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1.
The crop model CERES-Barley was used to assess the impacts of increased concentration of atmospheric CO2 on growth and development of the most important spring cereal in Central and Western Europe, i.e., spring barley, and to examine possible adaptation strategies. Three experimental regions were selected to compare the climate change impacts in various climatic and pedological conditions. The analysis was based on multi-year crop model simulations run with daily weather series obtained by stochastic weather generator and included two yield levels: stressed yields and potential yields. Four climate change scenarios based on global climate models and representing 2 × CO2 climate were applied. Results: (i) The crop model is suitable for use in the given environment, e.g., the coefficient of determination between the simulated and experimental yields equals 0.88. (ii) The indirect effect related to changed weather conditions is mostly negative. Its magnitude ranges from ?19% to +5% for the four scenarios applied at the three regions. (iii) The magnitude of the direct effect of doubled CO2 on the stressed yields for the three test sites is 35–55% in the present climate and 25–65% in the 2 × CO2 climates. (iv) The stressed yields would increase in 2 × CO2 conditions by 13–52% when both direct and indirect effects were considered. (v) The impacts of doubled CO2 on potential yields are more uniform throughout the localities in comparison with the stressed yields. The magnitude of the indirect and direct effects ranges from ?1 to ?9% and from +31 to +33%, respectively. Superposition of both effects results in 19–30% increase of the potential yields. (vi) Application of the earlier planting date (up to 60 days) would result in 15–22% increase of the yields in 2 × CO2 conditions. (vii) Use of a cultivar with longer vegetation duration would bring 1.5% yield increase per one extra day of the vegetation season. (viii) The initial water content in the soil water profile proved to be one of the key elements determining the spring barley yield. It causes the yields to increase by 54–101 kg.ha?1 per 1% increase of the available soil water content on the sowing day.  相似文献   

2.
Agricultural systems models are essential tools to assess potential climate change (CC) impacts on crop production and help guide policy decisions. In this study, impacts of projected CC on dryland crop rotations of wheat-fallow (WF), wheat-corn-fallow (WCF), and wheat-corn-millet (WCM) in the U.S. Central Great Plains (Akron, Colorado) were simulated using the CERES V4.0 crop modules in RZWQM2. The CC scenarios for CO2, temperature and precipitation were based on a synthesis of Intergovernmental Panel on Climate Change (IPCC 2007) projections for Colorado. The CC for years 2025, 2050, 2075, and 2100 (CC projection years) were super-imposed on measured baseline climate data for 15–17 years collected during the long-term WF and WCF (1992–2008), and WCM (1994–2008) experiments at the location to provide inter-annual variability. For all the CC projection years, a decline in simulated wheat yield and an increase in actual transpiration were observed, but compared to the baseline these changes were not significant (p > 0.05) in all cases but one. However, corn and proso millet yields in all rotations and projection years declined significantly (p < 0.05), which resulted in decreased transpiration. Overall, the projected negative effects of rising temperatures on crop production dominated over any positive impacts of atmospheric CO2 increases in these dryland cropping systems. Simulated adaptation via changes in planting dates did not mitigate the yield losses of the crops significantly. However, the no-tillage maintained higher wheat yields than the conventional tillage in the WF rotation to year 2075. Possible effects of historical CO2 increases during the past century (from 300 to 380 ppm) on crop yields were also simulated using 96 years of measured climate data (1912–2008) at the location. On average the CO2 increase enhanced wheat yields by about 30%, and millet yields by about 17%, with no significant changes in corn yields.  相似文献   

3.
A crop-growth-simulation model based on SUCROS87 was used to study effects of temperature rise and increase of atmospheric CO2 concentration on wheat yields in several regions in Europe. The model simulated potential and water-limited crop production (growth with ample supply of nutrients and in the absence of damage by pests, diseases and weeds). Historic daily weather data from 13 sites in Western Europe were used as starting point.For potential production (optimal water) a 3 °C temperature rise led to a yield decline due to a shortening of the growing period on all locations. Doubling of the CO2 concentration caused an increase in yield of 40% due to higher assimilation rates. It was found that effects of higher temperature and higher CO2 concentration were nearly additive and the combination of both led to a yield increase of 1–2 ton ha-1. A very small CO2-temperature interaction was found: the effect of doubled CO2 concentration on crop yield was larger at higher temperatures. The inter-annual yield variability was hardly affected.When water was limiting crop-production effects of temperature rise and higher CO2 levels were different than for the potential production. Rise in temperature led to a smaller yield reduction, doubled CO2 concentration to a larger yield increase and combination of both led to a large yield increase (3 ton ha-1) in comparison with yields simulated for the present situation. Both rise in temperature and increase in the CO2 concentration reduced water requirements of the crop. Water shortages became smaller, leading to a reduction in inter-annual variability. It is concluded that when no major changes in precipitation pattern occur a climate change will not affect wheat yields since negative effects of higher temperatures are compensated by positive effects of CO2 enrichment.  相似文献   

4.
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   

5.
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   

6.
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   

7.
This paper analyzes the impact of climate, crop production technology, and atmospheric carbon dioxide (CO2) on current and future crop yields. The analysis of crop yields endeavors to advance the literature by estimating the effect of atmospheric CO2 on observed crop yields. This is done using an econometric model estimated over pooled historical data for 1950–2009 and data from the free air CO2 enrichment experiments. The main econometric findings are: 1) Yields of C3 crops (soybeans, cotton, and wheat) directly respond to the elevated CO2, while yields of C4 crops (corn and sorghum) do not, but they are found to indirectly benefit from elevated CO2 in times and places of drought stress; 2) The effect of technological progress on mean yields is non-linear; 3) Ignoring atmospheric CO2 in an econometric model of crop yield likely leads to overestimates of the pure effects of technological progress on crop yields of about 51, 15, 17, 9, and 1 % of observed yield gain for cotton, soybeans, wheat, corn and sorghum, respectively; 4) Average climate conditions and climate variability contribute in a statistically significant way to average crop yields and their variability; and 5) The effect of CO2 fertilization generally outweighs the effect of climate change on mean crop yields in many regions resulting in an increase of 7–22, 4–47, 5–26, 65–96, and 3–35 % for yields of corn, sorghum, soybeans, cotton, and wheat, respectively.  相似文献   

8.
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   

9.
Anthropogenic climate change will continue long after anthropogenic CO2 emissions cease. Atmospheric CO2, global warming and ocean circulation will approach equilibrium on the millennial timescale, whereas thermal expansion of the ocean, ice sheet melt and their contributions to sea level rise are unlikely to be complete. Atmospheric CO2 in year 3000 depends non-linearly on the total amount of CO2 emitted and is very likely to exceed the present level of ∼380 ppmv. CO2 is doubled for ∼2500 GtC emitted, quadrupled if all ∼5000 GtC of conventional fossil fuel resources are emitted, and increases by a factor of ∼32 if a further 20,000 GtC of exotic fossil fuel resources are emitted. Global warming in year 3000 will also depend on climate sensitivity to doubling CO2, which is most probably ∼3 ∘C but highly uncertain. Thermal expansion will contribute 0.5–2 m to millennial sea level rise for each doubling of CO2. The Greenland ice sheet could melt completely within the millennium under > 8×CO2, adding a further ∼7 m to sea level. The rate of melt depends on the magnitude of forcing above a regional warming threshold of 1–3 ∘C. The West Antarctic ice sheet could be threatened by 4–10 ∘C local warming, and its potential contribution to millennial sea level rise exceeds current maximum estimates of ∼1 m. The fate of the ocean thermohaline circulation may depend on the rate as well as the magnitude of forcing.  相似文献   

10.
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   

11.
Summary The qualitative agreement of two climate models, HADCM2 and ECHAM3, on the response of surface climate to anthropogenic climate forcing in the period 2020 – 2049 is studied. Special attention is paid to the role of internal climate variability as a source of intermodel disagreement. After illustrating the methods in an intermodel comparison of simulated changes in June–August mean precipitation, some global statistics are presented. Excluding surface air temperature, the four-season mean proportion of areas in which the two models agree on the sign of the climatic response is only 53 – 60% both for increases in CO2 alone and for increases in CO2 together with direct radiative forcing by sulphate aerosols, but somewhat larger, 59 – 70% for the separate aerosol effect. In areas where the response is strong (at least twice the standard error associated with internal variability) in both models, the agreement is better and the contrast between the different forcings becomes more marked. The proportion of agreement in such areas is 57 – 75% for the response to increases in CO2 alone, 64 – 84% for the response to combined CO2 and aerosol forcing, and as high as 88 – 94% for the separate aerosol effect. The relatively good intermodel agreement for aerosol-induced climate changes is suggested to be associated with the uneven horizontal distribution of aerosol forcing. Received December 2, 1998 Revised May 5, 1999  相似文献   

12.
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   

13.
Climate change has the potential to be a source of increased variability if crops are more frequently exposed to damaging weather conditions. Yield variability could respond to a shift in the frequency of extreme events to which crops are susceptible, or if weather becomes more variable. Here we focus on the United States, which produces about 40% of the world’s maize, much of it in areas that are expected to see increased interannual variability in temperature. We combine a statistical crop model based on historical climate and yield data for 1950–2005 with temperature and precipitation projections from 15 different global circulation models. Holding current growing area constant, aggregate yields are projected to decrease by an average of 18% by 2030–2050 relative to 1980–2000 while the coefficient of variation of yield increases by an average of 47%. Projections from 13 out of 15 climate models result in an aggregate increase in national yield coefficient of variation, indicating that maize yields are likely to become more volatile in this key growing region without effective adaptation responses. Rising CO2 could partially dampen this increase in variability through improved water use efficiency in dry years, but we expect any interactions between CO2 and temperature or precipitation to have little effect on mean yield changes.  相似文献   

14.
A crop growth simulation model based on SUCROS87 was constructed to study the effects of temperature rise and increase of the atmospheric CO2 concentration on spring wheat yields in The Netherlands. The model simulated potential production (limited by crop characteristics, temperature and radiation but without any stress from water or nutrient shortages or pests, diseases and weeds) and water-limited production in which growth is also limited by water shortage. The model was validated for the present climatic conditions. When daily weather data from a nearby station were used, the model was well able to simulate yields obtained in field experiments.Effects of several combinations of temperature rise and atmospheric CO2 concentration on simulated yields were studied. A temperature rise resulted in a reduction in simulated yield due to shortening of the growing period. Large variations existed in the magnitude of this reduction. Increases in atmospheric CO2 concentration led to yield increases due to higher assimilation rates and to increase of the water use efficiency. Combination of temperature rise and higher CO2 concentration resulted in small yield increases in years in which water was not limiting growth and large yield increases in dry years.Change of variety or of sowing date could not reduce the negative effects of temperature rise on simulated yields.  相似文献   

15.
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   

16.
Rice is the staple food in China, and the country’s enlarging population puts increasing pressure on its rice production as well as on that of the world. In this study, we estimate the impact of climate change, CO2 fertilization, crop adaptation and the interactions of these three factors on the rice yields of China using model simulation with four hypothetical scenarios. According to the results of the model simulation, the rice yields without CO2 fertilization are predicted to decrease by 3.3 % in the 2040s. Considering a constant rice-growing season (GS), the rice yields are predicted to increase by 3.2 %. When the effect of CO2 fertilization is integrated into the Agro-C model, the expected rice yields increase by 20.9 %. When constant GS and CO2 fertilization are both integrated into the model, the predicted rice yield increases by 28.6 %. In summary, the rice yields in China are predicted to decrease in the 2040s by 0.22 t/ha due to climate change, to increase by 0.44 t/ha due to a constant GS and to increase by 1.65 t/ha due to CO2 fertilization. The benefits of crop adaptation would completely offset the negative impact of climate change. In the future, the most of the positive effects of climate change are expected to occur in northeastern and northwestern China, and the expansion of rice cultivation in northeastern China should further enhance the stability of rice production in China.  相似文献   

17.
Article 2 of the United Nations Framework Convention on Climate Change (UNFCCC) calls for stabilization of greenhouse gas (GHG) concentrations at levels that prevent dangerous anthropogenic interference (DAI) in the climate system. However, some of the recent policy literature has focused on dangerous climatic change (DCC) rather than on DAI. DAI is a set of increases in GHGs concentrations that has a non-negligible possibility of provoking changes in climate that in turn have a non-negligible possibility of causing unacceptable harm, including harm to one or more of ecosystems, food production systems, and sustainable socio-economic systems, whereas DCC is a change of climate that has actually occurred or is assumed to occur and that has a non-negligible possibility of causing unacceptable harm. If the goal of climate policy is to prevent DAI, then the determination of allowable GHG concentrations requires three inputs: the probability distribution function (pdf) for climate sensitivity, the pdf for the temperature change at which significant harm occurs, and the allowed probability (“risk”) of incurring harm previously deemed to be unacceptable. If the goal of climate policy is to prevent DCC, then one must know what the correct climate sensitivity is (along with the harm pdf and risk tolerance) in order to determine allowable GHG concentrations. DAI from elevated atmospheric CO2 also arises through its impact on ocean chemistry as the ocean absorbs CO2. The primary chemical impact is a reduction in the degree of supersaturation of ocean water with respect to calcium carbonate, the structural building material for coral and for calcareous phytoplankton at the base of the marine food chain. Here, the probability of significant harm (in particular, impacts violating the subsidiary conditions in Article 2 of the UNFCCC) is computed as a function of the ratio of total GHG radiative forcing to the radiative forcing for a CO2 doubling, using two alternative pdfs for climate sensitivity and three alternative pdfs for the harm temperature threshold. The allowable radiative forcing ratio depends on the probability of significant harm that is tolerated, and can be translated into allowable CO2 concentrations given some assumption concerning the future change in total non-CO2 GHG radiative forcing. If future non-CO2 GHG forcing is reduced to half of the present non-CO2 GHG forcing, then the allowable CO2 concentration is 290–430 ppmv for a 10% risk tolerance (depending on the chosen pdfs) and 300–500 ppmv for a 25% risk tolerance (assuming a pre-industrial CO2 concentration of 280 ppmv). For future non-CO2 GHG forcing frozen at the present value, and for a 10% risk threshold, the allowable CO2 concentration is 257–384 ppmv. The implications of these results are that (1) emissions of GHGs need to be reduced as quickly as possible, not in order to comply with the UNFCCC, but in order to minimize the extent and duration of non-compliance; (2) we do not have the luxury of trading off reductions in emissions of non-CO2 GHGs against smaller reductions in CO2 emissions, and (3) preparations should begin soon for the creation of negative CO2 emissions through the sequestration of biomass carbon.  相似文献   

18.
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   

19.
 The impact of CO2-induced global warming on the intensities of strong hurricanes is investigated using the GFDL regional high-resolution hurricane prediction system. The large-scale initial conditions and boundary conditions for the regional model experiments, including SSTs, are derived from control and transient CO2 increase experiments with the GFDL R30-resolution global coupled climate model. In a case study approach, 51 northwest Pacific storm cases derived from the global model under present-day climate conditions are simulated with the regional model, along with 51 storm cases for high CO2 conditions. For each case, the regional model is integrated forward for five days without ocean coupling. The high CO2 storms, with SSTs warmer by about 2.2 °C on average and higher environmental convective available potential energy (CAPE), are more intense than the control storms by about 3–7 m/s (5%–11%) for surface wind speed and 7 to 24 hPa for central surface pressure. The simulated intensity increases are statistically significant according to most of the statistical tests conducted and are robust to changes in storm initialization methods. Near-storm precipitation is 28% greater in the high CO2 sample. In terms of storm tracks, the high CO2 sample is quite similar to the control. The mean radius of hurricane force winds is 2 to 3% greater for the composite high CO2 storm than for the control, and the high CO2 storms penetrate slightly higher into the upper troposphere. More idealized experiments were also performed in which an initial storm disturbance was embedded in highly simplified flow fields using time mean temperature and moisture conditions from the global climate model. These idealized experiments support the case study results and suggest that, in terms of thermodynamic influences, the results for the NW Pacific basin are qualitatively applicable to other tropical storm basins. Received: 20 July 1998/Accepted: 24 December 1998  相似文献   

20.
A land-surface model (LSM) is coupled with a large-eddy simulation (LES) model to investigate the vegetation-atmosphere exchange of heat, water vapour, and carbon dioxide (CO2) in heterogeneous landscapes. The dissimilarity of scalar transport in the lower convective boundary layer is quantified in several ways: eddy diffusivity, spatial structure of the scalar fields, and spatial and temporal variations in the surface fluxes of these scalars. The results show that eddy diffusivities differ among the three scalars, by up to 10–12%, in the surface layer; the difference is partly attributed to the influence of top-down diffusion. The turbulence-organized structures of CO2 bear more resemblance to those of water vapour than those of the potential temperature. The surface fluxes when coupled with the flow aloft show large spatial variations even with perfectly homogeneous surface conditions and constant solar radiation forcing across the horizontal simulation domain. In general, the surface sensible heat flux shows the greatest spatial and temporal variations, and the CO2 flux the least. Furthermore, our results show that the one-dimensional land-surface model scheme underestimates the surface heat flux by 3–8% and overestimates the water vapour and CO2 fluxes by 2–8% and 1–9%, respectively, as compared to the flux simulated with the coupled LES-LSM.  相似文献   

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