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.     

Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part I. The Uncertainty Due to Spatial Scale

We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects ofCO₂ fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 ×CO₂ runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate changescenarios as an important uncertainty for climate change impacts analysis.     

Influence d'un changement climatique dû à une hausse de gaz à effet de serre sur l'agriculture au quebec

Abstract

This study, using a climate change scenario generated by the Canadian Climate Centre (CCC) general circulation model (GCM) examines the impacts of such a climate change on agriculture in southern Quebec. Using a crop model from the Food and Agriculture Organization (FAO), yield responses of a variety of cereals, legumes, oleaginous and special crops to climate change are analysed and discussed.

Results show that under the 2 × CO₂ climate scenario the growing season would be longer and accumulation of corn heat units and growing degree days would be more important than under actual climate (1961–1990). One of the more important results of this study is that, on the one hand yield of C₃ cereals would be lower and that of C₄ cereals higher in most agricultural regions. On the other hand, the direct fertilisation effect of increased CO₂ is not considered. It must be cautioned however that we can not generalise results obtained for one legume crop to all legumes.     

Simulated Climate Change Effects on Year-Round Water Temperatures in Temperate Zone Lakes

A deterministic, one-dimensional model is presented to simulate daily water temperature profiles and associated ice and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface area (A_s), maximum depth (H_MAX), and Secchi depth (z_s), the latter, used as a measure of light attenuation and trophic state. The model is driven by daily weather data and operates year-round over multiple years. The model has been tested with extensive data (over 5,000 temperature points). Standard error between simulated and measured water temperatures is 1.4°C in the open water season and 0.5°C in the ice cover season. The model is applied to simulate the sensitivity of Minnesota lake water temperature characteristics to climate change. The projected climate changes due to a doubling of atmospheric CO₂ are obtained from the output of the Canadian Climate Center General Circulation Model (CCC GCM) and the Goddard Institute of Space Studies General Circulation Model (GISS GCM). Simulated lake temperature characteristics have been plotted in a coordinate system with a lake geometry ratio (A _s ^0.25 /H_MAX) on one axis and Secchi depth on the other. The lake geometry ratio expresses a lake's susceptibility to stratification. By interpolation, the sensitivity of lake temperature characteristics to changes of water depth and Secchi depth under the projected climate scenarios can therefore be obtained. Selected lake temperature characteristics simulated with past climate conditions (1961–1979) and with a projected 2 × CO₂ climate scenario as input are presented herein in graphical form. The simulation results show that under the 2 × CO₂ climate scenario ice formation is delayed and ice cover period is shortened. These changes cause water temperature modifications throughout the year.     

REGIONAL CLIMATE CHANGE SCENARIOS UNDER GLOBAL WARMING IN KAZAKHSTAN

The aim of this paper is to report on the development of regional climate change scenarios for Kazakhstan as the result of increasing of CO₂ concentration in the global atmosphere. These scenarios are used in the assessment of climate change impacts on the agricultural, forest and water resources of Kazakhstan. Climate change scenarios for Kazakhstan to assess both long-term (2× CO₂ in 2075) and short-term (2000, 2010 and 2030) impacts were prepared. The climate conditions under increasing CO₂ concentration were estimated from three General Circulation Models (GCM) outputs: the model of the Canadian Climate Center Model (CCCM), the model of the Geophysical Fluid Dynamics Laboratory (GFDL) and the 1% transient version of the GFDL model (GFDL-T). The near-term climate scenarios were obtained using the probabilistic forecast model (PFM) to the year 2010 and the results of GFDL-T for years 2000 and 2030. A baseline scenario representing the current climate conditions based on observations from 1951 to 1980 was developed. The assessment of climate change in Kazakhstan based on the analysis of 100-years observations is given too. As a result of comparisons of the current climate (based on observed climate) the 1× CO₂ output from GCMs showed that the GFDL model best matches the observed climate. The GFDL model suggests that the minimum increase in temperature is expected in winter, when most of the territory is expected to have temperatures 2.3–4.5 °C higher. The maximum (4.3 to 8.2 °C) is expected to be in spring. CCCM scenario estimates an extreme worming above 11 °C in spring months. GFDL-T outputs provide an intermediate scenario.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO₂ fertilization effect on vegetation is examined by using two levels of atmospheric CO₂ concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO₂ fertilization effects.     

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.     

Spatial Scale Effects of Climate Scenarios on Simulated Cotton Production in the Southeastern U.S.A.

We examine the effect of climate scenarios generated using results from climate models of different spatial resolution on yields simulated by the deterministic cotton model GOSSYM for the southeastern U.S.A. Two related climate change scenarios were used: a coarse-scale scenario produced from results of a general circulation model (GCM) which also provided the boundary conditions to a regional climate model (RCM), from which a fine-scale scenario was constructed. Cotton model simulations were performed for three cases: climate change alone; climate change and elevatedCO₂; climate change, elevated CO₂ and adaptations to climate change. In general, significant differences in state-average projected yield changes between the coarse and fine-scale scenarios are found for these three cases. In the first two cases, different directions of change are found in some sub-regions. With adaptation, yields substantially increase for both climate scenarios, but more so for the coarse-scale scenario (30%domain-average increase). Under irrigation, yield change differences between the two climate scenarios are small in all three cases, and yields are higher under irrigation ( 35% domain-average increase with adaptation case) compared to dryland conditions. For the climate change alone case, differences in summer water-stress levels explain the contrasts in dryland yield patterns between the coarse and fine-scale climate scenarios.     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.     

A Climate Change Scenario for the Tropics

This paper describes the construction of a climate change scenario for a region representing the extended Tropics – 30° N to 30° S – using a methodology that combines results from a simple climate model and a Global Climate Model (GCM) transient climate change experiment. The estimated date by which this climate change scenario might be realized ranges from as early as the end of the 2030s to as late as well into the 22nd century. The central estimate is for this scenario to describe the climate of the 2060s, which would represent a global warming rate of about 0.2 °C per decade, with associated atmospheric CO₂ concentrations estimated to be about 560 ppmv, 55% higher than 1990 levels. The role of anthropogenic aerosols in offsetting part of this future global warming and altering the regional character of the changes has not been considered. The paper presents changes in mean temperature; mean rainfall; rainfall seasonality, variability, frequency, and intensity and soil moisture. These patterns of change derive from only one GCM climate change experiment; different experiments would yield different patterns for the same global warming. There is also some discussion about possible changes in tropical cyclone (TC) activity, although since TCs remain poorly modelled in GCMs, the full range of possibilities (from reduced activity, through no change, to increased activity) should be considered in any impact assessment.     

Climate simulation of the twenty-first century with interactive land-use changes

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean–atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.     

On the response of the oceanic wind-driven circulation to atmospheric CO2 increase

A global, flux-corrected climate model is employed to predict the surface wind stress and associated wind-driven oceanic circulation for climate states corresponding to a doubling and quadrupling of the atmospheric CO₂ concentration in a simple 1% per year CO₂ increase scenario. The model indicates that in response to CO₂ increase, the position of zero wind stress curl in the mid-latitudes of the Southern Hemisphere shifts poleward. In addition, the wind stress intensifies significantly in the mid-latitudes of the Southern Hemisphere. As a result, the rate of water circulation in the subpolar meridional overturning cell in the Southern Ocean increases by about 6 Sv (1 Sv=10⁶ m³ s⁻¹) for doubled CO₂ and by 12 Sv for quadrupled CO₂, implying an increase of deep water upwelling south of the circumpolar flow and an increase of Ekman pumping north of it. In addition, the changes in the wind stress and wind stress curl translate into changes in the horizontal mass transport, leading to a poleward expansion of the subtropical gyres in both hemispheres, and to strengthening of the Antarctic Circumpolar Current. Finally, the intensified near-surface winds over the Southern Ocean result in a substantial increase of mechanical energy supply to the ocean general circulation.     

Response of Soybean and Sorghum to Varying Spatial Scales of Climate Change Scenarios in the Southeastern United States

This study examines how uncertainty associated with the spatial scale of climate change scenarios influences estimates of soybean and sorghum yield response in the southeastern United States. We investigated response using coarse (300-km, CSIRO) and fine (50-km, RCM) scale climate change scenarios and considering climate changes alone, climate changes with CO₂ fertilization, and climate changes with CO₂ fertilization and adaptation. Relative to yields simulatedunder a current, control climate scenario, domain-wide soybean yield decreased by 49% with the coarse-scale climate change scenario alone, and by26% with consideration for CO₂ fertilization. By contrast, thefine-scale climate change scenario generally exhibited higher temperatures and lower precipitation in the summer months resulting in greater yield decreases (69% for climate change alone and 54% with CO₂fertilization). Changing planting date and shifting cultivars mitigated impacts, but yield still decreased by 8% and 18% respectively for the coarse andfine climate change scenarios. The results were similar for sorghum. Yield decreased by 51%, 42%, and 15% in response to fine-scaleclimate change alone, CO₂ fertilization, and adaptation cases, respectively– significantly worse than with the coarse-scale (CSIRO) scenarios. Adaptation strategies tempered the impacts of moisture and temperature stress during pod-fill and grain-fill periods and also differed with respect to the scale of the climate change scenario.     

Use of general circulation model output in the creation of climate change scenarios for impact analysis

Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO₂ and 1 × CO₂ GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO₂ concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.     

Analysis of variability and diurnal range of daily temperature in a nested regional climate model: comparison with observations and doubled CO2 results

Analysis of daily variability of temperature in climate model experiments is important as a model diagnostic and for determination of how such variability may change under perturbed climate conditions. The latter could be important from a climate impacts perspective. We analyze daily mean, diurnal range and variability of surface air temperature in two continuous 3 1/2 year long climate simulations over the continental USA, one for present day conditions and one for conditions under doubled carbon dioxide concentration, conducted with a regional climate model (RegCM), on a 60 km grid, nested in a general circulation model (GCM). Model output is compared with a 30-year daily observational data set for various regions of the USA. In comparison with observations the diurnal range in the model control run is somewhat too low although the daily temperature mean is often well reproduced. The daily variability of temperature is underestimated by the model in all areas, but particularly when and where the observed variability is relatively high. Causes for these underestimations are traced to deficiencies in the general circulation of the driving GCM. With doubled CO₂, both maximum and minimum temperatures increase, but the change in the diurnal temperature range (DTR) varies spatially and seasonally. On an annual average over the land domain, the DTR decreases by 0.25'C. Changes in DTR are most strongly correlated with changes in absorbed shortwave radiation at the surface, which explains 72% of the variance in DTR on an annual basis. Change in evaporation was a factor affecting DTR only in the summer when it explained 52% of the variance. The most significant findings with CO₂ doubling are substantial decreases in daily variability in winter over large portions of the domain, and localized increases in summer. Causes for these changes are traced to fluctuations in the intensity and position of the jet stream.     

Estimating the consequences of CO2-induced climatic change on north american grain agriculture using general circulation model information

A procedure to estimate the potential climatic effects of a doubling of atmospheric carbon dioxide concentration on agricultural production is illustrated. The method combines use of atmospheric general circulation models (GCMs) and process-oriented crop models. Wheat and corn (maize) yields in three important North American grain cropping regions are treated. Combined use of these two types of models can provide insights into the impacts of climate changes at the level of plant physiology, and potential means by which agricultural production practices may adapt to these changes.Specific agronomic predictions are found to depend critically on the details of the projected climate change. Uncertainties in the specification of the doubled-CO₂ climate by the GCM, particularly with respect to precipitation, dictate that agricultural predictions derived from them at this time must be regarded only as illustrative of the impact assessment method.     

Using a GCM analogue model to investigate the potential for Amazonian forest dieback

Summary A combined GCM analogue model and GCM land surface representation is used to investigate the influences of climatology and land surface parameterisation on modelled Amazonian vegetation change. This modelling structure (called IMOGEN) captures the main features of the changes in surface climate as estimated by a GCM with enhanced atmospheric greenhouse gas concentrations. Advantage is taken of IMOGENs computational speed which allows multiple simulations to be carried out to assess the robustness of the GCM results.The timing of forest dieback is found to be sensitive to the initial pre-industrial climate, as well as uncertainties in the representation of land-atmosphere CO₂ exchange. Changing from a Q ₁₀ form for plant dark and maintanence respiration (as used in the coupled GCM runs) to a respiration proportional to maximum photosynthesis, reduces the biomass lost from Amazonia in the 21st century. Replacing the GCM control climate (which has about 25% too little rain in the annual mean over Amazonia) with an observed climatology increases the CO₂ concentration at which rainfall drops to critical levels, and thereby further delays the dieback. On the other hand, calibration of the canopy photosynthesis model against Amazonian flux data tends to lead to earlier forest dieback. Further advances are required in both GCM rainfall simulation and land-surface process representation before a clearer picture will emerge on the timing of possible Amazonian forest dieback. However, it seems likely that these advances will overall lead to projections of later forest dieback as GCM control climates become more realistic.     

Regional Nested Model Simulations of Present Day and 2 × CO2 Climate over the Central Plains of the U.S.

A nested regional climate model is used to generate a scenario of climate change over the MINK region (Missouri, Iowa, Nebraska, Kansas) due to doubling of carbon dioxide concentration (2 × CO₂) for use in agricultural impact assessment studies. Five-year long present day (control) and 2 × CO₂ simulations are completed at a horizontal grid point spacing of 50 km. Monthly and seasonal precipitation and surface air temperature over the MINK region are reproduced well by the model in the control run, except for an underestimation of both variables during the spring months. The performance of the nested model in the control run is greatly improved compared to a similar experiment performed with a previous version of the nested modeling system by Giorgi et al. (1994). The nested model generally improves the simulation of spatial precipitation patterns compared to the driving general circulation model (GCM), especially during the summer. Seasonal surface warming of 4 to 6 K and seasonal precipitation increases of 6 to 24% are simulated in 2 × CO₂ conditions. The control run temperature biases are smaller than the simulated changes in all seasons, while the precipitation biases are of the same order of magnitude as the simulated changes. Although the large scale patterns of change in the driving GCM and nested RegCM model are similar, significant differences between the models, and substantial spatial variability, occur within the MINK region.     

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.     

Predicting the impacts of global warming on wildland fire

Simulations of impacts of a double-CO₂ climate with the Changed Climate Fire Modeling System in Northern California consistently projected increases in area burned and in the frequency of escaped fires compared with simulations of the present climate. However, the magnitude of those increases was strongly influenced by vegetation type, choice of atmospheric general circulation model (GCM) scenario, and choice of climatic forcing variables. The greatest projected increase in fire severity occurred in grasslands, using the Princeton Geophysical Fluid Dynamics Laboratory GCM, with wind speed, temperature, humidity and precipitation as driving variables.