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ABSTRACT The asynchronous regional regression model ( ARRM) is a flexible and computationally efficient statistical model that can downscale station-based or gridded daily values of any variable that can be transformed into an approximately symmetric distribution and for which a large-scale predictor exists. This technique was developed to bridge the gap between large-scale outputs from atmosphere-ocean general circulation models ( AOGCMs) and the fine-scale output required for local and regional climate impact assessments. ARRM uses piecewise regression to quantify the relationship between observed and modelled quantiles and then downscale future projections. Here, we evaluate the performance of three successive versions of the model in downscaling daily minimum and maximum temperature and precipitation for 20 stations in North America from diverse climate zones. Using cross-validation to maximize the independent comparison period, historical downscaled simulations are evaluated relative to observations in terms of three different quantities: the probability distributions, giving a visual image of the skill of each model; root-mean-square errors; and bias in nine quantiles that represent both means and extremes. Successive versions of the model show improved accuracy in simulating extremes, where AOGCMs are often most biased and which are frequently the focus of impact studies. Overall, the quantile regression-based technique is shown to be efficient, robust, and highly generalizable across multiple variables, regions, and climate model inputs. [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]

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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]

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]

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]

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]

The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades. [ABSTRACT FROM AUTHOR]

• Some types of weather affect Americans' belief that they have experienced global warming. • Americans associate hot, dry days and extreme drought with global warming. • People often fail to interpret extreme rainfall or flooding as due to global warming. Public perceptions of climate change in the United States are deeply rooted in cultural values and political identities. Yet, as the public experiences extreme weather and other climate change-related impacts, their perceptions of the issue may shift. Here, we explore whether, when, and where local climate trends have already influenced perceived experiences of global warming in the United States. Using a large national survey dataset (n = 13,607), we compare Americans' experiences of climate with corresponding trends in seven different high-resolution climate indicators for the period 2008 to 2015. We find that increases in hot dry day exposure significantly increases individuals' perceptions that they have personally experienced global warming. We do not find robust evidence that other precipitation and temperature anomalies have had a similar effect. We also use multilevel modeling to explore county-level patterns of perceived experiences with climate change. Whereas the individual-level analysis describes a likely causal relationship between a changing climate and individuals' perceived experience, the multilevel model depicts county-level changes in perceived experience resulting from particular climate trends. Overall, we find that exposure to hot dry days, has a modest influence on perceived experience, independent of the political and socio-demographic factors that dominate U.S. climate opinions today. [ABSTRACT FROM AUTHOR]

Historically, extreme hot, dry summers over the South‐Central (SC) United States are dominated by an isolated dome of high pressure centered over the region. Applying self‐organizing map techniques to North American Regional Reanalysis reanalysis and historical and future Coupled Model Intercomparison Project version 5 (CMIP5) simulations, we find that as the world warms, this type of high‐pressure system is likely to become stronger and more frequent—even after removing the effect of surface warming on the expansion of the lower atmosphere. These projected changes appear to be related to self‐reinforcing ocean‐atmosphere interactions in a warming world. Specifically, intensified easterly winds over the Atlantic and Gulf of Mexico drive an increase in the meridional sea surface temperature gradient due to oceanic Ekman transport, which further enhances the ridge of high pressure extending across the SC United States: a dynamical relationship that increases confidence in regional projections of summer drought risk over the SC United States. Plain Language Summary: Water is already a scarce resource in the South‐Central United States. The region's frequent droughts pit its agriculture community against the energy industry, ecosystem managers, and growing municipalities in competition for the region's increasingly over‐allocated water resources. Our study identifies the daily weather patterns associated with historical drought and examines how these are likely to change as the world gets warmer. We find that the main weather pattern associated with drought, an isolated dome of high pressure centered over the South‐Central region, is likely to become stronger and more frequent by the late 21st century under human‐induced climate change. We also find that this appears to be related to self‐reinforcing ocean‐atmosphere interactions: in other words, the warmer the world gets, the stronger this pattern becomes. This is not good news for the region, as it establishes a physical mechanism that explains why projected summer rainfall is expected to decrease, and droughts to become stronger and longer, as climate continues to change. Key Points: Extreme hot and dry summers over the South‐Central United States are historically characterized by an isolated dome of high pressure over the regionFuture projections indicate that this high‐pressure system is likely to become stronger and more frequent, as climate changesProjected changes in the high‐pressure system appear to be related to self‐reinforcing ocean‐atmosphere interactions in a warming world [ABSTRACT FROM AUTHOR]

To what extent will increasing High Occupancy Vehicle (HOV) lane-kilometer incentivize carpooling and reduce emissions of air pollutants and greenhouse gases? To answer these questions, we develop a multiple regression model relating HOV lanes and other socioeconomic factors to carpooling propensity in all 50 U.S. states and the District of Columbia, then calculate the extent to which increasing HOV lane-kilometers would lead to reductions in carbon dioxide equivalent (CO 2 e) and major air pollutants across the U.S., by state. Increasing HOV lane extent has the greatest potential to reduce annual CO 2 e in the District of Columbia, followed by Hawaii and New York. The smallest potential is found in states with the lowest population density, led by North Dakota. We then explore the extent to which recommendations made at one level of data aggregation (that of individual states) may be valid for another level, such as individual counties. The only state with sufficient data available to disaggregate the model to the county level is California, where we found a lower potential for state-wide CO 2 e emission reductions under the county-level model as compared to the state-level model (0.69% as compared to 1.08%, under the same hypothetical scenario), albeit with significant differences in emission reduction potential between counties with higher vs. lower population densities. This analysis demonstrates the potential to generate generalizable insight into the magnitude of vehicle emission reductions that might be achieved through expanding HOV lanes, and highlights the importance of data disaggregation in identifying the optimal locations for potential reductions. [ABSTRACT FROM AUTHOR]

Mosquitoes are ecologically and economically important invertebrates that transmit numerous diseases and are an integral part of the food web in many terrestrial and aquatic ecosystems. Despite their importance, there have been no central repositories for occurrence or abundance records of mosquitoes in the United States. To enable research dependent on the geographic distribution and abundance of mosquito species, we built a database of occurrence records collected by many individuals and agencies, primarily in the United States and with emphasis on unpublished data in the Midwest region. This resource is invaluable to researchers studying mosquito ecology, disease vectors and pathways, and insect pests. The database contains 542 144 occurrence records, and each record includes information on sex, life stage, sampling method, presence/absence or abundance, and date and location of sampling. The accessibility of this resource will directly impact management and planning for mosquito-borne diseases with region-specific or species-specific modeling. Because there is little centralized ecological information on mosquitoes, this database is foundational to expanding knowledge of mosquito ecology. [ABSTRACT FROM AUTHOR]