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1.
This modeling study addresses the potential impacts of climate change and changing climate variability due to increased atmospheric CO2 concentration on soybean (Glycine max (L.) Merrill) yields in theMidwestern Great Lakes Region. Nine representative farm locations and six future climate scenarios were analyzed using the crop growth model SOYGRO. Under the future climate scenarios earlierplanting dates produced soybean yield increases of up to 120% above current levels in the central and northern areas of the study region. In the southern areas, comparatively small increases (0.1 to 20%) and small decreases (–0.1 to–25%) in yield are found. The decreases in yield occurred under the Hadley Center greenhouse gas run (HadCM2-GHG), representing a greater warming, and the doubled climate variability scenario – a more extreme and variableclimate. Optimum planting dates become later in the southern regions. CO2fertilization effects (555 ppmv) are found to be significant for soybean, increasing yields around 20% under future climate scenarios.For the study region as a whole the climate changes modeled in this research would have an overall beneficial effect, with mean soybean yield increases of 40% over current levels.  相似文献   

2.
This study comprises (1) an analysis of recent climate trends at two sites in north-west India (Ludhiana in Punjab and Delhi) and (2) an impact and risk assessment for wheat yields associated with climatic variability. North-west Indian agriculture is dominated by rice-wheat rotation in which the wheat season (‘rabi’, November to March) is characterized by predominantly dry conditions—superimposed by very high inter-annual variability of rainfall (17 to 260 mm in Ludhiana and <1 to 155 mm in Delhi). While rainfall remained without discernable trend over the last three decades, minimum and average temperatures showed increasing trends of 0.06 and 0.03°C year???1, respectively, at Ludhiana. The site in (metropolitan) Delhi was apparently influenced by city-effects, which was noticeable from the decrease in solar radiation of 0.09 MJ m???2 day???1 year???1. The CERES-wheat model was used to calculate yields of rainfed wheat that were at both locations highly correlated with seasonal rainfall. An assessment framework was developed to quantify yield impacts due to rainfall variability in three steps: (1) data from different years were aggregated into four classes, i.e., years with scarce, low, moderate, and high rainfall, (2) yield records of each rainfall class were ranked according to yield to facilitate (3) a comparison of yields with identical rank, i.e. among the best yield of each class, the second-best, etc. The class with moderate rainfall was taken as baseline yield to compute yield impacts of other rainfall scenarios. Years with scarce rainfall resulted in only 34% (Ludhiana) and 35% (Delhi) of the baseline yield. The yields in years with low rainfall accounted for 61% (Delhi) and 49% (Ludhiana) of the baseline yields. In Ludhiana, high rainfall years resulted in 200% yield as compared to the baseline yield, whereas they reached only 105% in Delhi. Low-intensity (1× and 3×) irrigation decreased the relative yield losses, but entailed a higher vulnerability in terms of absolute yield losses. Only high-intensity (4×) irrigation buffered wheat yields against adverse rainfall years. Early sowing was beneficial for wheat yields under all rainfall scenarios. The framework could be a valuable decision-support tool at the farm level where seasonal rainfall variability is high.  相似文献   

3.
With the continuing warming due to greenhouse gases concentration, it is important to examine the potential impacts on regional crop production spatially and temporally. We assessed China’s potential maize production at 50 × 50 km grid scale under climate change scenarios using modelling approach. Two climate changes scenarios (A2 and B2) and three time slices (2011–2040, 2041–2070, 2071–2100) produced by the PRECIS Regional Climate Model were used. Rain-fed and irrigated maize yields were simulated with the CERES-Maize model, with present optimum management practices. The model was run for 30 years of baseline climate and three time slices for the two climate change scenarios, without and with simulation of direct CO2 fertilization effects. Crop simulation results under climate change scenarios varied considerably between regions and years. Without the CO2 fertilization effect, China’s maize production was predicted to suffer a negative effect under both A2 and B2 scenarios for all time slices, with greatest production decreases in today’s major maize planting areas. When the CO2 fertilization effect is taken into account, production was predicted to increase for rain-fed maize but decrease for irrigated maize, under both A2 and B2 scenarios for most time periods.  相似文献   

4.
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.  相似文献   

5.
This study investigates the impact of global warming on the savannization of the tropical land region and also examines the relative roles of the impact of the increase of greenhouse gas concentration and future changes in land cover on the tropical climate. For this purpose, a mechanistic–statistical–dynamical climate model with a bidirectional interaction between vegetation and climate is used. The results showed that climate change due to deforestation is more than that due to greenhouse gases in the tropical region. The warming due to deforestation corresponds to around 60% of the warming in the tropical region when the increase of CO2 concentration is included together. However, the global warming due to deforestation is negligible. On the other hand, with the increase of CO2 concentration projected for 2100, there is a lower decrease of evapotranspiration, precipitation and net surface radiation in the tropical region compared with the case with only deforestation. Differently from the case with only deforestation, the effect of the changes in the net surface radiation overcomes that due to the evapotranspiration, so that the warming in the tropical land region is increased. The impact of the increase of CO2 concentration on a deforestation scenario is to increase the reduction of the areas covered by tropical forest (and a corresponding increase in the areas covered by savanna) which may reach 7.5% in future compared with the present climate. Compared with the case with only deforestation, drying may increase by 66.7%. This corroborates with the hypothesis that the process of savannization of the tropical forest can be accelerated in future due to global warming.  相似文献   

6.
We use the CERES family of crop models to assess the effect of different spatial scales of climate change scenarios on the simulated yield changes of maize (Zea mays L.), winter wheat (Triticum aestivum L.),and rice (Oryza sativa L.) in the Southeastern United States. The climate change scenarios were produced with the control and doubled CO2 runs of a high resolution regional climate model anda coarse resolution general circulation model, which provided the initial and lateral boundary conditions for the regional model. Three different cases were considered for each scenario: climate change alone, climate change plus elevated CO2, and the latter with adaptations. On the state level,for most cases, significant differences in the climate changed yields for corn were found, the coarse scale scenario usually producing larger modeled yield decreases or smaller increases. For wheat, however, which suffered large decreases in yields for all cases, very little contrast in yield based on scale of scenario was found. Scenario scale resulted in significantly different rice yields, but mainly because of low variability in yields. For maize the primary climate variable that explained the contrast in the yields calculated from the two scenarios is the precipitation during grain fill leading to different water stress levels. Temperature during vernalization explains some contrasts in winter wheat yields. With adaptation, the contrasts in the yields of all crops produced by the scenarios were reduced but not entirely removed. Our results indicate that spatial resolution of climate change scenarios can be an important uncertainty in climate change impact assessments, depending on the crop and management conditions.  相似文献   

7.
Fulu Tao  Zhao Zhang 《Climatic change》2011,105(3-4):409-432
Projections of future climate change are plagued with uncertainties from global climate models and emission scenarios, causing difficulties for impact assessments and for planners taking decisions on adaptation measure. Here, we developed an approach to deal with the uncertainties and to project the changes of maize productivity and water use in China using a process-based crop model, against a global mean temperature (GMT) increase scale relative to 1961?C1990 values. From 20 climate scenarios output from the Intergovernmental Panel on Climate Change Data Distribution Centre, we adopted the median values of projected changes in monthly mean climate variables for representative stations and driven the CERES-Maize model to simulate maize production under baseline and future climate scenarios. Adaptation options such as automatic planting, automatic application of irrigation and fertilization were considered, although cultivars were assumed constant over the baseline and future. After assessing representative stations across China, we projected changes in maize yield, growing period, evapotranspiration, and irrigation-water use for GMT changes of 1°C, 2°C, and 3°C, respectively. Results indicated that median values of projected decreases in the yields of irrigated maize without (with) consideration of CO2-fertilization effects ranged from 1.4% to 10.9% (1.6% to 7.8%), 9.8% to 21.7% (10.2% to 16.4%), and 4.3% to 32.1% (3.9% to 26.6%) for GMT changes of 1°C, 2°C, and 3°C, respectively. Median values of projected changes in irrigation-water use without (with) consideration of CO2-fertilization effects ranged from ?1.3% to 2.5% (?18.8% to 0.0%), ?43.6% to 2.4% (?56.1% to ?18.9%), and ?19.6% to 2.2% (?50.6% to ?34.3%), which were ascribed to rising CO2 concentration, increased precipitation, as well as reduced growing period with GMT increasing. For rainfed maize, median values of projected changes in yields without (with) consideration of CO2-fertilization effects ranged from ?22.2% to ?1.0% (?10.8% to 0.7%), ?27.6% to ?7.9% (?18.1% to ?5.6%), and ?33.7% to ?4.6% (?25.9% to ?1.6%). Approximate comparisons showed that projected maize yield losses were larger than previous estimates, particularly for rainfed maize. Our study presents an approach to project maize productivity and water use with GMT increases using process-based crop models and multiple climate scenarios. The resultant impact function is fundamental for identifying which climate change level is dangerous for food security.  相似文献   

8.
Summary The crop growth model CERES-Maize is used to estimate the direct (through enhanced fertilisation effect of ambient CO2) and indirect (through changed climate conditions) effects of increased concentration of atmospheric CO2 on maize yields. The analysis is based on multi-year crop model simulations run with daily weather series obtained alternatively by a direct modification of observed weather series and by a stochastic weather generator. The crop model is run in two settings: stressed yields are simulated in water and nutrient limited conditions, potential yields in water and nutrient unlimited conditions. The climate change scenario was constructed using the output from the ECHAM3/T42 model (temperature), regression relationships between temperature and solar radiation, and an expert judgement (precipitation). Results: (i) After omitting the two most extreme misfits, the standard error between the observed and modelled yields is 11%. (ii) The direct effect of doubled CO2: The stressed yields would increase by 36–41% in the present climate and by 61–66% in the 2 × CO2 climate. The potential yields would increase only by 9–10% as the improved water use efficiency does not apply. (iii) The indirect effect of doubled CO2: The stressed yields would decrease by 27–29% (14–16%) at present (doubled) ambient CO2 concentration. The increased temperature shortens the phenological phases and does not allow for the optimal development of the crop. The simultaneous decrease of precipitation and increase of temperature and solar radiation deepen the water stress, thereby reducing the yields. The reduction of the potential yields is significantly smaller as the effect of the increased water stress does not apply. (iv) If both direct and indirect effects of doubled CO2 are considered, the stressed yields should increase by 17–18%, and the potential yields by 5–14%. (v) The decrease of the stressed yields due to the indirect effect may be reduced by applying earlier planting dates. Received March 9, 2001 Revised September 25, 2001  相似文献   

9.
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   

10.
Northeast China is the main crop production region in China, and future climate change will directly impact crop potential yields, so exploring crop potential yields under future climate scenarios in Northeast China is extremely critical for ensuring future food security. Here, this study projected the climate changes using 12 general circulation models (GCMs) under two moderate Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and 6.0) from 2015 to 2050. Then, based on the Global Agro-ecological Zones (GAEZ) model, we explored the effect of climate change on the potential yields of maize and paddy rice in Northeast China during 2015–2050. The annual relative humidity increased almost throughout the Northeast China under two RCPs. The annual precipitation increased more than 400 mm in some west, east, and south areas under RCP 4.5, but decreased slightly in some areas under RCP 6.0. The annual wind speed increased over 2 m/s in the west region. The annual net solar radiation changes varied significantly with latitude, but the changes of annual maximum temperature and minimum temperature were closely related to the terrain. Under RCP 4.5, the average maize potential yield increased by 34.31% under the influence of climate changes from 2015 to 2050. The average rice potential yield increased by 16.82% from 2015 to 2050. Under RCP 6.0, the average maize and rice potential yields increased by 25.65% and 6.34% respectively. The changes of maize potential yields were positively correlated with the changes of precipitation, wind speed, and net solar radiation (the correlation coefficients were > 0.2), and negatively correlated with the changes of relative humidity, minimum and maximum temperature under two RCPs. The changes of rice potential yields were positively correlated with the changes of precipitation (correlation coefficient = 0.15) under RCP 4.5. Under RCP 6.0, it had a slight positive correlation with net solar radiation, relative humidity, and wind speed.  相似文献   

11.
As a result of climate change, and in particular rainfall changes, agricultural production is likely to change across the globe. Until now most research has focused on areas which will become unsustainable for agricultural production. However, there are also regions where climate change might actually improve conditions for growth. In the western Pampas region of Argentina, average annual rainfall has increased by 100–200 mm over the last 70 years, mainly during summer. Wheat is grown during winter, primarily on stored soil water and the main factor limiting plant production in this area is rainfall. Using the well tested simulation model APSIM-NWheat, we studied whether recent climate change has potentially opened new opportunities for wheat cropping in Argentina. Simulation results indicated that the additional rainfall in the Pampas of Argentina has increased the achievable yield (defined as the yield limited by solar radiation, temperature, water and nitrogen supply) of wheat in the currently cropped region, but less than expected based on the large amount of additional rainfall. The higher achievable yield from additional rainfall could potentially allow an expansion of profitable wheat cropping into currently non-cropped areas, where the achievable wheat yield increased in average from 1 t/ha to currently 2 t/ha. However, the poor water-holding capacity of the sandy soils which dominate the region outside the current cropping area limits the systems ability to use most of the increased summer rainfall. Nevertheless, the current higher achievable yield indicates a suitability of the region for cropping, which will slightly decline or remain unchanged depending on summer rainfall storage, with current and future climate change, including projected changes in rainfall, temperature and atmospheric CO2 concentration. Factors other than just the achievable yield will eventually influence any future development of this region for cropping, including the high sensitivity of the sandy soils to erosion and nutrient leaching, current relatively high land prices, restrictions on clearing for cropping, the distance to the nearest port and current unsuitable cultivars withstanding the high frost risk.  相似文献   

12.
The study used a modelling approach to assess the potential impacts of likely climate change and increase in CO2 concentration on the wheat growth and water balance in Murray?CDarling Basin in Australia. Impacts of individual changes in temperature, rainfall or CO2 concentration as, well as the 2050 and 2070 climate change scenarios, were analysed. Along an E?CW transect, wheat yield at western sites (warmer and drier) was simulated to be more sensitive to temperature increase than that at eastern sites; along the S?CN transect, wheat yield at northern warmer sites was simulated to be more sensitive to temperature increase, within 1?C3°C temperature increase. Along the E?CW and S?CN transects, wheat at drier sites would benefit more from elevated [CO2] than at wetter sites, but more sensitive to the decline in rainfall. The increase in temperature only did not have much impact on water balance. Elevated [CO2] increased the drainage in all the sites, whilst rainfall reduction decreased evapotranspiration, runoff and drainage, especially at drier sites. In 2050, wheat yield would increase by 1?C10% under all climate change scenarios along the S?CN transect, except for the northernmost site (Dalby). Along the E?CW transect, the most obvious increase of wheat yields under all climate change scenarios occurred in cooler and wetter eastern sites (Yass and Young), with an average increase rate of 7%. The biggest loss occurred at the driest sites (Griffith and Swan Hill) under A1FI and B2 scenarios, ranging from ?5% to ?16%. In 2070, there would be an increased risk of yield loss in general, except for the cool and wet sites. Water use efficiency was simulated to increase at most of the study sites under all the climate change scenarios, except for the driest site. Yield variability would increase at drier sites (Ardlethan, Griffith and Swan Hill). Soil types would also impact on the response of wheat yield and water balance to future climate change.  相似文献   

13.
Crop growth models, used in climate change impact assessments to project production on a local scale, can obtain the daily weather information to drive them from models of the Earth's climate. General Circulation Models (GCMs), often used for this purpose, provide weather information for the entire globe but often cannot depict details of regional climates especially where complex topography plays an important role in weather patterns. The U.S. Pacific Northwest is an important wheat growing region where climate patterns are difficult to resolve with a coarse scale GCM. Here, we use the PNNL Regional Climate Model (RCM) which uses a sub-grid parameterization to resolve the complex topography and simulate meteorology to drive the Erosion Productivity Impact Calculator (EPIC) crop model. The climate scenarios were extracted from the PNNL-RCM baseline and 2 × CO2 simulationsfor each of sixteen 90 km2 grid cells of the RCM, with differentiation byelevation and without correction for climate biases. The dominant agricultural soil type and farm management practices were established for each grid cell. Using these climate and management data in EPIC, we simulated winter wheat production in eastern Washington for current climate conditions (baseline) and a 2 × CO2 `greenhouse' scenario of climate change.Dryland wheat yields for the baseline climate averaged 4.52 Mg ha–1 across the study region. Yields were zero at high elevations where temperatures were too low to allow the crops to mature. The highest yields (7.32 Mgha–1) occurred at intermediate elevations with sufficientprecipitation and mild temperatures. Mean yield of dryland winter wheat increased to 5.45 Mg ha–1 for the 2 × CO2 climate, which wasmarkedly warmer and wetter. Simulated yields of irrigated wheat were generally higher than dryland yields and followed the same pattern but were, of course, less sensitive to increases in precipitation. Increases in dryland and irrigated wheat yields were due, principally, to decreases in the frequency of temperature and water stress. This study shows that the elevation of a farm is a more important determinant of yield than farm location in eastern Washington and that climate changes would affect wheat yields at all farms in the study.  相似文献   

14.
To study impacts of climate variations on cropproduction, the growth models are used to simulateyields in present vs. changed climate conditions.Met&Roll is a four-variate (precipitation amount,solar radiation, minimum and maximum temperatures) stochasticweather generator used to supply synthetic dailyweather series for the crop growth model CERES-Maize.Three groups of experiments were conducted in thisstudy: (1) Validation of Met&Roll reveals some discrepanciesin the statistical structure of synthetic weatherseries, e.g., (i) the frequency of occurrence of longdry spells, extreme values of daily precipitationamount and variability of monthly means areunderestimated by the generator; (ii) correlations andlag-1 correlations among weather characteristicsexhibit a significant annual cycle not assumed by themodel. On the whole, the best fit of the observed andsynthetic weather series is experienced in summermonths. (2) The Wilcoxon test was employed to comparedistributions of maize yields simulated with use ofobserved vs. synthetic weather series. As nostatistically significant differences were detected,it is assumed that the generator imperfections inreproducing the statistical structure of weatherseries negligibly affect the model yields. (3) Thesensitivity of model yields to selectedcharacteristics of the daily weather series wasexamined. Emphasis was placed on the characteristicsnot addressed by typical GCM-based climate changescenarios: daily amplitude of temperature, persistenceof the weather series, shape of the distribution ofdaily precipitation amount, and frequency ofoccurrence of wet days. The results indicate that someof these characteristics may significantly affect cropyields and should therefore be considered in thedevelopment of climate change scenarios.  相似文献   

15.
Climate projections over the next two to four decades indicate that most of Australia’s wheat-belt is likely to become warmer and drier. Here we used a shire scale, dynamic stress-index model that accounts for the impacts of rainfall and temperature on wheat yield, and a range of climate change projections from global circulation models to spatially estimate yield changes assuming no adaptation and no CO2 fertilisation effects. We modelled five scenarios, a baseline climate (climatology, 1901–2007), and two emission scenarios (“low” and “high” CO2) for two time horizons, namely 2020 and 2050. The potential benefits from CO2 fertilisation were analysed separately using a point level functional simulation model. Irrespective of the emissions scenario, the 2020 projection showed negligible changes in the modelled yield relative to baseline climate, both using the shire or functional point scale models. For the 2050-high emissions scenario, changes in modelled yield relative to the baseline ranged from ?5 % to +6 % across most of Western Australia, parts of Victoria and southern New South Wales, and from ?5 to ?30 % in northern NSW, Queensland and the drier environments of Victoria, South Australia and in-land Western Australia. Taking into account CO2 fertilisation effects across a North–south transect through eastern Australia cancelled most of the yield reductions associated with increased temperatures and reduced rainfall by 2020, and attenuated the expected yield reductions by 2050.  相似文献   

16.
Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2°C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO2 doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO2 experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.  相似文献   

17.
A physically based conceptual framework is put forward that explains why an increase in heavy precipitation events should be a primary manifestation of the climate change that accompanies increases in greenhouse gases in the atmosphere. Increased concentrations of greenhouse gases in the atmosphere increase downwelling infrared radiation, and this global heating at the surface not only acts to increase temperatures but also increases evaporation which enhances the atmospheric moisture content. Consequently all weather systems, ranging from individual clouds and thunderstorms to extratropical cyclones, which feed on the available moisture through storm-scale moisture convergence, are likely to produce correspondingly enhanced precipitation rates. Increases in heavy rainfall at the expense of more moderate rainfall are the consequence along with increased runoff and risk of flooding. However, because of constraints in the surface energy budget, there are also implications for the frequency and/or efficiency of precipitation. It follows that increased attention should be given to trends in atmospheric moisture content, and datasets on hourly precipitation rates and frequency need to be developed and analyzed as well as total accumulation.  相似文献   

18.
This study reports the first assessment of the compounding effects of land-use change and greenhouse gas warming effects on our understanding of projections of future climate. An AGCM simulation of the potential impacts of tropical deforestation and greenhouse warming on climate, employing a version of NCAR Community Climate Model (CCM1-Oz), is presented. The joint impacts of tropical deforestation and greenhouse warming are assessed by an experiment in which removal of tropical rainforests is imposed into a greenhouse-warmed climate. Results show that the joint climate changes over tropical rainforest regions comprise large reductions in surface evapotranspiration (by about –180 mm yr–1) andprecipitation (by about –312 mm yr–1) over the Amazon Basin, along with anincrease of surface temperature by +3.0 K. Over Southeast Asia, similar but weaker changes are found in this study. Precipitation is decreased by –172 mmyr–1, together with the surface warming of 2.1 K. Over tropical Africa, changes in regional climate is much weaker and with some different features, such as the increase of precipitation by 25 mm yr–1. Energy budgetanalyses demonstrates that the large increase of surface temperature in the joint experiment is not solely produced by the increase of CO2concentration, but is a joint effect of the reduction of surface evaporation (due to deforestation) and the increase of downward atmospheric longwave radiation (due to the doubling of CO2 concentration). Furthermore, impactsof tropical deforestation on the greenhouse-warmed climate are estimated by comparing a pair of tropical deforestation simulations. It is found that in CCM1-Oz, deforestation has very similar impacts on greenhouse-warmed regional climates as on current climates over tropical rainforest regions. The extra-tropical climatic response to tropical deforestation is identified in both sets of tropical deforestation experiments. Statistically significant responses are seen in the large-scale atmospheric circulation such as changes in the velocity potential and vertically integrated kinetic and potential energy fields. Wave propagation patterns are identified in the large-scale circulation anomalies, which provides a mechanism for interpreting the model responses in the extra-tropics. In addition, this study suggests that land-use change such as tropical deforestation may affect projections of future climate.  相似文献   

19.
The potential impact of climate variability and climate change on agricultural production in the United States and Canada varies generally by latitude. Largest reductions are projected in southern crop areas due to increased temperatures and reduced water availability. A longer growing season and projected increases in CO2 may enhance crop yields in northern growing areas. Major factors in these scenarios analyzes are increased drought tendencies and more extreme weather events, both of which are detrimental to agriculture. Increasing competition for water between agriculture and non-agricultural users also focuses attention on water management issues. Agriculture also has impact on the greenhouse gas balance. Forests and soils are natural sinks for CO2. Removal of forests and changes in land use, associated with the conversion from rural to urban domains, alters these natural sinks. Agricultural livestock and rice cultivation are leading contributors to methane emission into the atmosphere. The application of fertilizers is also a significant contributor to nitrous oxide emission into the atmosphere. Thus, efficient management strategies in agriculture can play an important role in managing the sources and sinks of greenhouse gases. Forest and land management can be effective tools in mitigating the greenhouse effect.  相似文献   

20.
Grain maize yield in the main arable areas of the European Community (E.C.) was calculated with a simulation model, WOFOST, using historical weather data and average soil characteristics. The sensitivity of the model to individual weather variables was determined. Subsequent analyses were made using climate change scenarios with and without the direct effects of increased atmospheric CO2. The impact of crop management (sowing date, irrigation and cultivar type) in a changed climate was also assessed. Scenario climate change generally results in larger grain yields for the northern E.C., similar or slightly smaller yields for the central E.C. and considerably smaller yields for the southern E.C. The various climate change scenarios used appear to give considerably different changes in grain yield, both for each location and for the E.C. as a whole. Management analyses show that for both current and scenario climates the largest grain yield will be attained by varieties with an early start of grain filling, that average irrigation requirements to attain potential grain yield in the E.C. will increase with climate change but will decrease with both increased CO2 and climate change, and that sowing at both current and scenarios climate should occur as early as possible.The U.S. Government right to retain a nonexclusive, royalty-free licence in and to any copyright is acknowledged.  相似文献   

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