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1.
The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO2 concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO2 concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.  相似文献   

2.
Summary  It is expected that a change in climatic conditions due to global warming will directly impact agricultural production. Most climate change studies have been applied at very large scales, in which regions were represented by only one or two weather stations, which were mainly located at airports of major cities. The objective of this study was to determine the potential impact of climate change at a local level, taking into account weather data recorded at remote locations. Daily weather data for a 30-year period were obtained for more than 500 sites, representing the southeastern region of the USA. Climate change scenarios, using transient and equilibrium global circulation models (GCM), were defined, created and applied to the daily historical weather data. The modified temperature, precipitation and solar radiation databases corresponding to each of the climate change scenarios were used to run the CERES v.3.5 simulation model for maize and winter wheat and the CROPGRO v.3.5 model for soybean and peanut. The GCM scenarios projected a shorter duration of the crop-growing season. Under the current level of CO2, the GCM scenarios projected a decrease of crop yields in the 2020s. When the direct effects of CO2 were assumed in the study, the scenarios resulted in an increase in soybean and peanut yield. Under equilibrium , the GCM climate change scenarios projected a decrease of maize and winter wheat yield. The indirect effects of climate change also tended to decrease soybean and peanut yield. However, when the direct effects of CO2 were included, most of the scenarios resulted in an increase in legume yields. Possible changes in sowing data, hybrids and cultivar selection, and fertilization were considered as adaptation options to mitigate the potential negative impact of potential warming. Received July 20, 1999/Revised April 18, 2000  相似文献   

3.
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 (As), maximum depth (HMAX), and Secchi depth (zs), 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 /HMAX) 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.  相似文献   

4.
Many impact studies require climate change information at a finer resolution than that provided by global climate models (GCMs). This paper investigates the performances of existing state-of-the-art rule induction and tree algorithms, namely single conjunctive rule learner, decision table, M5 model tree, and REPTree, and explores the impact of climate change on maximum and minimum temperatures (i.e., predictands) of 14 meteorological stations in the Upper Thames River Basin, Ontario, Canada. The data used for evaluation were large-scale predictor variables, extracted from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset and the simulations from third generation Canadian coupled global climate model. Data for four grid points covering the study region were used for developing the downscaling model. M5 model tree algorithm was found to yield better performance among all other learning techniques explored in the present study. Hence, this technique was applied to project predictands generated from GCM using three scenarios (A1B, A2, and B1) for the periods (2046–2065 and 2081–2100). A simple multiplicative shift was used for correcting predictand values. The potential of the downscaling models in simulating predictands was evaluated, and downscaling results reveal that the proposed downscaling model can reproduce local daily predictands from large-scale weather variables. Trend of projected maximum and minimum temperatures was studied for historical as well as downscaled values using GCM and scenario uncertainty. There is likely an increasing trend for T max and T min for A1B, A2, and B1 scenarios while decreasing trend has been observed for B1 scenarios during 2081–2100.  相似文献   

5.
A series of coupled atmosphere-ocean-land global climate model (GCM) simulations using the National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) has been performed for the period 1870–2099 at a T85 horizontal resolution following the GCM experimental design suggested in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). First, a hindcast was performed using the atmospheric concentrations of three greenhouse gases (CO2, CH4, N2O) specified annually and globally on the basis of observations for the period 1870–1999. The hindcast results were compared with observations to evaluate the GCM’s reliability in future climate simulations. Second, climate projections for a 100-year period (2000–2099) were made using six scenarios of the atmospheric concentrations of the three greenhouse gases according to the A1FI, A1T, A1B, A2, B1, and B2 emission profiles of the Special Report on Emissions Scenarios. The present CCSM simulations are found to be consistent with IPCC’s AR4 results in the temporal and spatial distributions for both the present-day and future periods. The GCM results were used to examine the changes in extreme temperatures and precipitation in East Asia and Korea. The extreme temperatures were categorized into warm and cold events: the former includes tropical nights, warm days, and heat waves during summer (June–July–August) and the latter includes frost days, cold days, and cold surges during winter (December–January–February). Focusing on Korea, the results predict more frequent heat waves in response to future emissions: the projected percentage changes between the present day and the late 2090s range from 294% to 583% depending on the emission scenario. The projected global warming is predicted to decrease the frequency of cold extreme events; however, the projected changes in cold surge frequency are not statistically significant. Whereas the number of cold surges in the A1FI emission profile decreases from the present-day value by up to 24%, the decrease in the B1 scenario is less than 1%. The frequency and intensity of extreme precipitation events year-round were examined. Both the frequency and the intensity of these events are predicted to increase in the region around Korea. The present results will be helpful for establishing an adaptation strategy for possible climate change nationwide, especially extreme climate events, associated with global warming.  相似文献   

6.
 Changes in land surface driving variables, predicted by GCM transient climate change experiments, are confirmed to exhibit linearity in the global mean land temperature anomaly, ΔT l . The associated constants of proportionality retain spatial and seasonal characteristics of the GCM output, whilst ΔT l is related to radiative forcing anomalies. The resultant analogue model is shown to be robust between GCM runs and as such provides a computationally efficient technique of extending existing GCM experiments to a large range of climate change scenarios. As an example impacts study, the analogue model is used to drive a terrestrial ecosystem model, and predicted changes in terrestrial carbon are found to be similar to those when using GCM anomalies directly. Received: 4 January 1999 / Accepted: 11 December 1999  相似文献   

7.
For the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC), the recent version of the coupled atmosphere/ocean general circulation model (GCM) of the Max Planck Institute for Meteorology has been used to conduct an ensemble of transient climate simulations These simulations comprise three control simulations for the past century covering the period 1860–2000, and nine simulations for the future climate (2001–2100) using greenhouse gas (GHG) and aerosol concentrations according to the three IPCC scenarios B1, A1B and A2. For each scenario three simulations were performed. The global simulations were dynamically downscaled over Europe using the regional climate model (RCM) REMO at 0.44° horizontal resolution (about 50 km), whereas the physics packages of the GCM and RCM largely agree. The regional simulations comprise the three control simulations (1950–2000), the three A1B simulations and one simulation for B1 as well as for A2 (2001–2100). In our study we concentrate on the climate change signals in the hydrological cycle and the 2 m temperature by comparing the mean projected climate at the end of the twenty-first century (2071–2100) to a control period representing current climate (1961–1990). The robustness of the climate change signal projected by the GCM and RCM is analysed focussing on the large European catchments of Baltic Sea (land only), Danube and Rhine. In this respect, a robust climate change signal designates a projected change that sticks out of the noise of natural climate variability. Catchments and seasons are identified where the climate change signal in the components of the hydrological cycle is robust, and where this signal has a larger uncertainty. Notable differences in the robustness of the climate change signals between the GCM and RCM simulations are related to a stronger warming projected by the GCM in the winter over the Baltic Sea catchment and in the summer over the Danube and Rhine catchments. Our results indicate that the main explanation for these differences is that the finer resolution of the RCM leads to a better representation of local scale processes at the surface that feed back to the atmosphere, i.e. an improved representation of the land sea contrast and related moisture transport processes over the Baltic Sea catchment, and an improved representation of soil moisture feedbacks to the atmosphere over the Danube and Rhine catchments.  相似文献   

8.
Future Area Burned in Canada   总被引：16，自引：3，他引：16  
Historical relationships between weather, the Canadian fire weather index (FWI) system components and area burned in Canadian ecozones were analysed on a monthly basis in tandem with output from the Canadian and the Hadley Centre GCMs to project future area burned. Temperature and fuel moisture were the variables best related to historical monthly area burned with 36–64% of the variance explained depending on ecozone. Our results suggest significant increases in future area burned although there are large regional variations in fire activity. This was especially true for the Canadian GCM where some ecozones show little change in area burned, however area burned was not projected to decrease in any of the ecozones modelled. On average, area burned in Canada is projected to increase by 74–118% by the end of this century in a 3 × CO2 scenario. These estimates do not explicitly take into account any changes in vegetation, ignitions, fire season length, and human activity (fire management and land use activities) that may influence area burned. However, the estimated increases in area burned would have significant ecological, economic and social impacts for Canada.  相似文献   

9.
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.  相似文献   

10.
This study was undertaken to determine the impact of potential global warming on the magnitude of hail losses to winter cereal crops within two areas situated on the western slopes of New South Wales, Australia. A model relating historical crop hail losses to climatic variables was developed for each area. These models included seasonal measures of vertical instability, low-level moisture and the height of the freezing level. In both areas, windshear was not found to be an important factor influencing seasonal crop hail losses. The two crop hail loss models were then used in conjunction with upper-air climatic data from three single mixed-layer global climate models (GCMs). Each GCM was run for 1 × CO2 conditions and for 2 × CO2 conditions. The enhanced greenhouse effect on climatic variables was taken to be the difference between their values for these two runs. Changes to climatic variables were then translated directly into changes in the percentage value of the winter cereal crop lost due to hail. In both areas, the three GCMs agreed concerning the direction of change in each of the variables used in the crop hail loss model. GCM simulations of the greenhouse effect resulted in a decline in winter cereal crop hail losses, with the exception of one GCM simulation at one location where losses increased slightly. None of the changes due to the enhanced greenhouse effect, however, were significant owing to a large observed seasonal variability of crop hail losses. Also, the simulated seasonal variability of crop hail losses did not change significantly due to the enhanced greenhouse effect. These results depended on two important assumptions. Firstly, it was assumed that the dominant relationships between climatic variables and crop hail losses in the past would remain the same in a future climate. Secondly, it was assumed that the single mixed-layer GCMs used in the study were correctly predicting climate change under enhanced greenhouse conditions.  相似文献   

11.
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.  相似文献   

12.
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.  相似文献   

13.
A deterministic monthly runoff model (MINRUN96)was applied to watersheds with substantially differentclimates. One watershed is in the north-central U.S.(Minnesota) and is heavily timbered. The other is inthe south-central U.S. (Oklahoma) and is mainlycovered with pastures and agricultural crops. Runoffwas simulated for past historical climate and twoprojected 2 × CO2 climate scenarios. The output ofGeneral Circulation Models (GCMs) was used to specifythe two 2 × CO2 climate scenarios. One GCM is theGoddard Institute of Space Studies (GISS) model andthe other is from the Canadian Center of ClimateModelling (CCC). In the northern watershed morerunoff is projected to occur in winter under a warmerclimate and less runoff in spring. About 80%increase in fall runoff and 20% decrease in soilmoisture in June and July is projected for thesouthern watershed. When runoff simulations for the2 × CO2 climate scenarios were compared to pastrunoff, it was apparent that the change in runoffdepended on both the season and the magnitude of theprecipitation change. An increase in springprecipitation caused a significant increase in directrunoff, whereas an increase in fall precipitationcaused only a slight increase in total runoff. Alsothe runoff-precipitation relationship in the warm andseasonally dry southern watershed is very differentfrom that in the temperate and humid climate of thenorth. Therefore, runoff responses to projectedclimate change are substantially different in the tworegions.  相似文献   

14.
The study makes a probabilistic assessment of drought risks due to climate change over the southeast USA based on 15 Global Circulation Model (GCM) simulations and two emission scenarios. The effects of climate change on drought characteristics such as drought intensity, frequency, areal extent, and duration are investigated using the seasonal and continuous standard precipitation index (SPI) and the standard evapotranspiration index (SPEI). The GCM data are divided into four time periods namely Historical (1961–1990), Near (2010–2039), Mid (2040–2069), and Late (2070–2099), and significant differences between historical and future time periods are quantified using the mapping model agreement technique. Further, the kernel density estimation approach is used to derive a novel probability-based severity-area-frequency (PBS) curve for the study domain. Analysis suggests that future increases in temperature and evapotranspiration will outstrip increases in precipitation and significantly affect future droughts over the study domain. Seasonal drought analysis suggest that the summer season will be impacted the most based on SPI and SPEI. Projections based on SPI follow precipitation patterns and fewer GCMs agree on SPI and the direction of change compared to the SPEI. Long-term and extreme drought events are projected to be affected more than short-term and moderate ones. Based on an analysis of PBS curves, especially based on SPEI, droughts are projected to become more severe in the future. The development of PBS curves is a novel feature in this study and will provide policymakers with important tools for analyzing future drought risks, vulnerabilities and help build drought resilience. The PBS curves can be replicated for studies around the world for drought assessment under climate change.  相似文献   

15.
Although representation of hydrology is included in all regional climate models (RCMs), the utility of hydrological results from RCMs varies considerably from model to model. Studies to evaluate and compare the hydrological components of a suite of RCMs and their use in assessing hydrological impacts from future climate change were carried out over Europe. This included using different methods to transfer RCM runoff directly to river discharge and coupling different RCMs to offline hydrological models using different methods to transfer the climate change signal between models. The work focused on drainage areas to the Baltic Basin, the Bothnian Bay Basin and the Rhine Basin. A total of 20 anthropogenic climate change scenario simulations from 11 different RCMs were used. One conclusion is that choice of GCM (global climate model) has a larger impact on projected hydrological change than either selection of emissions scenario or RCM used for downscaling.  相似文献   

16.
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.  相似文献   

17.
The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.  相似文献   

18.
A regional atmospheric climate model with multi-layer snow module (RACMO2) is forced at the lateral boundaries by global climate model (GCM) data to assess the future climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS). Two different GCMs (ECHAM5 until 2100 and HadCM3 until 2200) and two different emission scenarios (A1B and E1) are used as forcing to capture a realistic range in future climate states. Simulated ice sheet averaged 2 m air temperature (T2m) increases (1.8–3.0 K in 2100 and 2.4–5.3 K in 2200), simultaneously and with the same magnitude as GCM simulated T2m. The SMB and its components increase in magnitude, as they are directly influenced by the temperature increase. Changes in atmospheric circulation around Antarctica play a minor role in future SMB changes. During the next two centuries, the projected increase in liquid water flux from rainfall and snowmelt, together 60–200 Gt year?1, will mostly refreeze in the snow pack, so runoff remains small (10–40 Gt year?1). Sublimation increases by 25–50 %, but remains an order of magnitude smaller than snowfall. The increase in snowfall mainly determines future changes in SMB on the AIS: 6–16 % in 2100 and 8–25 % in 2200. Without any ice dynamical response, this would result in an eustatic sea level drop of 20–43 mm in 2100 and 73–163 mm in 2200, compared to the twentieth century. Averaged over the AIS, a strong relation between $\Updelta$ SMB and $\Updelta\hbox{T}_{2{\rm m}}$ of 98 ± 5 Gt w.e. year?1 K?1 is found.  相似文献   

19.
Projecting the impacts of climate change includes various uncertainties from physical, biophysical, and socioeconomic processes. Providing a more comprehensive impact projection that better represents the uncertainties is a priority research issue. We used an ensemble-based projection approach that accounts for the uncertainties in climate projections associated with general circulation models (GCMs) and biophysical and empirical parameter values in a crop model. We applied the approach to address the paddy rice yield change in Japan in the 2050s (2046–2065) and 2090s (2081–2100) relative to the 1990s (1981–2000). Seventeen climate projections, nine (eight) climate projections performed by seven (six) GCMs conditional on the Special Report on Emission Scenarios (SRES) A1B (A2), were included in this projection. In addition, 50 sets of biophysical and empirical parameter values of a large-scale process-based crop model for irrigated paddy rice were included to represent the uncertainties of crop parameter values. The planting windows, cultivation practices, and crop cultivars in the future were assumed to be the same as the level in the baseline period (1990s). The resulting probability density functions conditioned on SRES A1B and A2 indicate projected median yield changes of +?17.2% and +?26.9% in Hokkaido, the northern part of Japan, in the 2050s and 2090s with 90% probability intervals of (??5.2%, +?40.3%) and (+?6.3%, +?51.2%), relative to the 1990s mean yield, respectively. The corresponding values in Aichi, on the Pacific side of Western Japan, are 2.2% and ??0.8%, with 90% probability intervals of (??15.0%, +?14.9%) and (??33.4%, +?17.9%), respectively. We also provided geographical maps of the probability that the future 20-year mean yield will decrease and that the future standard deviation of yield for 20 years will increase. Finally, we investigated the relative contributions of the climate projection and crop parameter values to the uncertainty in projecting yield change in the 2090s. The choice of GCM yielded a relatively larger spread of projected yield changes than that of the other factors. The choice of crop parameter values could be more important than that of GCM in a specific prefecture.  相似文献   

20.
The Mesoscale Modeling System Version 5 (MM5) was one-way nested to the Goddard Institute for Space Studies global climate model (GISS GCM), which provided the boundary conditions for present (1990s) and future (IPCC SRES A2 scenario, 2050s) five-summer “time-slice” simulations over the continental and eastern United States. Five configurations for planetary boundary layer, cumulus parameterization, and radiation scheme were tested, and one set was selected for use in the New York City Climate and Health Project—a multi-disciplinary study investigating the effects of climate change and land-use change on human health in the New York metropolitan region. Although hourly and daily data were used in the health project, in this paper we focus on long-term current and projected mean climate change. The GISS-MM5 was very sensitive to the choice of cumulus parameterization and planetary boundary layer scheme, leading to significantly different temperature and precipitation outcomes for the 1990s. These differences can be linked to precipitation type (convective vs. non-convective), to their effect on solar radiation received at the ground, and ultimately to surface temperature. The projected changes in climate (2050s minus 1990s) were not as sensitive to choice of model physics combination. The range of the projected surface temperature changes at a given grid point among the model versions was much less than the mean change for all five model configurations, indicating relative consensus for simulating surface temperature changes among the different model projections. The MM5 versions, however, offer less consensus regarding 1990s to 2050s changes in precipitation amounts. All of the projected 2050s temperature changes were found to be significant at the 95th percent confidence interval, while the majority of the precipitation changes were not.  相似文献   

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