the next several decades, warming produced by climate model simulations indicates that sea level rise (SLR) could substantially exceed the rate experienced during modern human development along the California coast and estuaries. A range of future SLR is estimated from a set of climate simulations governed by lower (B1), middle-upper (A2), and higher (A1fi) GHG emission scenarios. Projecting SLR from the ocean warming in GCMs, observational evidence of SLR, and separate calculations using a simple climate model yields a range of potential sea level increases, from 11 to 72 cm, by the 2070-2099 period. The combination of predicted astronomical tides with projected weather forcing, El Niño related variability, and secular SLR, gives a series of hourly sea level projections for 2005-2100. Gradual sea level rise progressively worsens the impacts of high tides, surge and waves resulting from storms, and also freshwater floods from Sierra and coastal mountain catchments. The occurrence of extreme sea levels is pronounced when these factors coincide. The frequency and magnitude of extreme events, relative to current levels, follows a sharply escalating pattern as the magnitude of future sea level rise increases. [ABSTRACT FROM AUTHOR]

To investigate possible future climate changes in California, a set of climate change model simulations was selected and evaluated. From the IPCC Fourth Assessment, simulations of twenty-first century climates under a B1 (low emissions) and an A2 (a medium-high emissions) emissions scenarios were evaluated, along with occasional comparisons to the A1fi (high emissions) scenario. The climate models whose simulations were the focus of the present study were from the Parallel Climate Model (PCM1) from NCAR and DOE, and the NOAA Geophysical Fluid Dynamics Laboratory CM2.1 model (GFDL). These emission scenarios and attendant climate simulations are not "predictions," but rather are a purposely diverse set of examples from among the many plausible climate sequences that might affect California in the next century. Temperatures over California warm significantly during the twenty-first century in each simulation, with end-of-century temperature increases from approximately +1.5°C under the lower emissions B1 scenario in the less responsive PCM1 to +4.5°C in the higher emissions A2 scenario within the more responsive GFDL model. Three of the simulations (all except the B1 scenario in PCM1) exhibit more warming in summer than in winter. In all of the simulations, most precipitation continues to occur in winter. Relatively small (less than ~10%) changes in overall precipitation are projected. The California landscape is complex and requires that model information be parsed out onto finer scales than GCMs presently offer. When downscaled to its mountainous terrain, warming has a profound influence on California snow accumulations, with snow losses that increase with warming. Consequently, snow losses are most severe in projections by the more responsive model in response to the highest emissions. [ABSTRACT FROM AUTHOR]

To assess the influence of global climate change at the regional scale, we examine past and future changes in key climate, hydrological, and biophysical indicators across the US Northeast (NE). We first consider the extent to which simulations of twentieth century climate from nine atmosphere-ocean general circulation models (AOGCMs) are able to reproduce observed changes in these indicators. We then evaluate projected future trends in primary climate characteristics and indicators of change, including seasonal temperatures, rainfall and drought, snow cover, soil moisture, streamflow, and changes in biometeorological indicators that depend on threshold or accumulated temperatures such as growing season, frost days, and Spring Indices (SI). Changes in indicators for which temperature-related signals have already been observed (seasonal warming patterns, advances in high-spring streamflow, decreases in snow depth, extended growing seasons, earlier bloom dates) are generally reproduced by past model simulations and are projected to continue in the future. Other indicators for which trends have not yet been observed also show projected future changes consistent with a warmer climate (shrinking snow cover, more frequent droughts, and extended low-flow periods in summer). The magnitude of temperature-driven trends in the future are generally projected to be higher under the Special Report on Emission Scenarios (SRES) mid-high (A2) and higher (A1FI) emissions scenarios than under the lower (B1) scenario. These results provide confidence regarding the direction of many regional climate trends, and highlight the fundamental role of future emissions in determining the potential magnitude of changes we can expect over the coming century. [ABSTRACT FROM AUTHOR]

Projections of changes in climate extremes are critical to assessing the potential impacts of climate change on human and natural systems. Modeling advances now provide the opportunity of utilizing global general circulation models (GCMs) for projections of extreme temperature and precipitation indicators. We analyze historical and future simulations of ten such indicators as derived from an ensemble of 9 GCMs contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4), under a range of emissions scenarios. Our focus is on the consensus from the GCM ensemble, in terms of direction and significance of the changes, at the global average and geographical scale. The climate extremes described by the ten indices range from heat-wave frequency to frost-day occurrence, from dry-spell length to heavy rainfall amounts. Historical trends generally agree with previous observational studies, providing a basic sense of reliability for the GCM simulations. Individual model projections for the 21st century across the three scenarios examined are in agreement in showing greater temperature extremes consistent with a warmer climate. For any specific temperature index, minor differences appear in the spatial distribution of the changes across models and across scenarios, while substantial differences appear in the relative magnitude of the trends under different emissions rates. Depictions of a wetter world and greater precipitation intensity emerge unequivocally in the global averages of most of the precipitation indices. However, consensus and significance are less strong when regional patterns are considered. This analysis provides a first overview of projected changes in climate extremes from the IPCC-AR4 model ensemble, and has significant implications with regard to climate projections for impact assessments. [ABSTRACT FROM AUTHOR]

Environmental and societal factors such as air quality, water quality and availability, land use changes and expanding urbanization are already affecting human health and welfare, agriculture, and natural ecosystems in the Midwestern United States. Over this century, these existing stresses will likely be exacerbated by climate changes resulting from human activities. It is essential that policy decisions aimed at preserving the well-being of a region be informed by a good understanding of the region's climate, how climate might change, and the uncertainties inherent in future projections. Recent updates in climate modeling expertise and an expanded view of possible non-intervention emission scenarios have narrowed the range of change that can be expected over the Midwest throughout the next century in some ways, while broadening it in others. In contrast to previous studies, which generally consider a mid-range scenario for future emissions, this study presents the range of change that would result from low to high scenarios for climate change. In this way we account for uncertainties in anthropogenic forcing on climate change in the region and quantify the potential effects of human actions on future climate. This analysis also combines the latest climate model projections with historical records of observed climate over the past century, effectively placing potential changes in extreme event frequencies such as heavy rainfall events and temperature threshold exceedances within the context of observed variability over the past century. The purpose of this study is to provide an updated picture of the potential impacts of climate change on the Midwest to inform the impact assessment and policy development community. From the magnitude of the changes projected by this study, it is clear that these must be included in future policy decisions in order to ensure the successful adaptation and survival of existing human and natural systems in the Midwest. [ABSTRACT FROM AUTHOR]

Assesses the effectiveness of an emission reduction strategy as a means of mitigating the net impact of human activities on climate for the substitution of gas for coal. Key substances included in the substitution of gas for coal; Methane emissions from coal mining and natural gas loss; Time-dependent sensitivity of the benefits of fuel switching to key options in a given gas-for-coal substitution.

The article presents a correction to the article "Going to the extremes: An intercomparison of model-simulated historical and future changes in extreme events," which was published in the 15 March 2007 issue.

The massive deployment of clean energy technologies plays a vital role in the strategy to attain carbon neutrality by 2050 and allow subsequent negative CO2 emissions in order to achieve our climate goals. An emerging challenge, known as ‘From Emissions to Resources,’ highlights the significant increase in demand for critical raw materials (CRMs) in clean energy technologies. Despite the presence of ample geological reserves, ensuring sustainable access to these materials is crucial for the successful transition to clean energy, taking into account the environmental and social impacts. The commentary centers on four renewable energy technologies namely solar photovoltaics, wind turbines, Li-ion batteries, and water electrolysers. Four pathways for mitigation are quantitatively examined to assess their potential in reducing the vulnerability of the CRM supply chain for these four clean energy technologies: (i) Enhancing material efficiency, (ii) employing substitutivity strategies, (iii) exploring recycling prospects, and (iv) promoting relocalisation initiatives. It is important to note that no single mitigation lever can completely eliminate the risk of CRM supply, rather the accelerated adoption of all four levers is necessary to minimize the CRM supply risk to its absolute minimum. Hence, the study underscores the significance of increased research, innovation, and regulatory initiatives, along with raising social awareness, in effectively addressing the challenges faced by the CRM supply chain and contributing to a sustainable energy transition. [ABSTRACT FROM AUTHOR]