The potential effects of climate change on ecosystem processes and cattle production on U.S. rangelands

In spite of the uncertainties of potential climate change, a scientific consensus is emerging that increasing concentrations of atmospheric CO₂ could alter global temperatures and precipitation patterns. Changes in global climate as predicted by General Circulation Models (GCM) could therefore, have profound implications for global agriculture. The objective of this study was to assess the impacts of potential climate change on livestock and grassland production in the major producing regions of the United States. Simulation sites were selected for the study on the basis of the region's economic dependence on rangeland livestock production. Five thirty-year simulations were conducted on each site using the Simulation of Production and Utilization of Rangelands model and Colorado Beef Cattle Production Model. Climate change files were obtained by combining historic weather data from each site with predicted output from three GCM's. Results from nominal runs were compared with the three climate change scenarios and a doubled CO₂ run. The magnitude and direction of ecosystem response to climate change varied among the GCM's and by geographic region. Simulations demonstrated that changes in temperature and precipitation patterns caused an increase in above-ground net primary production for most sites. Increased decomposition rates were recorded for northern regions. Similarly, animal production in northern regions increased, implying an increase in economic survivability. However, because decreases in animal production indicators were recorded for the southern regions, economic survivability in southern regions is less certain.     

Projected global climate change impact on water temperatures in five north central U.S. streams

The effect of projected global climate change due to a doubling of atmospheric CO₂ on water temperatures in five streams in Minnesota was estimated using a deterministic heat transport model. The model calculates heat exchange between the atmosphere and the water and is driven by climate parameters and stream hydrologic parameters. The model is most sensitive to air temperature and solar radiation. The model was calibrated against detailed measurements to account for seasonally variable shading and wind sheltering. Using climate projections from the GISS, GFDL and OSU GCMs as input; stream temperature simulations predict a warming of freely flowing river reaches by 2.4 °C to 4.7 °C when atmospheric CO₂ doubles. In small shaded streams water temperatures are predicted to rise by an additional 6 °C in summer if trees along stream banks should be lost due to climate change or other human activities (e.g. logging). These projected water temperature changes have significant consequences for survival and growth of fishes. Simulation with the complete heat budget equations were also used to examine simplified water temperature/air temperature correlations.     

A reassessment of the economic effects of global climate change on U.S. agriculture

This study uses recent GCM forecasts, improved plant science and water supply data and refined economic modeling capabilities to reassess the economic consequences of long-term climate change on U.S. agriculture. Changes in crop yields, crop water demand and irrigation water arising from climate change result in changes in economic welfare. Economic consequences of the three GCM scenarios are mixed; GISS and GFDL-QFlux result in aggregate economic gains, UKMO implies losses. As in previous studies, the yield enhancing effects of atmospheric CO₂ are an important determinant of potential economic consequences. Inclusion of changes in world food production and associated export changes generally have a positive affect on U.S. agriculture. As with previous studies, the magnitude of economic effects estimated here are a small percentage of U.S. agricultural value.     

The influence of national temperature fluctuations on opinions about climate change in the U.S. since 1990

Public opinion in the United States about human-caused climate change has varied over the past 20 years, despite an increasing consensus about the issue in the expert community. Attitudes about climate change have been attributed to a number of factors including personal values, political ideology, the media environment and personal experience. Recent studies have found evidence that the temperature can influence one’s opinion about climate change and willingness to change behaviour and/or support climate policy. Although there is some evidence that individual cool or warm years have influenced large-scale opinion about climate change, the extent to which temperature can explain the past variability in public opinion and public discourse about climate change at the national level is not known. Here we isolate the relationship between opinion about climate change and temperature at the national scale, using data from opinion polls, a discourse analysis of opinion articles from five major daily newspapers, and a national air temperature database. The fraction of respondents to national polls who express “belief in” or “worry about” climate change is found to be significantly correlated to U.S. mean temperature anomalies over the previous 3–12 months. In addition, the fraction of editorial and opinion articles which “agree” with the expert consensus on climate change is also found to be significantly correlated to U.S. mean temperature anomalies at seasonal and annual scales. These results suggest that a fraction of the past variance in American views about climate change could potentially be explained by climate variability.     

Understanding U.S. public support for domestic climate change policies

In the U.S., public support for federal, state and local efforts to reduce greenhouse gases (GHGs) continues to be a crucial element of the political viability of these proposals. We present a detailed analysis of the reasons given by the general public of Michigan and Virginia for supporting or rejecting a number of policies that could be implemented to meet GHG reductions. The data allow us to analyze the relationships between reasons provided by respondents, social psychological and demographic characteristics, and policy support. This analysis can provide policymakers pragmatic guidance in (1) developing tactics to engage the public that build on current concerns about climate change policies and (2) crafting and communicating policies that garner support from various segments of the public. This analysis also raises theoretical questions regarding the relationship between public discourse on environmental issues and the formation of public policy support. We suggest that future efforts to understand the U.S. dynamics of public support for climate change policies could benefit from understanding the public discursive and the reasoning processes that underlie public opinion formation.     

Assessment of climate change adaptation costs for the U.S. road network

The U.S. road network is one of the nation's most important capital assets and is vital to the functioning of the U.S. economy. Maintaining this asset involves approximately $134 billion of government funds annually from Federal, State, and local agencies. Climate change may represent a risk or an opportunity to this network, as changes in climate stress will affect the resources necessary for both road maintenance and construction projects. This paper develops an approach for estimating climate-related changes in road maintenance and construction costs such that the current level of service provided by roads is maintained over time. We estimate these costs under a baseline scenario in which annual mean global temperature increases by 1.5 °C in 2050 relative to the historical average and a mitigation scenario under which this increase in mean temperature is limited to 1.0 °C. Depending on the nature of the changes in climate that occur in a given area, our analysis suggests that climate change may lead to a reduction in road maintenance and/or construction costs or an increase in costs. Overall, however, our analysis shows that climate change, if unchecked, will increase the annual costs of keeping paved and unpaved roads in service by $785 million in present value terms by 2050. When not discounted, this figure increases to $2.8 billion. Policies to reduce greenhouse gas emissions are estimated to reduce these costs by approximately $280 million in present value terms and by $885 million when not discounted. These costs vary substantially by region and time period, information that should be important for transportation planners at the national, state, and local levels.     

The effect of global climate change, population distribution, and climate mitigation on building energy use in the U.S. and China

Climate change will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate change on heating and cooling demands requires taking into account not only the manner in which the building sector might evolve over time, but also important uncertainty about the nature of climate change itself. In this study, we explore the uncertainty in climate change impacts on heating and cooling requirement by constructing estimates of heating and cooling degree days (HDD/CDDs) for both reference (no-policy) and 550 ppmv CO₂ concentration pathways built from three different Global Climate Models (GCMs) output and three scenarios of gridded population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China are then explored by using the results of HDD/CDDs as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). The results across the modeled changes in climate and population distributions indicate that unabated climate change would cause building sector’s final energy consumption to decrease modestly (6 % decrease or less depending on climate models) in both the U.S. and China by the end of the century as decreased heating consumption more than offsets increased cooling using primarily electricity. However, global climate change virtually has negligible effect on total CO₂ emissions in the buildings sector in both countries. The results also indicate more substantial implications for the fuel mix with increases in electricity and decreases in other fuels, which may be consistent with climate mitigation goals. The variation in results across all scenarios due to variation of population distribution is smaller than variation due to the use of different climate models.     

Multi-factor impact analysis of agricultural production in Bangladesh with climate change

Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040–2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21 Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins’ hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.     

The impact of climate change on the river rhine: A scenario study

This paper concerns the impact of human-induced global climate change on the River Rhine discharge. For this purpose a model for climate assessment, named ESCAPE, is coupled to a water balance model, named RHINEFLOW. From climate scenarios, changes in regional annual water availability and seasonal discharge in the River Rhine Basin are estimated. The climate scenarios are based on greenhouse gases emissions scenarios. An assessment is made for best guess seasonal discharge changes and for changes in frequencies of low and high discharges in the downstream reaches of the river. In addition, a quantitative estimation of the uncertainties associated with this guess is arrived at.The results show that the extent and range of uncertainty is large with respect to the best guess changes. The uncertainty range is 2–3 times larger for the Business-as-Usual than for the Accelerated Policies scenarios. This large range stems from the doubtful precipitation simulations from the present General Circulation Models. This scenario study showed the precipitation scenarios to be the key-elements within the present range of reliable climate change scenarios.For the River Rhine best guess changes for annual water availability are small according to both scenarios. The river changes from a present combined snow-melt-rain fed river to an almost entirely rain fed river. The difference between present-day large average discharge in winter and the small average discharge in autumn should increase for all scenarios. This trend is largest in the Alpine part of the basin. Here, winter discharges should increase even for scenarios forecasting annual precipitation decreases. Summer discharge should decrease. Best guess scenarios should lead to increased frequencies of both low and high flow events in the downstream (Dutch) part of the river. The results indicate changes could be larger than presently assumed in worst case scenarios used by the Dutch water management authorities.     

Institutionalizing delay: foundation funding and the creation of U.S. climate change counter-movement organizations

This paper conducts an analysis of the financial resource mobilization of the organizations that make up the climate change counter-movement (CCCM) in the United States. Utilizing IRS data, total annual income is compiled for a sample of CCCM organizations (including advocacy organizations, think tanks, and trade associations). These data are coupled with IRS data on philanthropic foundation funding of these CCCM organizations contained in the Foundation Center’s data base. This results in a data sample that contains financial information for the time period 2003 to 2010 on the annual income of 91 CCCM organizations funded by 140 different foundations. An examination of these data shows that these 91 CCCM organizations have an annual income of just over $900 million, with an annual average of $64 million in identifiable foundation support. The overwhelming majority of the philanthropic support comes from conservative foundations. Additionally, there is evidence of a trend toward concealing the sources of CCCM funding through the use of donor directed philanthropies.     

The near-term risk of climate uncertainty among the U.S. states

This article describes a study employing a risk-assessment methodology for evaluating uncertain future climatic conditions. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, the study estimated the impacts from responses to climate change on U.S. state- and national-level economic activity. The study used results of the climate-model CMIP3 dataset developed for the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report to 1) estimate a proxy for representing climate uncertainty over the next 40 years, 2) map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and 3) perform a detailed, economy-wide, 70-industry analysis of economic impacts among the interdependent lower-48 states for the years 2010 through 2050. The analysis determined the interacting industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. When compared to a baseline economic forecast, the calculations produced an average risk of damage of $1 trillion to the U.S. economy from climate change over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Added uncertainty would increase the estimated risk.     

Examining the impact of multiple climate forcings on simulated Southern Hemisphere climate variability

Climate Dynamics - The study examines the influence of external climate forcings, and atmosphere–ocean–sea–ice coupled interaction on the Southern Hemisphere (SH) atmospheric...     

A weather-resolving index for assessing the impact of climate change on tourism related climate resources

This study develops and tests a Modified Climate Index for Tourism (MCIT) utilizing more than 50 years of hourly temperature, wind and significant weather data from contrasting climatic regions, Florida and Alaska. The index measures climate as a tourism resource by combining several tourism-related climate elements. It improves previous methods by incorporating variables that are more relevant to tourism activities, by addressing the overriding nature of some conditions, and by incorporating hourly observations rather than simple daily averages. The MCIT was tested using hourly weather observations from King Salmon, Alaska and Orlando, Florida. The results show that average temperature alone is not sufficient to represent tourism climate resources. For example, at both the Florida and Alaskan sites, showers and thunderstorms are more limiting factors than temperature during much of the year. When applied to past climate data, the proposed MCIT generates meaningful results that capture tourism-related climate variations and trends, including (a) the increasingly favorable tourism conditions in Alaska due to a lengthening of the warm season and (b) a decrease of ideal climatic conditions in central Florida due to the increased summer temperatures. Thus, the index has the potential to become a useful quantitative tool to be used in conjunction with climate models to predict the nature and magnitude of the impact of anticipated climate changes on tourism.     

A Ricardian analysis of the impact of climate change on agriculture in Germany

Based on a Ricardian analysis accounting for spatial autocorrelation and relying on recent climate change forecasts at a low spatial scale, this study assesses the impact of climate change on German agriculture. Given the limited availability of data (e.g., the unknown average soil quality at the district level), a spatial error model is used in order to obtain unbiased marginal effects. The Ricardian analysis is performed using data from the 1999 agricultural census along with data from the network of German weather observation stations. The cross-sectional analysis yields an increase of land rent along with both a rising mean temperature and a declining spring precipitation, except for in the Eastern part of the country. The subsequent simulation of local land rent changes under three different IPCC scenarios is done by entering into the estimated regression equations spatially processed data averages for the period between 2011 and 2040 from the regional climate model REMO. The resulting expected benefits arising from climate change are represented in maps containing the 439 German districts; the calculated overall rent increase corresponds to approximately 5–6% of net German agricultural income. However, in the long run, when temperature and precipitation changes will be more severe than those simulated for 2011–2040, income losses for German agriculture cannot be excluded.     

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.     

A co-evolutionary approach to climate change impact assessment: Part I. Integrating socio-economic and climate change scenarios

Climate change policies currently pay disproportionately greater attention to the mitigation of climate change through emission reductions strategies than to adaptation measures. Realising that the world is already committed to some global warming, policy makers are beginning to turn their attention to the challenge of preparing society to adapt to the unfolding impacts at the local level. This two-part article presents an integrated, or `co-evolutionary', approach to using scenarios in adaptation and vulnerability assessment. Part I explains how climate and social scenarios can be integrated to better understand the inter-relationships between a changing climate and the dynamic evolution of social, economic and political systems. The integrated scenarios are then calibrated so that they can be applied `bottom up’ to local stakeholders in vulnerable sectors of the economy. Part I concludes that a co-evolutionary approach (1) produces a more sophisticated and dynamic account of the potential feedbacks between natural and human systems; (2) suggests that sustainability indicators are both a potentially valuable input to and an output of integrated scenario formulation and application. Part II describes how a broadly representative sample of public, private and voluntary organisations in the East Anglian region of the UK responded to the scenarios, and identifies future research priorities.     

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.