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.     

CLIMATE CHANGE HYDROLOGY AND WATER RESOURCES IMPACT AND ADAPTATION FOR SELECTED RIVER BASINS IN THE CZECH REPUBLIC

The Czech Republic has a northern hemisphere Atlantic-continental type of moderate climate. Mean annual temperature ranges between 1.0 and 9.4 °C (between 8.8 and 18.5 °C in summer and between –6.8 and 0.2 °C in winter). Annual precipitation ranges between 450 mm in dry regions and 1300 mm in mountainous regions of the country. With its 2000 m³ per capita fresh water availability, the Czech Republic is slightly below average. Occasional water shortages do not usually result from general unavailability of water resources but rather from time or space variability of water supply/demand and high degree of water resources exploitation. To study potential impacts of climate change on hydrological system and water resources, four river basins have been selected in the territory of the Czech Republic: the Elbe River at Decin (50761.7 km²), the Zelivka River at Soutice (1188.6 km²), the Upa River at Ceska Skalice (460.7 km²) and the Metuje River at Marsov n. M. (93.9 km²). To simulate potential changes in runoff, three hydrological models have been applied using incremental and GCM (GISS, GFDL and CCCM) scenarios: the BILAN water balance model, the SACRAMENTO (SAC-SMA) conceptual model and the CLIRUN water balance model. The paper reviews methods applied in the study, results of the assessments and concludes with suggestions for possible general adaptation policy options where the preference is for nonstructural measures such as water conservation, efficient water demand management and protection of water resources.     

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.     

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.     

Analyse régionale des simulations climatiques du modèle canadien de circulation générale de l'atmosphère pour le territoire québécois

Abstract

Current understanding of the possible nature of climatic change at the regional scale is limited by the spatial resolution of General Circulation Models (GCM). The use of GCM outputs without correction linked to the spatial variability of the variables can bring significant errors in their utilization at the regional scale. The potential of the Canadian GCM for regional applications in Quebec has been analysed by comparison to the climatic normals of temperature and precipitation, measured over the Quebec climatological network, on an annual and seasonal basis. This analysis has been undertaken with the support of a geographical information system (GIS) (PAMAP). In summary, a difference between the climatic normal and the GCM output has been estimated at 20% for temperature and 30% for precipitation. We present an analysis of a corrected regionalized scenario for the province of Quebec of the possible climatic change simulated by the Canadian GCM under the hypothesis of a doubling of atmospheric CO₂. Results show an increase of the annual average temperature of 4° C for summer and 6°C for winter, associated with an average increase of 80 mm (10%) in annual precipitation, reaching 25% in some regions.     

Constructing Site-Specific Climate Change Scenarios on a Monthly Scale Using Statistical Downscaling

Summary Monthly mean temperature and monthly precipitation totals in two small catchments in the Czech Republic are estimated from large-scale 500 hPa height and 1000/500 hPa thickness fields using statistical downscaling. The method used is multiple linear regression. Whereas precipitation can be determined from large-scale fields with some confidence in only a few months of the year, temperature can be determined successfully. Principal components calculated separately from the height and thickness anomalies are identified as the best predictor set. The method is most accurate if the regression is performed using seasons based on three months. The test on an independent sample, consisting of warm seasons, confirms that the method successfully reproduces the difference in mean temperature between two climatic states, which indicates that this downscaling method is applicable for constructing scenarios of a future climate change. The ECHAM3 GCM is used for scenario construction. The GCM is shown to simulate surface temperature and precipitation with low accuracy, whereas the large-scale atmospheric fields are reproduced well; this justifies the downscaling approach. The observed regression equations are applied to 2xCO₂ GCM output so that the model’s bias is eleminated. This procedure is then discussed and finally, temperature scenarios for the 2xCO₂ climate are constructed for the two catchments. Received December 3, 1998 Revised December 4, 1999     

Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations

The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.     

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.     

RegCM3 regional climatologies for South America using reanalysis and ECHAM global model driving fields

To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.     

Annual and seasonal climate and climatic changes in the Canadian prairies simulated by the CCC GCM

Abstract

As part of a study on the effects of climatic variability and change on the sustainability of agriculture in Alberto, the modelling performance of the second‐generation Canadian Climate Centre GCM (general circulation model) is examined. For the region in general, the simulation of 1 × CO₂ mean temperature is generally better than that for mean precipitation, and summer is the season best modelled for each variable. At the scale of individual grid squares, DJF (December, January, February) (temperature) and JJA (June, July, August) (precipitation) are the seasons best modelled. The GCM‐simulated increases in mean annual temperature resulting from a doubling of CO₂ are of the order of 5 to 6°C in the Prairie region, with much of this increase resulting from substantial warming in the winter and spring. Increases in mean annual precipitation are of the order of 50 to 150 mm (changes of +5 to +15%), with the greatest changes again occurring in winter and spring. As far as the limited GCM run durations allow, temperature and precipitation variance generally show no significant changes from a 1 × CO₂ to a 2 × CO₂ climate. Increased precipitation in winter and spring does not result in greater snow accumulations owing to the magnitude of warming; and significant decreases in soil moisture content occur in summer and fall. The resulting effects on the growing season and moisture regime have the potential to affect agricultural practices in the area.     

Nested regional simulation of climate change over the Alps for the scenario of a doubled greenhouse forcing

Summary Simulated temperature and precipitation changes over western Europe for a scenario of doubled atmospheric concentrations of CO₂ are presented. The simulations are performed using a Limited Area Model LAM (RegCM2) nested into a General Circulation Model (ECHAM3). Both model components are operated at very high spatial resolutions — approximately 120 km for the GCM and 20 km for the LAM; the LAM domain encompasses a region of 1100 × 1100 km squared. Climatologies for five January and five July periods have been simulated. Average surface (2 m) temperatures are found to increase by 1.4 K in winter (January) and 3.9 K in summer (July); this latter figure is, however, largely dependent on a positive bias in the summer temperature fields of the driving GCM. Average precipitation changes are generally small in absolute values, but exhibit considerable spatial variability. Large precipitation amounts are seen to be shifted towards higher elevations with a corresponding reduction in the upwind areas. The results are discussed taking into account the predictive skill of the modelling system, which is derived from comparing the simulated present day temperature and precipitation fields to the corresponding climatological information. A method is introduced to assess the reliability of climate scenario predictions — such as those discussed here — on the basis of this predictive skill.With 14 Figures     

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.     

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.     

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.     

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.     

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.     

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.     

Water Resources Implications of Global Warming: A U.S. Regional Perspective

The implications of global warming for the performance of six U.S. water resource systems are evaluated. The six case study sites represent a range of geographic and hydrologic, as well as institutional and social settings. Large, multi-reservoir systems (Columbia River, Missouri River, Apalachicola-Chatahoochee-Flint (ACF) Rivers), small, one or two reservoir systems (Tacoma and Boston) and medium size systems (Savannah River) are represented. The river basins range from mountainous to low relief and semi-humid to semi-arid, and the system operational purposes range from predominantly municipal to broadly multi-purpose. The studies inferred, using a chain of climate downscaling, hydrologic and water resources systems models, the sensitivity of six water resources systems to changes in precipitation, temperature and solar radiation. The climate change scenarios used in this study are based on results from transient climate change experiments performed with coupled ocean-atmosphere General Circulation Models (GCMs) for the 1995 Intergovernmental Panel on Climate Change (IPCC) assessment. An earlier doubled-CO₂ scenario from one of the GCMs was also used in the evaluation. The GCM scenarios were transferred to the local level using a simple downscaling approach that scales local weather variables by fixed monthly ratios (for precipitation) and fixed monthly shifts (for temperature). For those river basins where snow plays an important role in the current climate hydrology (Tacoma, Columbia, Missouri and, to a lesser extent, Boston) changes in temperature result in important changes in seasonal streamflow hydrographs. In these systems, spring snowmelt peaks are reduced and winter flows increase, on average. Changes in precipitation are generally reflected in the annual total runoff volumes more than in the seasonal shape of the hydrographs. In the Savannah and ACF systems, where snow plays a minor hydrological role, changes in hydrological response are linked more directly to temperature and precipitation changes. Effects on system performance varied from system to system, from GCM to GCM, and for each system operating objective (such as hydropower production, municipal and industrial supply, flood control, recreation, navigation and instream flow protection). Effects were generally smaller for the transient scenarios than for the doubled CO₂ scenario. In terms of streamflow, one of the transient scenarios tended to have increases at most sites, while another tended to have decreases at most sites. The third showed no general consistency over the six sites. Generally, the water resource system performance effects were determined by the hydrologic changes and the amount of buffering provided by the system's storage capacity. The effects of demand growth and other plausible future operational considerations were evaluated as well. For most sites, the effects of these non-climatic effects on future system performance would about equal or exceed the effects of climate change over system planning horizons.     

The potential effects of climate change on summer season dairy cattle milk production and reproduction

The potential direct effects of possible global warming on summer season dairy production and reproduction were evaluated for the United States and Europe. Algorithms used for milk production and conception rate were previously developed and validated. Three widely known global circulation models (GISS, GFDL, and UKMO) were used to represent possible scenarios of future climate. Milk production and conception rate declines were highest under the UKMO model scenario and lowest under the GISS model scenario. Predicted declines for the GCM scenarios are generally higher than either 1 year in 10 probability-based declines or declines based on the abnormally hot summer of 1980 in the United States. The greatest declines (about 10% for the GISS and GFDL scenarios, and about 20% for the UKMO scenario) in the United States are predicted to occur in the Southeast and the Southwest. Substantial declines (up to 35%) in conception rates were also predicted in many locations, particularly the eastern and southern United States. These areas correspond to areas of high dairy cattle concentration. They already have relatively large summer season milk production declines resulting from normally hot conditions. Thus, the actual impacts of increased production declines may be greater in other areas, which are not accustomed to large summer season declines and therefore may require more extensive mitigation measures.Published as Paper No. 9698 Journal Series, Nebraska Agricultural Research Division. The work reported here was conducted under Nebraska Agricultural Research Division Project 27–007.     

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.