The impact of climate change on continuous corn production in the Southern U.S.A.

The Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) has been used in conjunction with a field level plant process model (CERES-Maize) and a field level pesticide transport model (PRZM) to study the impacts of doubled levels of atmospheric CO₂ on various aspects of corn production in the Southern U.S.A. Grid-box scale GCM output has been applied to a 38-year time series of historical weather data at 28 different locations for several typical soil profiles throughout the South. Limitations on the use of the climate scenario in conjunction with the process models are discussed. Major shortcomings include: 1) no direct impacts of atmospheric CO₂ on plant growth and development in the plant process model; 2) neither macro-pore solute transport nor chemical decay rate response to temperature are included in the pesticide transport model; and 3) the climate change scenario output does not provide information concerning changes in temperature extremes and variability or precipitation frequency, intensity or duration. The latter are particularly critical parameters for the detailed simulation of hydrological processes. In spite of these omissions, the combination of the three models facilitates the study of the impacts of GCM modeled climate change on several inter-related agro-climatic issues of interest to agricultural policy makers. These issues include: changes in dryland and irrigated corn yields; changes in sowing and harvest dates; modification of crop water demand; and estimates of effects on pesticide losses from the soil surface and through leaching from the bottom of the active corn root zone. Model generated results which address these issues are presented but must be used with caution in light of the GCM and process model limitations. The results of this study suggest that substantial changes in agricultural production and management practices may be needed to respond to the climate changes expected to take place throughout the Southern U.S.A.     

Environmental change in grasslands: Assessment using models

Modeling studies and observed data suggest that plant production, species distribution, disturbance regimes, grassland biome boundaries and secondary production (i.e., animal productivity) could be affected by potential changes in climate and by changes in land use practices. There are many studies in which computer models have been used to assess the impact of climate changes on grassland ecosystems. A global assessment of climate change impacts suggest that some grassland ecosystems will have higher plant production (humid temperate grasslands) while the production of extreme continental steppes (e.g., more arid regions of the temperate grasslands of North America and Eurasia) could be reduced substantially. All of the grassland systems studied are projected to lose soil carbon, with the greatest losses in the extreme continental grassland systems. There are large differences in the projected changes in plant production for some regions, while alterations in soil C are relatively similar over a range of climate change projections drawn from various General Circulation Models (GCM's). The potential impact of climatic change on cattle weight gains is unclear. The results of modeling studies also suggest that the direct impact of increased atmospheric CO₂ on photosynthesis and water use in grasslands must be considered since these direct impacts could be as large as those due to climatic changes. In addition to its direct effects on photosynthesis and water use, elevated CO₂ concentrations lower N content and reduce digestibility of the forage.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

Here we simulate dryland agriculture in the United States in order to assess potential future agricultural production under a set of general circulation model (GCM)-based climate change scenarios. The total national production of three major grain crops—corn, soybeans, and winter wheat—and two forage crops—alfalfa and clover hay—is calculated for the actual present day core production area (CPA) of each of these crops. In general, higher global mean temperature (GMT) reduces production and higher atmospheric carbon dioxide concentration ([CO₂]) increases production. Depending on the climatic change scenarios employed overall national production of the crops studied changes by up to plus or minus 25% from present-day levels. Impacts are more significant regionally, with crop production varying by greater than ±50% from baseline levels. Analysis of currently possible production areas (CPPAs) for each crop indicates that the regions most likely to be affected by climate change are those on the margins of the areas in which they are currently grown. Crop yield variability was found to be primarily influenced by local weather and geographic features rather than by large-scale changes in climate patterns and atmospheric composition. Future US agronomic potential will be significantly affected by the changes in climate projected here. The nature of the crop response will depend primarily on to what extent precipitation patterns change and also on the degree of warming experienced.     

Future cereal production in China: The interaction of climate change,water availability and socio-economic scenarios

Food production in China is a fundamental component of the national economy and driver of agricultural policy. Sustaining and increasing output to meet growing demand faces significant challenges including climate change, increasing population, agricultural land loss and competing demands for water. Recent warming in China is projected to accelerate by climate models with associated changes in precipitation and frequency of extreme events. How changes in cereal production and water availability due to climate change will interact with other socio-economic pressures is poorly understood. By linking crop and water simulation models and two scenarios of climate (derived from the Regional Climate Model PRECIS) and socio-economic change (downscaled from IPCC SRES A2 and B2) we demonstrate that by the 2040s the absolute effects of climate change are relatively modest. The interactive effects of other drivers are negative, leading to decreases in total production of ?18% (A2) and ?9% (B2). Outcomes are highly dependent on climate scenario, socio-economic development pathway and the effects of CO₂ fertilization on crop yields which may almost totally offset the decreases in production. We find that water availability plays a significant limiting role on future cereal production, due to the combined effects of higher crop water requirements (due to climate change) and increasing demand for non-agricultural use of water (due to socio-economic development). Without adaptation, per capita cereal production falls in all cases, by up to 40% of the current baseline.By simulating the effects of three adaptation scenarios we show that for these future scenarios China is able to maintain per capita cereal production, given reasonable assumptions about policies on land and water management and progress in agricultural technology. Our results are optimistic because PRECIS simulates much wetter conditions than a multi-model average, the CO₂ crop yield response function is highly uncertain and the effects of extreme events on crop growth and water availability are likely to be underestimated.     

Potential Soil C Sequestration on U.S. Agricultural Soils

Soil carbon sequestration has been suggested as a means to help mitigate atmospheric CO₂ increases, however there is limited knowledge aboutthe magnitude of the mitigation potential. Field studies across the U.S. provide information on soil C stock changes that result from changes in agricultural management. However, data from such studies are not readily extrapolated to changes at a national scale because soils, climate, and management regimes vary locally and regionally. We used a modified version of the Intergovernmental Panel on Climate Change (IPCC) soil organic C inventory method, together with the National Resources Inventory (NRI) and other data, to estimate agricultural soil C sequestration potential in the conterminous U.S. The IPCC method estimates soil C stock changes associated with changes in land use and/or land management practices. In the U.S., the NRI provides a detailed record of land use and management activities on agricultural land that can be used to implement the IPCC method. We analyzed potential soil C storage from increased adoption of no-till, decreased fallow operations, conversion of highly erodible land to grassland, and increased use of cover crops in annual cropping systems. The results represent potentials that do not explicitly consider the economic feasibility of proposed agricultural production changes, but provide an indication of the biophysical potential of soil C sequestration as a guide to policy makers. Our analysis suggests that U.S. cropland soils have the potential to increase sequestered soil C by an additional 60–70 Tg (10¹²g) C yr^{– 1}, over present rates of 17 Tg C yr^–1(estimated using the IPCC method), with widespread adoption of soil C sequestering management practices. Adoption of no-till on all currently annually cropped area (129Mha) would increase soil C sequestration by 47 Tg C yr^–1. Alternatively, use of no-till on 50% of annual cropland, with reduced tillage practices on the other 50%, would sequester less – about37 Tg C yr^–1. Elimination of summer fallow practices and conversionof highly erodible cropland to perennial grass cover could sequester around 20 and 28Tg C yr^–1, respectively. The soil C sequestration potentialfrom including a winter cover crop on annual cropping systems was estimated at 40Tg C yr^–1. All rates were estimated for a fifteen-yearprojection period, and annual rates of soil C accumulations would be expected to decrease substantially over longer time periods. The total sequestration potential we have estimated for the projection period (83 Tg C yr^–1) represents about 5% of 1999total U.S. CO₂ emissions or nearly double estimated CO₂ emissionsfrom agricultural production (43 Tg C yr^–1). For purposes ofstabilizing or reducing CO₂ emissions, e.g., by 7% of 1990 levels asoriginally called for in the Kyoto Protocol, total potential soil C sequestration would represent 15% of that reduction level from projected 2008 emissions(2008 total greenhouse gas emissions less 93% of 1990 greenhouse gasemissions). Thus, our analysis suggests that agricultural soil C sequestration could play a meaningful, but not predominant, role in helping mitigate greenhouse gas increases.     

A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.     

The Potential Response of Terrestrial Carbon Storage to Changes in Climate and Atmospheric CO2

We use a georeferenced model of ecosystem carbon dynamics to explore the sensitivity of global terrestrial carbon storage to changes in atmospheric CO₂ and climate. We model changes in ecosystem carbon density, but we do not model shifts in vegetation type. A model of annual NPP is coupled with a model of carbon allocation in vegetation and a model of decomposition and soil carbon dynamics. NPP is a function of climate and atmospheric CO₂ concentration. The CO₂ response is derived from a biochemical model of photosynthesis. With no change in climate, a doubling of atmospheric CO₂ from 280 ppm to 560 ppm enhances equilibrium global NPP by 16.9%; equilibrium global terrestrial ecosystem carbon (TEC) increases by 14.9%. Simulations with no change in atmospheric CO₂ concentration but changes in climate from five atmospheric general circulation models yield increases in global NPP of 10.0–14.8%. The changes in NPP are very nearly balanced by changes in decomposition, and the resulting changes in TEC range from an increase of 1.1% to a decrease of 1.1%. These results are similar to those from analyses using bioclimatic biome models that simulate shifts in ecosystem distribution but do not model changes in carbon density within vegetation types. With changes in both climate and a doubling of atmospheric CO₂, our model generates increases in NPP of 30.2–36.5%. The increases in NPP and litter inputs to the soil more than compensate for any climate stimulation of decomposition and lead to increases in global TEC of 15.4–18.2%.     

Agricultural Impact Assessment, Vulnerability, and the Scope for Adaptation

Climate change assessments which have considered climate impacts of a 2xCO₂ climate, using models of the global agricultural system, have found small impacts on overall production, but larger regional changes. Production shifts among regions can be considered one mechanism for adaptation. Adaptation at the farm level, through changes in crops, cultivars, and production practices, is another adaptation mechanism. Existing studies differ in how important these mechanisms will be. Studies that have considered yield effects at specific sites have found very wide ranges of impacts. A useful way to evaluate the impacts of climate change, given the uncertainty about future impacts, is to consider vulnerability. Studies have defined vulnerability in terms of yield, farm profitability, regional economy, and hunger. Vulnerability and climate impacts, particularly in terms of higher order effects on profitability and sustainability, will depend on how society and the economy develop. Lower income populations and marginal agricultural regions, particularly arid or flood prone areas, are most vulnerable to climate change.     

COMPARISON OF GLOBAL CLIMATE CHANGE SIMULATIONS FOR 2 × CO2-INDUCED WARMING

In this article we compile 108 national and international studies on global climate change, each projecting a quantitative impact on global surface-air temperature due to a doubling of the atmospheric CO₂ concentration. These predictions, documented between 1980 and 1995, are based primarily on climate-modeling research, including radiative-convective, energy-balance, and general circulation models. Collectively over the past 15 years, the average (mean) temperature change projection due to doubled CO₂ is +2.62°C, with a range of 0.16–8.7°C. General circulation models tend to estimate slightly higher values (2.98°C), compared with radiative-convective models (1.98°C) and energy-balance models (2.54°C). During the years 1980 through 1995, an increasing trend in predictions is noticed, although the mean temperature change prediction each year has remained fairly consistent near 2–3°C. These findings suggest that the estimated sensitivity of the climate system continues to remain comparable to the range calculated in earlier studies. However, tremendous advancements in the capacity of climate models continue to reveal important uncertainties in the dynamic nature of global atmospheric interactions. The predictions continue to validate the need for a global policy relating to human influence on global climate change.     

Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part II. Accounting for Adaptation and CO2 Direct Effects

We assert that the simulation of fine-scale crop growth processes and agronomic adaptive management using coarse-scale climate change scenarios lower confidence in regional estimates of agronomic adaptive potential. Specifically, we ask: 1) are simulated yield responses tolow-resolution climate change, after adaptation (without and with increased atmospheric CO₂), significantly different from simulated yield responses tohigh-resolution climate change, after adaptation (without and with increased atmospheric CO₂)? and 2) does the scale of the soils information, in addition to the scale of the climate change information, affect yields after adaptation? Equilibrium (1 × CO₂ versus 2 × CO₂)climate changes are simulated at two different spatial resolutions in the Great Plains using the CSIRO general circulation model (low resolution) and the National Center for Atmospheric Research (NCAR) RegCM2 regional climate model (high resolution). The EPIC crop model is used to simulate the effects of these climate changes; adaptations in EPIC include earlier planting and switch to longer-season cultivars. Adapted yields (without and with additional carbon dioxide) are compared at the different spatial resolutions. Our findings with respect to question 1 suggest adaptation is more effective in most cases when simulated with a higher resolution climate change than its more generalized low resolution equivalent. We are not persuaded that the use of high resolution climate change information provides insights into the direct effects of higher atmospheric CO₂ levels on crops beyond what can be obtained with low resolution information. However, this last finding may be partly an artifact of the agriculturally benign CSIRO and RegCM2 climate changes. With respect to question 2, we found that high resolution details of soil characteristics are particularly important to include in adaptation simulations in regions typified by soils with poor water holding capacity.     

Evaluation of the impact of climate changes on water storage and groundwater recharge at the watershed scale

 The increase of concentration of carbon dioxide and other greenhouse gases in the atmosphere will certainly affect hydrological regimes. Global warning is thus expected to have major implications on water resources management. Our objective is to present a general approach to evaluate the effect of potential climate changes on groundwater resources. In the current stage of knowledge, large-scale global climate models are probably the best available tools to provide estimates of the effects of raising greenhouse gases on rainfall and evaporation patterns through a continuous, three dimensional simulation of atmospheric, oceanic and cryospheric processes. However their spatial resolution (generally some thousands of square kilometers) is not compatible with that of watershed hydrologic models. The main purpose of this study is to evaluate the impact of potential climate changes upon groundwater resources. A general methodology is proposed in order to disaggregate outputs of large-scale models and thus to make information directly usable by hydrologic models. As an illustration, this method is applied to a CO₂-doubling scenario through the development of a local weather generator, although many uncertainties are not yet assessed about the results of climate models. Two important hydrological variables: rainfall and potential evapotranspiration are thus generated. They are then used by coupling with a physically based hydrological model to estimate the effects of climate changes on groundwater recharge and soil moisture in the root zone. Received: 17 April 1998 / Accepted: 29 September 1998     

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.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

During this century global warming will lead to changes in global weather and climate, affecting many aspects of our environment. Agriculture is the sector of the United States economy most likely to be directly impacted by climatic changes. We have examined potential changes in dryland agriculture (Part 3) and in water resources necessary for crop production (Part 4) in response to a set of climate change scenarios. In this paper we assess to what extent, under these same scenarios, water supplies will be sufficient to meet the irrigation requirement of major grain crops in the US. In addition, we assess the overall impacts of changes in water supply on national grain production. We apply the 12 climate change scenarios described in Part 1 to the water resources and crop growth simulation models described in Part 2 for the conterminous United States. Drawing on data from Parts 3 and 4 we calculate what the aggregate national production would be in those regions in which grain crops are currently produced by applying irrigation where needed and water supplies allow. The total amount of irrigation water applied to crops declines under all climate change scenarios employed in this study. Under certain of the scenarios and in particular regions, precipitation decreases so much that water supplies are too limited; in other regions precipitation becomes so plentiful that little value is derived from irrigation. Nationwide grain crop production is greater when irrigation is applied as needed. Under irrigation, less corn and soybeans are produced under most of the climate change scenarios than is produced under baseline climate conditions. Winter wheat production under irrigation responds significantly to elevated atmospheric carbon dioxide concentrations [CO₂] and appears likely to increase under climate change.     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

Modeling the eco-hydrologic response of a Mediterranean type ecosystem to the combined impacts of projected climate change and altered fire frequencies

Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO₂ for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs.     

Impacts of a Ghg-Induced Climate Change on Crop Yields: Effects of Acceleration in Maturation, Moisture Stress and Optimal Temperature

The present study involves using the Canadian Climate Centre (CCC) climate change scenario to evaluate the impacts of a CO₂-induced climate change on agriculture in Québec and vicinity. Climate change using the CCC General Circulation Model (GCM) data are fed into a crop model (FAO) so as to gauge the changes in agroclimatic factors such as growing season length and growing degree days, and subsequently potential yield changes for a variety of cereal (C₃ and C₄), leguminous, oleaginous, vegetable and special crops, for twelve major agricultural regions in southern Québec. Our results show that depending upon the agricultural zone and crop type, yields may increase (ex. corn and sorghum by 20%) or decrease (ex. wheat and soybean by 20 to 30%). Also, these crop yield changes appear to be related to acceleration in maturation rates, mainly to change in moisture stress and to shifts in optimal thermal growth conditions. These possible shifts in agricultural production potentials would solicit the formulation of appropriate adaptation strategies.     

Climate Change, Agriculture, and Water Quality in the Chesapeake Bay Region

Research on climate change and agriculture has largely focused on production, food prices, and producer incomes. However, societal interest in agriculture is much broader than these issues. The objective of this paper is to analyze the potential impacts of climate change on an important negative externality from agriculture, water quality. We construct a simulation model of maize production in twelve watersheds within the U.S. Chesapeake Bay Region that has economic and watershed components linking climate to productivity, production decisions by maize farmers, and nitrogen loadings delivered to the Chesapeake Bay. Maize is an important crop to study because of its importance to the region's agriculture and because it is a major source of nutrient pollution. The model is run under alternative scenarios regarding the future climate, future baseline (without any climate change), whether farmers respond to climate change, whether there are carbon dioxide (CO₂) enrichment effects on maize production, and whether agricultural prices facing the region change due to climate change impacts on global agricultural commodity markets. The simulation results differ from one scenario to another on the magnitude and direction of change in nitrogen deliveries to the Chesapeake Bay. The results are highly sensitive to the choice of future baseline scenario and to whether there are CO₂ enrichment effects. The results are also highly sensitive to assumptions about the impact of climate change on commodity prices facing farmers in the Chesapeake Bay region. The results indicate that economic responses by farmers to climate change definitely matter. Assuming that farmers do not respond to changes in temperature, precipitation, and atmosphericCO₂ levels could lead to mistaken conclusions about the magnitude and direction of environmental impacts.     

The role of closed ecological systems in carbon cycle modelling

Acquiring a mechanistic understanding of the role of biotic feedbacks for the links between atmospheric CO₂ concentrations and temperature is essential for trustworthy climate predictions. Currently, computer-based simulations are the only available tool to estimate the global impact of biotic feedbacks on future atmospheric CO₂ and temperatures. Here we propose an alternative and complementary approach by using materially closed, energetically open analogue/physical models of the carbon cycle. We argue that there is unexplored potential in using a materially closed approach to improve our understanding of the magnitude and direction of many biotic carbon feedbacks and that recent technological advances make this feasible. We also suggest how such systems could be designed and discuss the advantages and limitations of establishing physical models of the global carbon cycle.     

Food consumption,diet shifts and associated non-CO2 greenhouse gases from agricultural production

Today, the agricultural sector accounts for approximately 15% of total global anthropogenic emissions, mainly methane and nitrous oxide. Projecting the future development of agricultural non-CO₂ greenhouse gas (GHG) emissions is important to assess their impacts on the climate system but poses many problems as future demand of agricultural products is highly uncertain. We developed a global land use model (MAgPIE) that is suited to assess future anthropogenic agricultural non-CO₂ GHG emissions from various agricultural activities by combining socio-economic information on population, income, food demand, and production costs with spatially explicit environmental data on potential crop yields. In this article we describe how agricultural non-CO₂ GHG emissions are implemented within MAgPIE and compare our simulation results with other studies. Furthermore, we apply the model up to 2055 to assess the impact of future changes in food consumption and diet shifts, but also of technological mitigation options on agricultural non-CO₂ GHG emissions. As a result, we found that global agricultural non-CO₂ emissions increase significantly until 2055 if food energy consumption and diet preferences remain constant at the level of 1995. Non-CO₂ GHG emissions will rise even more if increasing food energy consumption and changing dietary preferences towards higher value foods, like meat and milk, with increasing income are taken into account. In contrast, under a scenario of reduced meat consumption, non-CO₂ GHG emissions would decrease even compared to 1995. Technological mitigation options in the agricultural sector have also the capability of decreasing non-CO₂ GHG emissions significantly. However, these technological mitigation options are not as effective as changes in food consumption. Highest reduction potentials will be achieved by a combination of both approaches.     

Radiation indices of climate-forming factors and their estimates under anthropogenic climate changes

Predictions of expected climate changes are mainly based on the use of large climate models. In the results of these models, it is difficult sometimes to single out the effects and role of separate climate-forming factors. The estimates of such effects are needed for the activities on the mitigation of negative consequences of climate changes on various temporal and spatial scales. Therefore, the methods of computation and comparison of climate-forming factor indices such as the radiative forcing, global warming potential, climate forcing efficiency, et al. are of special importance. Presented is a brief review of indices of principal anthropogenic factors influencing the atmospheric radiation regime on global and local scales such as greenhouse gases, atmospheric aerosols, and radiative properties of the Earth??s surface. The rates of changes in these indices are assessed, as well as their contribution to the variations of climatic characteristics. The examples of these rates are given.