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1.
A numerical stream temperature model that accounts for kinematic wave flow routing, and heat exchange fluxes between stream water and the atmosphere, and stream water and the stream bed is developed and calibrated to a data-set from the Lower Madison River, Montana, USA. Future climate scenarios were applied to the model through changes to the atmospheric input data based on air temperature and solar radiation output from four General Circulation Models (GCM) for the region under atmospheric CO2 concentration doubling. The purpose of this study was to quantify potential climate change impacts on water temperature for the Lower Madison River, and to assess possible impacts to aquatic ecosystems. Because water temperature is a critical component of fish habitat, this information could be of use in future planning operations of current reservoirs. We applied air temperature changes to diurnal temperatures, daytime temperatures only, and nighttime temperatures only, to assess the impacts of variable potential warming trends. The results suggest that, given the potential climatic changes, the aquatic ecosystem downstream of Ennis Lake will experience higher water temperatures, possibly leading to increased stress on fish populations.Daytime warming produced the largest increases in downstream water temperature.  相似文献   

2.
A deterministic heat transport model was developed to calculate stream water temperatures downstream of reservoir outlets (tailwaters) and groundwater sources. The model calculates heat exchange between the atmosphere, the water and the sediments and is driven by climate and stream hydrologic parameters. Past and projected climate conditions were used as input to the stream water temperature model. To produce a projected future weather scenario, output from the Columbia University Goddard Institute for Space Studies (GISS) global circulation model (GCM) for a doubling of atmospheric CO2 were used to adjust past (1955–1979) weather parameters. Stream reach lengths, within which water temperatures are suitable for survival or good growth of 28 fish species, were determined for four selected streams. Several alternative upstream inflow conditions were chosen: Discharges from surface (epilimnion) and bottom (hypolimnion) outlets of reservoirs, and two groundwater inflow scenarios. By applying water temperature criteria for fish survival and good growth (Stefanet al., 1993) to simulated stream temperatures, it was possible to estimate stream lengths with suitable habitat. When simulated suitable habitat was compared to actual fish observations, good agreement was found. For projected climate change, the simulations showed how much of the available stream habitat would be lost. In the examples presented the effect of cold hypolimnetic water release from a reservoir or groundwater discharges is felt as far as 48 km (30 miles) downstream from its source, especially in smaller shaded streams. The impact of climate change on stream temperatures below dams is more pronounced when the water release is from the epilimnion (reservoir surface) rather than the hypolimnion (deep water). Examples used for this study show elimination of coldwater habitat for rainbow trout when the upstream release is from the surface of a reservoir, but only reductions of coldwater habitat when the upstream release is from a reservoir hypolimnion.  相似文献   

3.
Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO2 and 1 × CO2 GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO2 concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.  相似文献   

4.
C. Tague  L. Seaby  A. Hope 《Climatic change》2009,93(1-2):137-155
Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO2 for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs.  相似文献   

5.
This study uses empirical agricultural impact models to compare the U.S. climate change predictions of 16 General Circulation Models (GCMs). The impact analysis provides a policy-relevant index by which to judge complex climate predictions. National aggregate impacts vary widely across the 16 GCMs because of varying regional and seasonal patterns of predicted climate change. Examining the predicted impacts from the full set of GCMs reveals that the seasonal detail in the GCM predictions is so noisy that it is not significantly different from a constant annual change. However, a consistent regional pattern does emerge across the set of models. Nonetheless, aggregating climate change across seasons and regions within the United States, using a national-annual climate change provides a reasonable and efficient approximation to the expected impact predicted by the 16 GCM models.  相似文献   

6.
The aim of this paper is to report on the development of regional climate change scenarios for Kazakhstan as the result of increasing of CO2 concentration in the global atmosphere. These scenarios are used in the assessment of climate change impacts on the agricultural, forest and water resources of Kazakhstan. Climate change scenarios for Kazakhstan to assess both long-term (2× CO2 in 2075) and short-term (2000, 2010 and 2030) impacts were prepared. The climate conditions under increasing CO2 concentration were estimated from three General Circulation Models (GCM) outputs: the model of the Canadian Climate Center Model (CCCM), the model of the Geophysical Fluid Dynamics Laboratory (GFDL) and the 1% transient version of the GFDL model (GFDL-T). The near-term climate scenarios were obtained using the probabilistic forecast model (PFM) to the year 2010 and the results of GFDL-T for years 2000 and 2030. A baseline scenario representing the current climate conditions based on observations from 1951 to 1980 was developed. The assessment of climate change in Kazakhstan based on the analysis of 100-years observations is given too. As a result of comparisons of the current climate (based on observed climate) the 1× CO2 output from GCMs showed that the GFDL model best matches the observed climate. The GFDL model suggests that the minimum increase in temperature is expected in winter, when most of the territory is expected to have temperatures 2.3–4.5 °C higher. The maximum (4.3 to 8.2 °C) is expected to be in spring. CCCM scenario estimates an extreme worming above 11 °C in spring months. GFDL-T outputs provide an intermediate scenario.  相似文献   

7.
The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO2 concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO2 concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.  相似文献   

8.
There is increasing concern that avoiding climate change impacts will require proactive adaptation, particularly for infrastructure systems with long lifespans. However, one challenge in adaptation is the uncertainty surrounding climate change projections generated by general circulation models (GCMs). This uncertainty has been addressed in different ways. For example, some researchers use ensembles of GCMs to generate probabilistic climate change projections, but these projections can be highly sensitive to assumptions about model independence and weighting schemes. Because of these issues, others argue that robustness-based approaches to climate adaptation are more appropriate, since they do not rely on a precise probabilistic representation of uncertainty. In this research, we present a new approach for characterizing climate change risks that leverages robust decision frameworks and probabilistic GCM ensembles. The scenario discovery process is used to search across a multi-dimensional space and identify climate scenarios most associated with system failure, and a Bayesian statistical model informed by GCM projections is then developed to estimate the probability of those scenarios. This provides an important advancement in that it can incorporate decision-relevant climate variables beyond mean temperature and precipitation and account for uncertainty in probabilistic estimates in a straightforward way. We also suggest several advancements building on prior approaches to Bayesian modeling of climate change projections to make them more broadly applicable. We demonstrate the methodology using proposed water resources infrastructure in Lake Tana, Ethiopia, where GCM disagreement on changes in future rainfall presents a major challenge for infrastructure planning.  相似文献   

9.
Assessing future climate and its potential implications on river flows is a key challenge facing water resource planners. Sound, scientifically-based advice to decision makers also needs to incorporate information on the uncertainty in the results. Moreover, existing bias in the reproduction of the ‘current’ (or baseline) river flow regime is likely to transfer to the simulations of flow in future time horizons, and it is thus critical to undertake baseline flow assessment while undertaking future impacts studies. This paper investigates the three main sources of uncertainty surrounding climate change impact studies on river flows: uncertainty in GCMs, in downscaling techniques and in hydrological modelling. The study looked at four British catchments’ flow series simulated by a lumped conceptual rainfall–runoff model with observed and GCM-derived rainfall series representative of the baseline time horizon (1961–1990). A block-resample technique was used to assess climate variability, either from observed records (natural variability) or reproduced by GCMs. Variations in mean monthly flows due to hydrological model uncertainty from different model structures or model parameters were also evaluated. Three GCMs (HadCM3, CCGCM2, and CSIRO-mk2) and two downscaling techniques (SDSM and HadRM3) were considered. Results showed that for all four catchments, GCM uncertainty is generally larger than downscaling uncertainty, and both are consistently greater than uncertainty from hydrological modelling or natural variability. No GCM or downscaling technique was found to be significantly better or to have a systematic bias smaller than the others. This highlights the need to consider more than one GCM and downscaling technique in impact studies, and to assess the bias they introduce when modelling river flows.  相似文献   

10.
Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data. Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.  相似文献   

11.
Simulated impacts of global and regional climate change, induced by an enhanced greenhouse effect and by Amazonian deforestation, on the phenology and yield of two grain corn cultivars in Venezuela (CENIAP PB-8 and OBREGON) are reported. Three sites were selected:Turén, Barinas andYaritagua, representing two important agricultural regions in the country. The CERES-Maize model, a mechanistic process-based model, in theDecision Support System for Agrotechnology Transfer (DSSAT) was used for the crop simulations. These simulations assume non-limiting nutrients, no pest damage and no damage from excess water; therefore, the results indicate only the difference between baseline and perturbed climatic conditions, when other conditions remain the same. Four greenhouse-induced global climate change scenarios, covering different sensitivity levels, and one deforestation-induced regional climate change scenario were used. The greenhouse scenarios assume increased air temperature, increased rainfall and decreased incoming solar radiation, as derived from atmospheric GCMs for doubled CO2 conditions. The deforestation scenarios assume increased air temperature, increased incoming solar radiation and decreased rainfall, as predicted by coupled atmosphere-biosphere models for extensive deforestation of a portion of the Amazon basin. Two baseline climate years for each site were selected, one year with average precipitation and another with lower than average rainfall. Scenarios associated with the greenhouse effect cause a decrease in yield of both cultivars at all three sites, while the deforestation scenarios produce small changes. Sensitivity tests revealed the reasons for these responses. Increasing temperatures, especially daily maximum temperatures, reduce yield by reducing the duration of the phenological phases of both cultivars, as expected from CERES-Maize. The reduction of the duration of the kernel filling phase has the largest effect on yield. Increases of precipitation associated with greenhouse warming have no effects on yield, because these sites already have adequate precipitation; however, the crop model used here does not simulate potential negative effects of excess water, which could have important consequences in terms of soil erosion and nutrient leaching. Increases in solar radiation increased yields, according to the non-saturating light response of the photosynthesis rate of a C4 plant like corn, compensating for reduced yields from increased temperatures in deforestation scenarios. In the greenhouse scenarios, reduced insolation (due to increased cloud cover) and increased temperatures combine to reduce yields; a combination of temperature increase with a reduction in solar radiation produces fewer and lighter kernels.A report of thePAN-EARTH Project, Venezuela Case Study.  相似文献   

12.
One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.  相似文献   

13.
The FORSKA2 patch model was used to simulate responses of forest biomass and species composition to four GCM projections of climate change at 11 locations along a transect oriented northeast-southwest across the boreal zone of central Canada. In agreement with earlier results, FORSKA2 produced estimates of present-day biomass accumulation and functional types very consistent with local inventory data. Simulated responses to the four GCM scenarios of climate change produced different results. The GFDL scenario consistently reduced total biomass accumulation compared to present-day conditions, whereas the other three GCMs produced overall increases. In the north, where ecosystem productivity is thought to be limited by low temperature, changes in steady-state biomass accumulation and species composition were relatively minor. In the south, where productivity is probably limited by summer water deficits, the GCM scenarios resulted in larger absolute changes, with generally large increases under GISS, and OSU and generally smaller increases under UKMO. Pronounced changes in species composition were not evident in most simulations, with the exception that warmer winter temperatures evidently allowed invasion by species currently excluded through intolerance to winter minima.  相似文献   

14.
This paper investigates the uncertainty in the impact of climate change on flood frequency in England, through the use of continuous simulation of river flows. Six different sources of uncertainty are discussed: future greenhouse gas emissions; Global Climate Model (GCM) structure; downscaling from GCMs (including Regional Climate Model structure); hydrological model structure; hydrological model parameters and the internal variability of the climate system (sampled by applying different GCM initial conditions). These sources of uncertainty are demonstrated (separately) for two example catchments in England, by propagation through to flood frequency impact. The results suggest that uncertainty from GCM structure is by far the largest source of uncertainty. However, this is due to the extremely large increases in winter rainfall predicted by one of the five GCMs used. Other sources of uncertainty become more significant if the results from this GCM are omitted, although uncertainty from sources relating to modelling of the future climate is generally still larger than that relating to emissions or hydrological modelling. It is also shown that understanding current and future natural variability is critical in assessing the importance of climate change impacts on hydrology.  相似文献   

15.
Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.  相似文献   

16.
A deterministic, one-dimensional model is presented to simulate daily water temperature profiles and associated ice and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface area (As), maximum depth (HMAX), and Secchi depth (zs), the latter, used as a measure of light attenuation and trophic state. The model is driven by daily weather data and operates year-round over multiple years. The model has been tested with extensive data (over 5,000 temperature points). Standard error between simulated and measured water temperatures is 1.4°C in the open water season and 0.5°C in the ice cover season. The model is applied to simulate the sensitivity of Minnesota lake water temperature characteristics to climate change. The projected climate changes due to a doubling of atmospheric CO2 are obtained from the output of the Canadian Climate Center General Circulation Model (CCC GCM) and the Goddard Institute of Space Studies General Circulation Model (GISS GCM). Simulated lake temperature characteristics have been plotted in a coordinate system with a lake geometry ratio (A s 0.25 /HMAX) on one axis and Secchi depth on the other. The lake geometry ratio expresses a lake's susceptibility to stratification. By interpolation, the sensitivity of lake temperature characteristics to changes of water depth and Secchi depth under the projected climate scenarios can therefore be obtained. Selected lake temperature characteristics simulated with past climate conditions (1961–1979) and with a projected 2 × CO2 climate scenario as input are presented herein in graphical form. The simulation results show that under the 2 × CO2 climate scenario ice formation is delayed and ice cover period is shortened. These changes cause water temperature modifications throughout the year.  相似文献   

17.
The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.  相似文献   

18.
 Changes in land surface driving variables, predicted by GCM transient climate change experiments, are confirmed to exhibit linearity in the global mean land temperature anomaly, ΔT l . The associated constants of proportionality retain spatial and seasonal characteristics of the GCM output, whilst ΔT l is related to radiative forcing anomalies. The resultant analogue model is shown to be robust between GCM runs and as such provides a computationally efficient technique of extending existing GCM experiments to a large range of climate change scenarios. As an example impacts study, the analogue model is used to drive a terrestrial ecosystem model, and predicted changes in terrestrial carbon are found to be similar to those when using GCM anomalies directly. Received: 4 January 1999 / Accepted: 11 December 1999  相似文献   

19.
This paper describes the regional climate change scenarios that are recommended for use in the U.S. Country Studies Program (CSP) and evaluates how well four general circulation models (GCMs) simulate current climate over Europe. Under the umbrella of the CSP, 50 countries with varying skills and experience in developing climate change scenarios are assessing vulnerability and adaptation. We considered the use of general circulation models, analogue warm periods, and incremental scenarios as the basis for creating climate change scenarios. We recommended that participants in the CSP use a combination of GCM based scenarios and incremental scenarios. The GCMs, in spite of their many deficiencies, are the best source of information about regional climate change. Incremental scenarios help identify sensitivities to changes in a particular meteorological variable and ensure that a wide range of regional climate change scenarios are considered. We recommend using the period 1951–1980 as baseline climate because it was a relatively stable climate period globally. Average monthly changes from the GCMs and the incremental changes in climate variables are combined with the historical record to produce scenarios. The scenarios do not consider changes in interannual, daily, or subgrid scale variability. Countries participating in the Country Studies Program were encouraged to compare the GCMs' estimates of current climate with actual long-term climate means. In this paper, we compare output of four GCMs (CCCM, GFDL, UKMO, and GISS) with observed climate over Europe by performing a spatial correlation analysis for temperature and precipitation, by statistically comparing spatial patterns averaged climate estimates from the GCMs with observed climate, and by examining how well the models estimate seasonal patterns of temperature and precipitation. In Europe, the GISS and CCCM models best simulate current temperature, whereas the GISS and UK89 models, and the CCCM model, best simulate precipitation in defined northern and southern regions, respectively.  相似文献   

20.
Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040–2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21 Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins’ hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.  相似文献   

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