Projected climate change impacts on skiing and snowmobiling: A case study of the United States

We use a physically-based water and energy balance model to simulate natural snow accumulation at 247 winter recreation locations across the continental United States. We combine this model with projections of snowmaking conditions to determine downhill skiing, cross-country skiing, and snowmobiling season lengths under baseline and future climates, using data from five climate models and two emissions scenarios. Projected season lengths are combined with baseline estimates of winter recreation activity, entrance fee information, and potential changes in population to monetize impacts to the selected winter recreation activity categories for the years 2050 and 2090. Our results identify changes in winter recreation season lengths across the United States that vary by location, recreational activity type, and climate scenario. However, virtually all locations are projected to see reductions in winter recreation season lengths, exceeding 50% by 2050 and 80% in 2090 for some downhill skiing locations. We estimate these season length changes could result in millions to tens of millions of foregone recreational visits annually by 2050, with an annual monetized impact of hundreds of millions of dollars. Comparing results from the alternative emissions scenarios shows that limiting global greenhouse gas emissions could both delay and substantially reduce adverse impacts to the winter recreation industry.     

Cultural impacts to tribes from climate change influences on forests

Climate change related impacts, such as increased frequency and intensity of wildfires, higher temperatures, extreme changes to ecosystem processes, forest conversion and habitat degradation are threatening tribal access to valued resources. Climate change is and will affect the quantity and quality of resources tribes depend upon to perpetuate their cultures and livelihoods. Climate impacts on forests are expected to directly affect culturally important fungi, plant and animal species, in turn affecting tribal sovereignty, culture, and economy. This article examines the climate impacts on forests and the resulting effects on tribal cultures and resources. To understand potential adaptive strategies to climate change, the article also explores traditional ecological knowledge and historical tribal adaptive approaches in resource management, and contemporary examples of research and tribal practices related to forestry, invasive species, traditional use of fire and tribal-federal coordination on resource management projects. The article concludes by summarizing tribal adaptive strategies to climate change and considerations for strengthening the federal-tribal relationship to address climate change impacts to forests and tribal valued resources.     

Implications of twenty-first century climate change on Northeastern United States maple syrup production: impacts and adaptations

Previous research on the impacts of maple syrup production in the Northeastern United States has been based on correlative relationships between syrup production and average temperature. Here a simple biologically and physically-based model of sapflow potential is used to assess observed changes in sapflow across the Northeastern US from 1980 to 2006; document the correspondence between these observations and independent downscaled atmosphere ocean general circulation model (AOGCM) simulations of conditions during this period; and quantify changes in sapflow potential through 2100. The sapflow model is able to capture the spatial and temporal (in terms of the start date of sapflow) variations of sapflow that are observed across the Northeast. Likewise the AOGCM simulations reflect the mean number of sapflow days and the timing of sapflow during the 1980–2006 overlap period. Through the twenty-first century, warming winter temperatures will result in a decline in the number of sapflow days if traditional sap collection schedules are maintained. Under the A1fi emissions scenario the number of sapflow days decreases by up to 14 days. However, the changes in climate also translate the optimal timing of sap collection to earlier in the year. Across the region, the time period that maximizes the number of sapflows days becomes as much as 30 days earlier by 2100 under the A1fi emissions scenario. Provided this change is accounted for by modifying the start of the traditional sap collection schedule, there is essentially no net loss of sapflow days across the majority of the region, with a net increase of sapflow days indicated in the extreme north.     

Potential consequences of projected climate change impacts on hydroelectricity generation

There is a growing concern that countries should reduce their dependence on fossil fuels for electricity generation and look to other cleaner technologies. Hydroelectricity is one such option. However, given that hydropower is dependent on rainfall and associated runoff for power generation, it is susceptible to both the positive and negative impacts of climate change, such as increases in temperature and changes in precipitation and runoff. In this paper, impacts on hydropower generation have been organised as either changes in long-term trends or short-term variability and shocks. These impacts could either manifest themselves as direct impacts on hydropower generation potential or as indirect impacts (or ancillary impacts) such as increased competition for water. Citing examples from around the world, this paper investigates the scale of these projected impacts, and the potential cost implication of inaction. It concludes by making recommendations for possible adaptive options to build resilience in response to local impacts.     

The implications of climate policy for the impacts of climate change on global water resources

This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4 °C by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450 ppm CO₂e and leads to a 2 °C increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.     

Potential impacts of afforestation on climate change and extreme events in Nigeria

Afforestation is usually thought as a good approach to mitigate impacts of warming over a region. This study presents an argument that afforestation may have bigger impacts than originally thought by previous studies. The study investigates the impacts of afforestation on future climate and extreme events in Nigeria, using a regional climate model (RegCM3), forced with global climate model simulations. The impacts of seven afforestation options on the near future (2031–2050, under A1B scenario) climate and the extreme events are investigated. RegCM3 replicates essential features in the present-day (1981–2000) climate and the associated extreme events, and adequately simulates the seasonal variations over the ecological zones in the country. However, the model simulates the seasonal climate better over the northern ecological zones than over the southern ecological zones. The simulated spatial distribution of the extreme events agrees well with the observation, though the magnitude of the simulated events is smaller than the observed. The study shows that afforestation in Nigeria could have both positive and negative future impacts on the climate change and extreme events in the country. While afforestation reduces the projected global warming and enhances rainfall over the afforested area (and over coastal zones), it enhances the warming and reduces the rainfall over the north-eastern part of the country. In addition, the afforestation induces more frequent occurrence of extreme rainfall events (flooding) over the coastal region and more frequent occurrence of heat waves and droughts over the semi-arid region. The positive and negative impacts of the afforestation are not limited to Nigeria; they extend to the neighboring countries. While afforestation lowers the warming and enhances rainfall over Benin Republic, it increases the warming and lowers the rainfall over Niger, Chad and Cameroon. The result of the study has important implication for the ongoing climate change mitigation and adaptation efforts in Nigeria.     

Potential impact of future climate change on crop yield in northeastern China

We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China(NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5(CMIP5) under the Representative Concentration Pathway 4.5 scenario(RCP4.5), the projected maize yield changes for three future periods [2010–39(period 1), 2040–69(period 2), and 2070–99(period 3)] relative to the mean yield in the baseline period(1976–2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase(but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers.     

Assessing impacts of climate change on forests: The state of biological modeling

Models that address the impacts of climate change on forests are reviewed at four levels of biological organization: global, regional or landscape, community, and tree. The models are compared for their ability to assess changes in fluxes of biogenic greenhouse gases, land use, patterns of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models have been used to consider more impacts than the other models. The development of landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research needing additional effort are identified: (1) linking socioeconomic and ecologic models; (2) interfacing forest models at different scales; (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes; and (4) relating information from different scales.The U.S. Government right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.Managed by Martin Marietta Energy Systems, Inc., for the U.S. Department of Energy under contract DE-AC05-84OR21400.     

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5?×?0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km² of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km² of cropland, and the change in risk varies between ?9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.     

Standardized estimates of climate change damages for the United States

Nordhaus (1991), Cline (1992), Fankhauser (1992), and Titus (1992) have published comprehensive estimates of annual climate change damages to the United States in about 2060 that vary from $55 billion to $111 billion ($1990). The estimates are comprehensive because they address market and nonmarket impacts. They based their estimates on different assumptions about the rates of climate change and sea level rise, rates of return on investment, and changes in population and income. In addition, many of the damage estimates, although reported for a 2.5–3.0 °C warming, were based on studies that assumed higher rates of warming. Thus, these studies may have overestimated damages associated with a 2.5–3.0 °C warming. In this paper, the results of these studies were standardized for a 2.5 °C warming, a 50-cm sea level rise, 1990 income and population, and a 4% real rate of return on investments. After standardization, the total damage estimates range from $42.3 billion to $52.8 billion, slightly less than 1% of United States GNP in 1990. Yet, within individual sectors, such as agriculture and electricity, standardized damages differ by more than an order of magnitude. In addition, a significant amount of speculation underlies the damage estimates. Thus, the small range of total standardized damages and apparent agreement about the magnitude of such damages should be interpreted with caution.     

Dissecting indices of aridity for assessing the impacts of global climate change

There is great interest in understanding how climate change will impact aridity through the interaction of precipitation changes with rising temperatures. The Aridity Index (AI), Climatic Moisture Deficit (CMD), and Climatic Moisture Surplus (CMS) are metrics commonly used to quantify and map patterns in aridity and water cycling. Here we show that these metrics have different patterns of change under future climate—based on an ensemble of nine general circulation climate models—and the different metrics are appropriate for different purposes. Based on these differences between the metrics, we propose that aridity can be dissected into three different types—hydrological (CMS), agricultural (CMD), and meteorological. In doing this, we propose a novel modified version of the Aridity Index, called AI+, that can be useful for assessing changes in meteorological aridity. The AI?+?is based on the same ratio between precipitation and evapotranspiration as the traditional AI, but unlike the traditional AI, the AI?+?only accounts for changes to precipitation during months when precipitation is less than reference/potential evapotranspiration (i.e. there is a deficit). Moreover, we show that the traditional AI provides a better estimate of change in moisture surplus driven by changes to precipitation during the wet season, rather than changes in deficit that occur during the drier seasons. These results show that it is important to select the most appropriate metric for assessing climate driven changes in aridity.     

Potential impacts of sea-level rise on the Mid- and Upper-Atlantic Region of the United States

We made projections of relative sea-level rise, horizontal inundation, and the associated impacts on people and infrastructure in the coastal portion of the Mid- and Upper-Atlantic Region (MUAR) of the United States. The output of five global climate models (GCMs) run under two greenhouse gas scenarios was used in combination with tide gauge observations to project sea-level increases ranging from 200 to 900 mm by 2100, depending on location, GCM and scenario. The range mainly reflects equal contributions of spatial variability (due to subsidence) and GCM uncertainty, with a smaller fraction of the range due to scenario uncertainty. We evaluated 30-m Digital Elevation Models (DEMs) using 10-m DEMs and LIDAR data at five locations in the MUAR. We found average RMS differences of 0.3 m with the 10-m DEMs and 1.2 m with the LIDAR data, much lower than the reported mean RMS errors of 7 m for the 30-m DEMs. Using the 30-m DEMs, the GCM- and scenario-means of projected sea-level rise, and local subsidence estimates, we estimated a total inundation of 2,600 km² for the MUAR by 2100. Inundation area increases to 3,800 km² at high tide if we incorporate local tidal ranges in the analysis. About 510,000 people and 1,000 km of road lie within this area. Inundation area per length of coastline generally increases to south, where relative sea-level rise is greater and relief is smaller. More economically developed states, such as New York and New Jersey, have the largest number of people and infrastructure exposed to risk of inundation due to sea-level rise.     

Urbanization, climate change and flood policy in the United States

The average annual cost of floods in the United States has been estimated at about $2 billion (current US dollars). The federal government, through the creation of the National Flood Insurance Program (NFIP), has assumed responsibility for mitigating the societal and economic impacts of flooding by establishing a national policy that provides subsidized flood insurance. Increased flood costs during the past two decades have made the NFIP operate at a deficit. This paper argues that our current understanding of climate change and of the sensitivity of the urban environment to floods call for changes to the flood policy scheme. Conclusions are drawn on specific examples from cities along the heavily urbanized corridor of northeastern United States. Mesoscale and global models along with urbanization and economic growth statistics are used to provide insights and recommendations for future flood costs under different emissions scenarios. Mesoscale modeling and future projections from global models suggest, for example, that under a high emissions scenario, New York City could experience almost twice as many days of extreme precipitation that cause flood damage and are disruptive to business as today. The results of the paper suggest that annual flood costs in the United States will increase sharply by the end of the 21st Century, ranging from about $7 to $19 billion current US dollars, depending on the economic growth rate and the emissions scenarios. Hydrologic, hydraulic and other related uncertainties are addressed and a revised version of the NFIP is suggested.     

The impacts of climate change on agricultural production systems in China

Climate change can bring positive and negative effects on Chinese agriculture, but negative impacts tend to dominate. The annual mean surface temperature has risen about 0.5–0.8 °C. The precipitation trends have not been identified during the past 100 years in China, although the frequency and intensity of extreme weather/climate events have increased, especially of drought. Water scarcity, more frequent and serious outbreaks of insects and diseases, and soil degradation caused by climate change have impacted agro-environmental conditions. However, temperature rise prolonged the crop growth seasons and cold damages have reduced in Northeast China. The projection of climate change indicates that the surface temperature will continue to increase with about 3.9 to 6.0 °C and precipitation is expected to increase by 9 to 11 % at the end of 21st century in China. Climate warming will provide more heat and as a consequence, the boundary of the triple-cropping system (TCS) will extend northwards by as much as 200 to 300 km, from the Yangtze River Valley to the Yellow River Basin, and the current double-cropping system (DCS) will move to the central part of China, into the current single cropping system (SCS) area which will decrease in SCS surface area of 23.1 % by 2050. Climate warming will also affect the optimum location for the cultivation of China’s main crop varieties. If no measures are taken to adapt to climate changes, compared with the potential yield in 1961–1990, yields of irrigated wheat, corn and rice are projected to decrease by 2.2–6.7 %, 0.4 %–11.9 % and 4.3–12.4 % respectively in the 2050s. Climate warming will enhance potential evaporation and reduce the availability of soil moisture, thus causing a greater need for agricultural irrigation, intensifying the conflict between water supply and demand, especially in arid and semi-arid areas of China. With adequate irrigation, the extent of the reduction in yield of China’s corn and wheat can be improved by 5 % to 15 %, and rice by 5 % or so than the potential yield in 1961–1990. Adaptive measures can reduce the agricultural loss under climate change. If effective measures are taken in a timely way, then climate change in the next 30–50 years will not have a significant influence on China’s food security.     

An annual cycle of vegetation in a GCM. Part II: global impacts on climate and hydrology

The Met Office Hadley Centre Unified Model (HadAM3) with the tiled version of the Met Office Surface Exchange Scheme (MOSES2) land surface scheme is used to assess the impact of a comprehensive imposed vegetation annual cycle on global climate and hydrology. Two 25-year numerical experiments are completed: the first with structural vegetation characteristics (Leaf Area Index, LAI, canopy height, canopy water capacity, canopy heat capacity, albedo) held at annual mean values, the second with realistic seasonally varying vegetation characteristics. It is found that the seasonalities of latent heat flux and surface temperature are widely affected. The difference in latent heat flux between experiments is proportional to the difference in LAI. Summer growing season surface temperatures are between 1 and 4 K lower in the phenology experiment over a majority of grid points with a significant vegetation annual cycle. During winter, midlatitude surface temperatures are also cooler due to brighter surface albedo over low LAI surfaces whereas during the dry season in the tropics, characterized by dormant vegetation, surface temperatures are slightly warmer due to reduced transpiration. Precipitation is not as systematically affected as surface temperature by a vegetation annual cycle, but enhanced growing season precipitation rates are seen in regions where the latent heat flux (evaporation) difference is large. Differences between experiments in evapotranspiration, soil moisture storage, the timing of soil thaw, and canopy interception generate regional perturbations to surface and sub-surface runoff annual cycles in the model.