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1.
Climate Change and People-Caused Forest Fire Occurrence in Ontario   总被引：2，自引：0，他引：2  
Climate change that results from increasing levels of greenhouse gases in the atmosphere has the potential to increase temperature and alter rainfall patterns across the boreal forest region of Canada. Daily output from the Canadian Climate Centre coupled general circulation model (GCM) and the Hadley Centre's HadCM3 GCM provided simulated historic climate data and future climate scenarios for the forested area of the province of Ontario, Canada. These models project that in climates of increased greenhouse gases and aerosols, surface air temperatures will increase while seasonal precipitation amounts will remain relatively constant or increase slightly during the forest fire season. These projected changes in weather conditions are used to predict changes in the moisture content of forest fuel, which influences the incidence of people-caused forest fires. Poisson regression analysis methods are used to develop predictive models for the daily number of fires occurring in each of the ecoregions across the forest fire management region of Ontario. This people-caused fire prediction model, combined with GCM data, predicts the total number of people-caused fires in Ontario could increase by approximately 18% by 2020–2040 and50% by the end of the 21st century.  相似文献   

2.
利用Hadley气候预测与研究中心的区域气候模式系统PRECIS单向嵌套该中心全球海-气耦合气候模式HadCM3高分辨率的大气部分HadAM3H,分析了SRES A2情景下2071-2100年相对于气候基准时段（1961-1990年）中国区域的气候变化,包括气温和降水的年际、季节和日时间尺度的变化以及极端气候事件的变化趋势。模拟结果表明：气温呈明显增加趋势,其中新疆和东北地区增温明显。而降水表现了更大的年际变化和季节变化,冬季南方降水减少,但沿黄河流域的降水明显增加,夏季与冬季相比呈现出相反的趋势。此外,连续高温日数呈现增加趋势,而连续霜冻日数呈现减少趋势。连续湿日数也表现出一定的增加趋势。  相似文献   

3.
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.  相似文献   

4.
We examine the internal climate variability of a 1000?year long integration of the third version of the Hadley Centre coupled model (HadCM3). The model requires no flux adjustment, needs no spin up procedure prior to coupling and has a stable climate in the global mean. The principal aims are (1) to validate the internal climate variability against observed climate variability, (2) to examine the model for any periodic modes of variability, (3) to use the model estimate of internal climate variability to asses the probability of occurrence of observed trends in climate variables, and (4) to compare HadCM3 with the previous version of the Hadley Centre model, HadCM2. The magnitude and frequency characteristics of the variability of the global mean surface temperature of HadCM3 on annual to decadal time scales is in good agreement with the observations. Observed upward trends in temperature over the last 20?years and longer are inconsistent with the internal variability of the model. The simulated spatial pattern of surface temperature variability is qualitatively similar to that observed, although there is an overestimation of the land temperature variability and regional errors in ocean temperature variability. The model simulates an El Niño Southern Oscillation with an irregular 3–4?year cycle, and with a teleconnection pattern which is much more like the observations than was found in HadCM2. The interdecadal variability of the model ocean in the tropical Pacific, North Pacific and North Atlantic is broadly similar to that in the real world with none of the simulated patterns having any periodic behaviour. HadCM3 simulates an Arctic Oscillation/North Atlantic Oscillation (NAO) in Northern Hemisphere winter which has a spatial pattern consistent with the observations in the Atlantic region, but has too much teleconnection with the North Pacific. The recent observed upward trend in the NAO index is inconsistent with the model internal variability. The variability of the simulated zonal mean atmospheric temperature shows some marked differences to the observed zonal mean temperature variability, although the comparison is confounded by the sparse observational network and its possible contamination by a climate change signal.  相似文献   

5.
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.  相似文献   

6.
CERES-Wheat, a dynamic process crop growth model, is specified and validated for seven sites in the major wheat-growing regions of Spain. Variables explaining a significant proportion of simulated yield variance are crop water (sum of precipitation and irrigation) and temperature during the growing season. A multiple linear regression model is developed to represent simulated yield response to these variables. Seven agro-climatic regions are defined based on K-mean cluster analysis of temperature and precipitation data from 329 meteorological stations and provincial crop yield data. The yield functions derived from the validated crop model were then used with the gridded agro-climatic database to conduct a spatial analysis of climate change impacts on national wheat production. Climate change scenarios with and without sulfate aerosols developed from the Hadley Centre (HCGG and HCGS) and Canadian Climate Centre (CCGG and CCGC) are tested.  相似文献   

7.
The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961–2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18–6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011–2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961–2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and CGCM3 A2 scenario). According to the model simulation, the September–November periods might be the more significant months projecting the increment of the precipitation amount around over 50 %, while the precipitation deficit would be seen in March–May periods.  相似文献   

8.
The outputs of three GCMs, ECHAM5, CCSM3 and HadCM3, are downscaled for the eastern Mediterranean–Black Sea region for the period 1961–1990 using a regional climate model, RegCM3, to assess the capability of these models in simulating the climatology of the region. In addition, the NCEP/NCAR Reanalysis data are also downscaled for the same period to display the performance of the regional climate model for the same region, which constitutes a relatively complex terrain and rich variety of climates. The gridded observational dataset of CRU is primarily used in the evaluation of the models, however, a regional dataset, which is based on a relatively dense gauging network, is also used to see how it affects the performance measures of the models. The reanalysis simulation indicates that RegCM3 is able to simulate the precipitation and surface temperature as well as the upper level fields reasonably well. However, it tends to overestimate the precipitation over the mountainous areas. All three GCM models are found to be highly skilled in simulating the winter precipitation and temperature in the region. The two models, ECHAM5 and HadCM3, are also good at simulating the summer precipitation and temperature, but the CCSM3 simulation generates dryer and warmer conditions than the observations for the whole region, which are most likely a result of the dryness in the upper levels of the original outputs. The use of the regional observational dataset does not necessarily improve the pattern correlations, but it yields better match between the modeled and observed precipitation in terms of variability and root-mean-square difference. It could be said that the outputs of these GCMs can be used in the climate change downscaling and impact assessment studies for the region, given that their strengths and weaknesses that are displayed in the present study are considered.  相似文献   

9.
Based on principal component analysis (PCA) and a k-means clustering algorithm, daily mean sea level pressure (MSLP) fields over the northeastern Atlantic and Western Europe, simulated by the Hadley Centre's second generation coupled ocean-atmosphere GCM (HADCM2) control run (HADCM2CON), are validated by comparison with the observed daily MSLP fields. It is clear that HADCM2 reproduces daily MSLP fields and its seasonal variability over the region very well, despite suffering from some deficiencies, such as the systematic displacement of the atmospheric centres of action. Four daily circulation patterns, previously identified from the observed daily MSLP fields over the area and well related to daily precipitation in Portugal, were also well classified from the daily MSLP fields simulated by HADCM2. The model can also simulate rather successfully the relationships between the four daily circulation patterns and daily precipitation in southern Portugal. However, compared with observations, daily precipitation intensities simulated by the model are too weak in southern Portugal. Nevertheless, HADCM2 represents a considerable improvement relative to the UKTR experiment. The results described here imply that it is doubtful whether regional precipitation scenarios provided by HADCM2 can be directly applied in impact studies and that a downscaling technique, based on daily circulation patterns, might be successful in reproducing local and regional precipitation characteristics. Moreover, the four circulation patterns can also be clearly identified in the two perturbed experiments, one under greenhouse gases forcing only (HADCM2GHG) and the other under additional forcing of sulphate aerosol (HADCM2SUL), although changes in the frequencies of occurrence of certain circulation patterns are found. Nevertheless, the observed links between regional precipitation in southern Portugal and large-scale atmospheric circulation seem likely to hold in the model's perturbed climate. It is therefore credible to use those links to downscale large-scale atmospheric circulation from GCM simulations to obtain future precipitation scenarios in southern Portugal. Received: 21 August 1998 / Accepted: 28 May 1999  相似文献   

10.
X-C Zhang 《Climatic change》2007,84(3-4):337-363
Spatial downscaling of climate change scenarios can be a significant source of uncertainty in simulating climatic impacts on soil erosion, hydrology, and crop production. The objective of this study is to compare responses of simulated soil erosion, surface hydrology, and wheat and maize yields to two (implicit and explicit) spatial downscaling methods used to downscale the A2a, B2a, and GGa1 climate change scenarios projected by the Hadley Centre’s global climate model (HadCM3). The explicit method, in contrast to the implicit method, explicitly considers spatial differences of climate scenarios and variability during downscaling. Monthly projections of precipitation and temperature during 1950–2039 were used in the implicit and explicit spatial downscaling. A stochastic weather generator (CLIGEN) was then used to disaggregate monthly values to daily weather series following the spatial downscaling. The Water Erosion Prediction Project (WEPP) model was run for a wheat–wheat–maize rotation under conventional tillage at the 8.7 and 17.6% slopes in southern Loess Plateau of China. Both explicit and implicit methods projected general increases in annual precipitation and temperature during 2010–2039 at the Changwu station. However, relative climate changes downscaled by the explicit method, as compared to the implicit method, appeared more dynamic or variable. Consequently, the responses to climate change, simulated with the explicit method, seemed more dynamic and sensitive. For a 1% increase in precipitation, percent increases in average annual runoff (soil loss) were 3–6 (4–10) times greater with the explicit method than those with the implicit method. Differences in grain yield were also found between the two methods. These contrasting results between the two methods indicate that spatial downscaling of climate change scenarios can be a significant source of uncertainty, and further underscore the importance of proper spatial treatments of climate change scenarios, and especially climate variability, prior to impact simulation. The implicit method, which applies aggregated climate changes at the GCM grid scale directly to a target station, is more appropriate for simulating a first-order regional response of nature resources to climate change. But for the site-specific impact assessments, especially for entities that are heavily influenced by local conditions such as soil loss and crop yield, the explicit method must be used.  相似文献   

11.
Data from global and regional climate models refer to grid cells and, hence, are basically different from station data. This particularly holds for variables with enhanced spatio-temporal variability like precipitation. On the other hand, many applications like for instance hydrological models require atmospheric data with the statistical characteristics of station data. Here, we present a dynamical-statistical tool to construct virtual station data based on regional climate model output for tropical West Africa. This weather generator (WEGE) incorporates daily gridded rainfall from the model, an orographic term and a stochastic term, accounting for the chaotic spatial distribution of local rain events within a model grid box. In addition, the simulated probability density function of daily precipitation is adjusted to available station data in Benin. It is also assured that the generated data are still consistent with other model parameters like cloudiness and atmospheric circulation. The resulting virtual station data are in excellent agreement with various observed characteristics which are not explicitly addressed by the WEGE algorithm. This holds for the mean daily rainfall intensity and variability, the relative number of rainless days and the scaling of precipitation in time. The data set has already been used successfully for various climate impact studies in Benin.  相似文献   

12.
 The realism of the Hadley Centre’s coupled climate model (HadCM2) is evaluated in terms of its simulation of the winter North Atlantic Oscillation (NAO), a major natural mode of the Northern Hemisphere atmosphere that is currently the subject of considerable scientific interest. During 1400 y of a control integration with present-day radiative forcing levels, HadCM2 exhibits a realistic NAO associated with spatial patterns of sea level pressure, synoptic activity, temperature and precipitation anomalies that are very similar to those observed. Spatially, the main model deficiency is that the simulated NAO has a teleconnection with the North Pacific that is stronger than observed. In a temporal sense the simulation is compatible with the observations if the recent observed trend (from low values in the 1960s to high values in the early 1990s) in the winter NAO index (the pressure difference between Gibraltar and Iceland) is ignored. This recent trend is, however, outside the range of variability simulated by the control integration of HadCM2, implying that either the model is deficient or that external forcing is responsible for the variation. It is shown, by analysing two ensembles, each of four HadCM2 integrations that were forced with historic and possible future changes in greenhouse gas and sulphate aerosol concentrations, that a small part of the recent observed variation may be a result of anthropogenic forcing. If so, then the HadCM2 experiments indicate that the anthropogenic effect should reverse early next century, weakening the winter pressure gradient between Gibraltar and Iceland. Even combining this anthropogenic forcing and internal variability cannot explain all of the recent observed variations, indicating either some model deficiency or that some other external forcing is partly responsible. Received: 20 August 1998 / Accepted: 12 May 1999  相似文献   

13.
Downscaling of South America present climate driven by 4-member HadCM3 runs   总被引：5，自引：2，他引：3  
The objective of this work is to evaluate climate simulations over South America using the regional Eta Model driven by four members of an ensemble of the UK Met Office Hadley Centre HadCM3 global model. The Eta Model has been modified with the purpose of performing long-term decadal integrations and has shown to reproduce “present climate”—the period 1961–1990—reasonably well when forced by HadCM3. The global model lateral conditions with a resolution of 2.5° latitude?×?3.75° longitude were provided at a frequency of 6?h. Each member of the global model ensemble has a different climate sensitivity, and the four members were selected to span the range of uncertainty encompassed by the ensemble. The Eta Model nested in the HadCM3 global model was configured with 40-km horizontal resolution and 38 layers in the vertical. No large-scale internal nudging was applied. Results are shown for austral summer and winter at present climate defined as 1961–90. The upper and low-level circulation patterns produced by the Eta-CPTEC/HadCM3 experiment set-up show good agreement with reanalysis data and the mean precipitation and temperature with CRU observation data. The spread in the downscaled mean precipitation and temperature is small when compared against model errors. On the other hand, the benefits in using an ensemble is clear in the improved representation of the seasonal cycle by the ensemble mean over any one realization. El Ni?o and La Ni?a years were identified in the HadCM3 member runs based on the NOAA Climate Prediction Center criterion of sea surface temperature anomalies in the Ni?o 3.4 area. The frequency of the El Ni?o and La Ni?a events in the studied period is underestimated by HadCM3. The precipitation and temperature anomalies typical of these events are reproduced by most of the Eta-CPTEC/HadCM3 ensemble, although small displacements of the positions of the anomalies occur. This experiment configuration is the first step on the implementation of Eta-CPTEC/HadCM3 upcoming experiments on climate change studies that are discussed in a companion paper.  相似文献   

14.
The multivariate adaptive regression splines (MARS) model was used to capture the observed relationships between sea level pressure (SLP) anomalies over the Euro-Atlantic sector and the winter time (December–February) monthly rainfall at eight sites in Portugal; possible anthropogenic changes of the rainfall in a perturbed future climate were then estimated by using both the observed SLP-rainfall relationships, described by MARS models, and the GCM simulated SLP, taken from the output of the Hadley Centre Transient Climate Change Experiment (UKTR). Also, principal component analysis was carried out to reduce the dimensionality of the SLP data, and to assess the ability of the GCM in simulating the large-scale circulation; the first six principal components were retained as predictors in the MARS model. The MARS model were built up by using the data for 1946–1991 as the training set and that for 1901–1943 as the testing set, showing satisfactory prediction skills. It is concluded that the UKTR control simulation successfully reproduced main features of the large-scale circulation, but the observed relationship between SLP and the regional rainfall was not well preserved. With respect to the 54-year experiment of perturbed run, the MARS estimation of rainfall and the relevant direct GCM rainfall output possess similar multi-annual variations; however, there are substantial differences regarding details; the change in the area mean of winter time mean monthly rainfall in Portugal estimated by MARS (indirect GCM output) is about –12.7 mm per 54-year, and the relevant direct GCM output is –16.9 mm/54-year. This reduction tendency is consistent with previously reported findings respecting rainfall in the Iberian Peninsula, which were based on the MPI (Max-Planck Institute for Meteorology) transient simulations.  相似文献   

15.
Summary Two climate model simulations made with the Rossby Centre regional Atmospheric model version 1 (RCA1) are evaluated for the precipitation climate in Scania, southernmost Sweden. These simulations are driven by the HadCM2 and the ECHAM4/OPYC3 global circulation models (GCMs) for 10 years. Output from the global and the regional simulations are compared with an observational data set, constructed from a dense precipitation gauge network in Scania. Area-averaged time series corresponding to the size and location of the RCA1 grid points in Scania have been created (the Scanian Data Set). This data set was compared to a commonly used gridded surface climatology provided by the Climatic Research Unit (CRU). Relatively large differences were found, mainly due to the fact that the CRU-climatology uses fewer stations and lacks a correction for rain-gauge under-catch. This underlines the importance of the data set chosen for model evaluations. The validation is carried out at a large scale including the whole area of Scania and at the finest resolution of RCA1 (the grid point level). When integrated over the whole area of Scania, RCA1 improves the shape of the annual precipitation cycle and the inter-annual variability compared to output from the GCMs. The RCA1 control climate is generally too wet compared to the observations. At the grid point level, RCA1 improves the simulation of the variability compared to the GCMs. There is a strong positive correlation between precipitation and altitude in all seasons in the observations. This relationship is, however, much weaker and even reversed in the RCA1 simulations. Analysis of the dense rain gauge network reveals features of spatial variability at around 20–35km in the area and indicates that a finer resolution is needed if the spatial variability in the area is to be better captured by RCA1.  相似文献   

16.
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   

17.
We investigate the effect of changes in daily and interannual variability of temperature and precipitation on yields simulated by the CERES-Wheat model at two locations in the central Great Plains. Changes in variability were effected by adjusting parameters of the Richardson daily weather generator. Two types of changes in precipitation were created: one with both intensity and frequency changed; and another with change only in persistence. In both types mean total monthly precipitation is held constant. Changes in daily (and interannual) variability of temperature result in substantial changes in the mean and variability of simulated wheat yields. With a doubling of temperature variability, large reductions in mean yield and increases in variability of yield result primarily from crop failures due to winter kill at both locations. Reduced temperature variability has little effect. Changes in daily precipitation variability also resulted in substantial changes in mean and variability of yield. Interesting interactions of the precipitation variability changes with the contrasting base climates are found at the two locations. At one site where soil moisture is not limiting, mean yield decreased and variability of yield increased with increasing precipitation variability, whereas mean yields increased at the other location, where soil moisture is limiting. Yield changes were similar for the two different types of precipitation variability change investigated. Compared to an earlier study for the same locations wherein variability changes were effected by altering observed time series, and the focus was on interannual variability, the present results for yield changes are much more substantial. This study demonstrates the importance of taking into account change in daily (and interannual) variability of climate when analyzing the effect of climate change on crop yields.The National Center for Atmospheric Research is sponsored by the National Science Foundation.  相似文献   

18.
This study used the Statistical Downscaling Model (SDSM) to increase the resolution of the Global Circulation Model (GCM) at forecasting the amount of precipitation in the Mekong River basin. The model was initially calibrated using the reanalysis data by National Centers for Environmental Prediction (NCEP) and the data on observed precipitation. The results of comparison between the SDSM calculations and the observational data were used to generate the distribution of precipitation until 2099 using HadCM3, SRES A2 and B2 scenarios. After total annual precipitation had been downscaled, the percentage change in precipitation was interpolated among the selected stations in order to create precipitation maps. Both A2 and B2 scenario indicate the possibility of remarkable increase in annual precipitation in the Mekong basin, which may amount to 150 and 110%, respectively. The December–January–February precipitation is likely to increase significantly in the most part of the region, and in some areas, almost by three times. On the contrary, the June–July–August precipitation will remarkably decrease in the different parts of the territory under study. As the water resource sector is the backbone of the economics of this region including hydropower and agricultural sector, the changes in the amount of precipitation and its interannual variability can put the usual water business into stress. Thus, proper adaptive measures should be applied both at local and at regional levels for the benefit of all associated countries utilizing the resource of the Mekong River.  相似文献   

19.
Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.  相似文献   

20.
The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.  相似文献   

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