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 change mitigation scenarios and policies and measures: the case of Kazakhstan

This article illustrates the main difficulties encountered in the preparation of GHG emission projections and climate change mitigation policies and measures (P&M) for Kazakhstan. Difficulties in representing the system with an economic model have been overcome by representing the energy system with a technical-economic growth model (MARKAL-TIMES) based on the stock of existing plants, transformation processes, and end-use devices. GHG emission scenarios depend mainly on the pace of transition in Kazakhstan from a planned economy to a market economy. Three scenarios are portrayed: an incomplete transition, a fast and successful one, and even more advanced participation in global climate change mitigation, including participation in some emission trading schemes. If the transition to a market economy is completed by 2020, P&M already adopted may reduce emissions of CO₂ from combustion by about 85 MtCO₂ by 2030 – 17% of the emissions in the baseline (WOM) scenario. One-third of these reductions are likely to be obtained from the demand sectors, and two-thirds from the supply sectors. If every tonne of CO₂ not emitted is valued up to US$10 in 2020 and $20 in 2030, additional P&M may further reduce emissions by 110 MtCO₂ by 2030.     

PROJECTIONS OF CLIMATE CHANGE FOR THE CZECH REPUBLIC

The paper deals with a selection of the climatological baseline, GCM validity and construction of the climate change scenarios for an impact assessment in the Czech territory. The period of 1961–1990 has been selected as the climatological baseline. The corresponding database includes more than 50 monthly mean temperature and precipitation series, and 16 time series of daily meteorological data that contain also the solar radiation data. The 1× CO₂ outputs produced by four GCMs, provided by the CSMT (GISS, GFD30, GFD01, and CCCM), were compared with observed temperature and precipitation conditions in western and central Europe with a particular attention devoted to the Czech territory. The GCM ability to simulate annual cycles of temperature, precipitation and radiation was thoroughly examined. The GISS and CCCM were selected as a basis for constructing climate change scenarios as they simulated reasonably the observed patterns. According to the GISS variant, 2× CO₂ climate assumes a higher winter and lower summer warming, and an increase in annual precipitation amounts. A dangerous combination of the summer temperature increase and declining precipitation amounts is a specific feature of the CCCM scenario. An incremental scenario for temperature and precipitation is based on the combination of prescribed changes in both annual means and annual courses.     

Implications of CO2 global warming on great lakes ice cover

Statistical ice cover models were used to project daily mean basin ice cover and annual ice cover duration for Lakes Superior and Erie. Models were applied to a 1951–80 base period and to three 30-year steady double carbon dioxide (2 × CO₂) scenarios produced by the Geophysical Fluid Dynamics Laboratory (GFDL), the Goddard Institute of Space Studies (GISS), and the Oregon State University (OSU) general circulation models. Ice cover estimates were made for the West, Central, and East Basins of Lake Erie and for the West, East, and Whitefish Bay Basins of Lake Superior. Average ice cover duration for the 1951– 80 base period ranged from 13 to 16 weeks for individual lake basins. Reductions in average ice cover duration under the three 2 × CO₂ scenarios for individual lake basins ranged from 5 to 12 weeks for the OSU scenario, 8 to 13 weeks for the GISS scenario, and 11 to 13 weeks for GFDL scenario. Winters without ice formation become common for Lake Superior under the GFDL scenario and under all three 2 × CO₂ scenarios for the Central and East Basins of Lake Erie. During an average 2 × CO₂ winter, ice cover would be limited to the shallow areas of Lakes Erie and Superior. Because of uncertainties in the ice cover models, the results given here represent only a first approximation and are likely to represent an upper limit of the extent and duration of ice cover under the climate change projected by the three 2 × CO₂scenarios. Notwithstanding these limitations, ice cover projected by the 2 × CO₂ scenarios provides a preliminary assessment of the potential sensitivity of the Great Lakes ice cover to global warming. Potential environmental and socioeconomic impacts of a 2 × CO₂ warming include year-round navigation, change in abundance of some fish species in the Great Lakes, discontinuation or reduction of winter recreational activities, and an increase in winter lake evaporation.     

Climate-related uncertainties in projections of the twenty-first century terrestrial carbon budget: off-line model experiments using IPCC greenhouse-gas scenarios and AOGCM climate projections

A terrestrial ecosystem model (Sim-CYCLE) was driven by multiple climate projections to investigate uncertainties in predicting the interactions between global environmental change and the terrestrial carbon cycle. Sim-CYCLE has a spatial resolution of 0.5°, and mechanistically evaluates photosynthetic and respiratory CO₂ exchange. Six scenarios for atmospheric-CO₂ concentrations in the twenty-first century, proposed by the Intergovernmental Panel on Climate Change, were considered. For each scenario, climate projections by a coupled atmosphere–ocean general circulation model (AOGCM) were used to assess the uncertainty due to socio-economic predictions. Under a single CO₂ scenario, climate projections with seven AOGCMs were used to investigate the uncertainty stemming from uncertainty in the climate simulations. Increases in global photosynthesis and carbon storage differed considerably among scenarios, ranging from 23 to 37% and from 24 to 81 Pg C, respectively. Among the AOGCM projections, increases ranged from 26 to 33% and from 48 to 289 Pg C, respectively. There were regional heterogeneities in both climatic change and carbon budget response, and different carbon-cycle components often responded differently to a given environmental change. Photosynthetic CO₂ fixation was more sensitive to atmospheric CO₂, whereas soil carbon storage was more sensitive to temperature. Consequently, uncertainties in the CO₂ scenarios and climatic projections may create additional uncertainties in projecting atmospheric-CO₂ concentrations and climates through the interactive feedbacks between the atmosphere and the terrestrial ecosystem.     

Sensitivity of FORGRO to climatic change scenarios: A case study on Betula pubescens, Fagus sylvatica and Quercus robur in The Netherlands

The impacts of the climate change predictions of four general circulation models (GFDL, GISS, OSU and UKMO) on net primary production (NPP) ofBetula pubescens, Fagus sylvatica and Quercus robur in The Netherlands were analysed using the process-based model FORGRO. FORGRO is a model suitable to simulate growth of managed mono-species stands. For the GCMs mentioned, both transient and equilibrium 2 × CO₂ scenarios of temperature and precipitation change were evaluated and compared with responses under current climate. It was found that the NPP increases in the transient scenarios, but remains the same or declines in the 2 × CO₂ scenarios. This is because respiration increases more with rising temperature than photosynthesis. During the transient scenarios this effect gradually increases, while in the 2 × CO₂ scenario this effect is operating over the entire simulation period.If water limitation is taken into account, then the NPP of the reference scenario is reduced. In both the transient and 2 × CO₂ scenarios mis water limitation is annulated, resulting in a stronger response of NPP compared to the situation without water limitation. This enhancement of the response is most pronounced in the transient scenario due to the gradual effect of temperature on respiration.Similar results were obtained with a version of FORGRO in which the photosynthesis module of HYBRID (PGEN) is incorporated, although the response in FORGRO-PGEN is usually higher than that of FORGRO. This is because the response of photosynthesis to CO₂ rises with increasing temperature as defined in the PGEN-model, but not according to FORGRO.     

Global vegetation change predicted by the modified Budyko model

A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO₂ doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). Global vegetation maps after climate change are compared to the current climate vegetation map using the kappa statistic for judging agreement, as well as by calculating area statistics. All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Specifically, all Boreal vegetation classes are predicted to shrink. The interrelated classes of Tundra, Taiga, and Temperate Forest are predicted to replace much of their poleward (mostly northern) neighbors. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favoring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50–100 y needed for CO₂ doubling, it is nevertheless not clear if projected global warming will result in drastic or benign vegetation change.     

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.     

A Climate Change Database for Biological Assessments in the Southeastern United States: Development and Case Study

A regional database containing historical time series and climate change scenarios for the Southeastern United States was developed for the U.S.D.A. Forest Service Southern Global Change Program (SGCP). Daily historical values of maximum temperature, minimum temperature and precipitation and empirically derived estimates of vapor pressure deficit and solar radiation across a uniform 1° latitude × 1° longitude grid were obtained. Climate change scenarios of temperature, precipitation, vapor pressure deficit and solar radiation were generated using semi-empirical techniques which combined historical time series and simulation field summaries from GISS, GFDL, OSU and UKMO General Circulation Model (GCM) experiments. An internally consistent 1° latitude × 1° longitude climate change scenario database was produced in which vapor pressure deficit and solar radiation conditions were driven by the GCM temperature projections, but were not constrained to agree with GCM calculated radiation and humidity fields. Some of the unique characteristics of the database were illustrated through a case study featuring growing season and annual potential evapotranspiration (ET_p) estimates. Overall, the unconstrained scenarios produced smaller median ET_p changes from historical baseline conditions, with a smaller range of outcomes than those driven by GCM-directed scenarios. Collectively, the range of annual and growing season ET changes from baseline estimates in response to the unconstrained climate scenarios was +10% to +40%. No outlier responses were identified. ET_p changes driven by GCM-directed (constrained) UKMO radiation and humidity scenarios were on the order of +100%, resulting in the identification of some ET_p responses as statistical outliers. These response differences were attributed to differences between the constrained and unconstrained humidity scenarios.     

Impacts of CO2-induced climatic change on water resources in the Great Lakes Basin

Scenarios of CO₂-induced climatic change, based on models produced by the Goddard Institute for Space Studies (GISS) and the Geophysical Fluid Dynamics Lab (GFDL), were used to estimate future changes in water supply in the Great Lakes Basin. The major components of annual Net Basin Supply, surface runoff and lake evaporation, were estimated using the Thornthwaite water balance model and the mass transfer approach, respectively. Two scenarios were derived from each climatic change model, one based on present normal winds, the other assuming reduced wind speeds. A third scenario was derived from GFDL, using wind speeds generated by the GFDL model. Results varied from a decrease in Net Basin Supply of 28.9% for GISS-normal winds, to a decrease of 11.7% for GFDL-reduced wind speeds. All five scenarios projected decreases. These differences in projection will have to be considered when performing climate impact studies, since economic activities affected by lake levels would probably experience different impacts under these scenarios.     

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.     

Projections of Climate Change Effects on Water Temperature Characteristics of Small Lakes in the Contiguous U.S.

To simulate effects of projected climate change on water temperature characteristics of small lakes in the contiguous U.S., a deterministic, one-dimensional year-round water temperature model is applied. In cold regions the model simulates ice and snow cover on a lake. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous U.S. for the period 1961–1979 were used to represent present climate conditions. The projected climate change owing to a doubling of atmospheric CO₂ was obtained from the output of the Canadian Climate Center General Circulation Model. The simulated water temperature and ice characteristics are related to the geometric and trophic state lake characteristics and to geographic location. By interpolation, the sensitivity of lake water temperature characteristics to latitude, longitude, lake geometry and trophic status can therefore be quantified for small lakes in the contiguous U.S. The 2× CO₂ climate scenario is projected to increase maximum and minimum lake surface temperatures by up to 5.2°C. (Maximum surface water temperatures in lakes near the northern and the southern border of the contiguous U.S. currently differ by up to 13°C.) Maximum temperature differences between lake surface and lake bottom are projected to increase in average by only 1 to 2°C after climate warming. The duration of seasonal summer stratification is projected to be up to 66 days longer under a 2×CO₂ climate scenario. Water temperatures of less than 8°C are projected to occur on lake bottoms during a period which is on the order of 50 days shorter under a 2×CO₂ climate scenario. With water temperature change projected to be as high as 5.2°C, ecological impacts such as shifts in species distributions and in fish habitat are most likely. Ice covers on lakes of northern regions would also be changed strongly.     

REGIONAL CLIMATE CHANGE SCENARIOS FOR VULNERABILITY AND ADAPTATION ASSESSMENTS

This paper describes the regional climate change scenarios that are recommended for use in the U.S. Country Studies Program (CSP) and evaluates how well four general circulation models (GCMs) simulate current climate over Europe. Under the umbrella of the CSP, 50 countries with varying skills and experience in developing climate change scenarios are assessing vulnerability and adaptation. We considered the use of general circulation models, analogue warm periods, and incremental scenarios as the basis for creating climate change scenarios. We recommended that participants in the CSP use a combination of GCM based scenarios and incremental scenarios. The GCMs, in spite of their many deficiencies, are the best source of information about regional climate change. Incremental scenarios help identify sensitivities to changes in a particular meteorological variable and ensure that a wide range of regional climate change scenarios are considered. We recommend using the period 1951–1980 as baseline climate because it was a relatively stable climate period globally. Average monthly changes from the GCMs and the incremental changes in climate variables are combined with the historical record to produce scenarios. The scenarios do not consider changes in interannual, daily, or subgrid scale variability. Countries participating in the Country Studies Program were encouraged to compare the GCMs' estimates of current climate with actual long-term climate means. In this paper, we compare output of four GCMs (CCCM, GFDL, UKMO, and GISS) with observed climate over Europe by performing a spatial correlation analysis for temperature and precipitation, by statistically comparing spatial patterns averaged climate estimates from the GCMs with observed climate, and by examining how well the models estimate seasonal patterns of temperature and precipitation. In Europe, the GISS and CCCM models best simulate current temperature, whereas the GISS and UK89 models, and the CCCM model, best simulate precipitation in defined northern and southern regions, respectively.     

Exploring optimal mitigation and adaptation investment strategies in China

After the successful conclusion of the Paris Climate Conference (Conference of the Parties (COP) 21), countries are now attempting to identify implementation measures. An important consensus has been reached on the necessity of putting in place both mitigation and adaptation measures. In this context, this article builds a three-sector China and rest of the world model based on the DE-carbonization Model with Endogenous Technologies for Emission Reductions (DEMETER) and World Induced Technical Change Hybrid (WITCH) models. It assesses China’s mitigation and adaptation investment strategies by 2050 with an optimization including climate externalities. By making the 450?ppm target and China’s 2030 CO₂ emissions peak exogenous, it assesses two scenarios: (1) investment only in mitigation and (2) investment in both mitigation and adaptation. The article finds the following: First, the policy package with investment in both mitigation and adaptation can ensure lower CO₂ emissions and avoid more climate damage. Second, investment in adaptation should be massively injected by around 2040, whereas mitigation efforts should be continuous. Third, the CO₂ emissions peak in the tertiary sector should come prior to 2030 while the emissions pathway of the secondary sector could be allowed to increase slowly until 2035.

POLICY RELEVANCE

• The necessity of engaging in both mitigation and adaptation has been widely accepted since the Paris Climate Conference (COP21), yet few studies exist in this regard concerning China.

• Substantial investment in adaptation needs to be introduced by 2040 while the investment on mitigation should peak by 2030.

• The CO₂ emissions peak in the tertiary sector would be reached prior to 2030 while the peak in the secondary sector is achieved around 2035.

• This provides an alternative in China to the existing argument of an earlier peak in the secondary sector.

     

Nutrient cycling and biomass growth at a North American hardwood site in relation to climate change: ForSVA assessments

The biomass growth and nutrient cycling model ForSVA (forest-soil-vegetation-atmosphere model) is used to analyze potential changes in nutrient cycling (Ca, Mg, K, N, S) and forest biomass production in response to four climate-change scenarios. The analysis is done for an old-growth hardwood stand within the Turkey Lakes watershed north of Lake Superior, Ontario. With ForSVA, any effects due to species interactions, competition, and resulting species shifts are not addressed explicitly. Instead, the calculations are based on functional relationships that primarily respond to soil and climate conditions in general, and to structural changes within the forest itself. The simulations cover a period of about 200 years, and suggest that a principal change in annual pattern of soil moisture is to be expected for the UKMO climate scenario, and that this scenario will likely induce a major change of vegetation covertype resulting from major changes in seasonal soil moisture conditions and a general lack of snow during winter. In contrast, the OSU, GISS and GFDL scenarios should not cause a principal change in forest type, but the soil will be somewhat drier than what is currently the case. However, increased precipitation rates and/or air temperatures during summer and spring should, in combination, increase actual evapotranspiration rates, and such increases should increase net primary production. For example, calculations with GFDL suggest that cumulative wood biomass at the Turkey Lakes site can be expected to increase by 25%. Foliage biomass and fine root production can be expected to increase by 70% from current conditions. It is assumed that within-tree allocation of photosynthate is not affected by climate.     

Potential impacts of climate change on a mixed broadleaved-Korean pine forest stand: A gap model approach

A gap-typed forest dynamic model KOPIDE was used to assess the dynamic responses of a mixed broadleaved-Korean pine forest stand to climate change in northeastern China. The GFDL climate change scenario was applied to derive the changes in environmental variables, such as 10 °C based DEGD and PET/P, which were used to implement the model. The simulation result suggests that the climate change would cause important changes in stand structure. Korean pine, the dominant species in the area under current climate conditions, would disappear under the GFDL equilibrium scenario. Oak and elm would become the dominant species replacing Korean pine, ash and basswood. Such a potential change in forest structure would require different strategies for forest management in northeastern China.     

Simulation of the effect of doubled atmospheric CO2 on the climate of northern and central California

A Local Climate Model (LCM) is described that can provide a high-resolution (10 km) simulation of climate resulting from a doubling of atmospheric CO₂ concentrations. A canonicalregression function is used to compute the monthly temperature (mean of daily-maximum-temperature) and precipitation for any point, given a set of predictor variables. Predictor variables represent the influence of terrain, sea-surface temperature (SST), windfields, CO₂ concentration, and solar radiation on climate. The canonical-regression function is calibrated and validated using empirical windfield, SST, and climate data from stations in the western U.S. To illustrate an application of the LCM, the climate of northern and central California is simulated for a doubled CO₂ (600 ppmv) and a control scenario (300 ppmv CO₂). Windfields and SSTs used to compute predictor variables are taken from general circulation model simulations for these two scenarios. LCM solutions indicate that doubling CO₂ will result in a 3 C° increase in January temperature, a 2 C° increase in July temperature, a 16 mm (37%) increase in January precipitation, and a 3 mm (46%) increase in July precipitation.     

Spatial impact of projected changes in rainfall and temperature on wheat yields in Australia

Climate projections over the next two to four decades indicate that most of Australia’s wheat-belt is likely to become warmer and drier. Here we used a shire scale, dynamic stress-index model that accounts for the impacts of rainfall and temperature on wheat yield, and a range of climate change projections from global circulation models to spatially estimate yield changes assuming no adaptation and no CO₂ fertilisation effects. We modelled five scenarios, a baseline climate (climatology, 1901–2007), and two emission scenarios (“low” and “high” CO₂) for two time horizons, namely 2020 and 2050. The potential benefits from CO₂ fertilisation were analysed separately using a point level functional simulation model. Irrespective of the emissions scenario, the 2020 projection showed negligible changes in the modelled yield relative to baseline climate, both using the shire or functional point scale models. For the 2050-high emissions scenario, changes in modelled yield relative to the baseline ranged from ?5 % to +6 % across most of Western Australia, parts of Victoria and southern New South Wales, and from ?5 to ?30 % in northern NSW, Queensland and the drier environments of Victoria, South Australia and in-land Western Australia. Taking into account CO₂ fertilisation effects across a North–south transect through eastern Australia cancelled most of the yield reductions associated with increased temperatures and reduced rainfall by 2020, and attenuated the expected yield reductions by 2050.     

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.     

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.