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1.
Biomes computed from simulated climatologies   总被引：4，自引：0，他引：4  
The biome model of Prentice et al. (1992a) is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fur Meteorologie. This study is undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a difference in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to failures in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are seen for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced C02 concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting changes in vegetation patterns due to a rapid climate change, the latter simulation has to be taken as a prediction of changes in conditions favourable for the existence of certain biomes, not as a prediction of a future distribution of biomes.[/ab]  相似文献   

2.
The participation of different vegetation types within the physical climate system is investigated using a coupled atmosphere-biosphere model, CCM3-IBIS. We analyze the effects that six different vegetation biomes (tropical, boreal, and temperate forests, savanna, grassland and steppe, and shrubland/tundra) have on the climate through their role in modulating the biophysical exchanges of energy, water, and momentum between the land-surface and the atmosphere. Using CCM3-IBIS we completely remove the vegetation cover of a particular biome and compare it to a control simulation where the biome is present, thereby isolating the climatic effects of each biome. Results from the tropical and boreal forest removal simulations are in agreement with previous studies while the other simulations provide new evidence as to their contribution in forcing the climate. Removal of the temperate forest vegetation exhibits behavior characteristic of both the tropical and boreal simulations with cooling during winter and spring due to an increase in the surface albedo and warming during the summer caused by a reduction in latent cooling. Removal of the savanna vegetation exhibits behavior much like the tropical forest simulation while removal of the grassland and steppe vegetation has the largest effect over the central United States with warming and drying of the atmosphere in summer. The largest climatic effect of shrubland and tundra vegetation removal occurs in DJF in Australia and central Siberia and is due to reduced latent cooling and enhanced cold air advection, respectively. Our results show that removal of the boreal forest yields the largest temperature signal globally when either including or excluding the areas of forest removal. Globally, precipitation is most affected by removal of the savanna vegetation when including the areas of vegetation removal, while removal of the tropical forest most influences the global precipitation excluding the areas of vegetation removal.  相似文献   

3.
The use of one-way coupling of an equilibrium-response vegetation, or biome, model with atmospheric circulation models is critically assessed. Global biome patterns from various, equally likely numerical realisations of present-day climate are compared. It has been found that the changes in global biome patterns to be expected from interdecadal variability in the atmosphere affect 9–12% of the continental surface (Antarctica excluded). There is no unique difference pattern, although changes are mainly induced by the variability of annual moisture availability and, to a lesser extent, by winter temperatures. This variability of biome patterns reflects the uncertainty in the estimate of equilibrium vegetation patterns from finite time interval climatologies. Changes in biome distributions between present-day climate and anomaly climate, the latter induced by an increase in sea-surface temperatures and atmospheric CO2, are larger than and different in kind from the changes due to interdecadal variability. Roughly 30% of the land surface is affected by these changes. It appears that the strongest and most significant signal is seen for boreal biomes which can be attributed to an increase in near surface temperatures.  相似文献   

4.
Terrestrial ecosystems provide a range of important services to humans, including global and regional climate regulation. These services arise from natural ecosystem functioning as governed by drivers such as climate, atmospheric carbon dioxide mixing ratio, and land-use change. From the perspective of carbon sequestration, numerous studies have assessed trends and projections of the past and future terrestrial carbon cycle, but links to the ecosystem service concept have been hindered by the lack of appropriate quantitative service metrics. The recently introduced concept of the Greenhouse Gas Value (GHGV) accounts for the land-atmosphere exchanges of multiple greenhouse gases by taking into consideration the associated ecosystem pool sizes, annual exchange fluxes and probable effects of natural disturbance in a time-sensitive manner.We use here GHGV as an indicator for the carbon sequestration aspects of the climate regulation ecosystem service, and quantify it at global scale using the LPJ-GUESS dynamic global vegetation model. The response of ecosystem dynamics and ecosystem state variables to trends in climate, atmospheric carbon dioxide levels and land use simulated by LPJ-GUESS are used to calculate the contribution of carbon dioxide to GHGV. We evaluate global variations in GHGV over historical periods and for future scenarios (1850–2100) on a biome basis following a high and a low emission scenario.GHGV is found to vary substantially depending on the biogeochemical processes represented in LPJ-GUESS (e.g. carbon–nitrogen coupling, representation of land use). The consideration of disturbance events that occur as part of an ecosystem's natural dynamics is crucial for realistic GHGV assessments; their omission results in unrealistically high GHGV. By considering the biome-specific response to current climate and land use, and their projections for the future, we highlight the importance of all forest biomes for maintaining and increasing biogeochemical carbon sequestration. Under future climate and carbon dioxide levels following a high emission scenario GHGV values are projected to increase, especially so in tropical forests, but land-use change (e.g. deforestation) opposes this trend. The GHGV of ecosystems, especially when assessed over large areas, is an appropriate metric to assess the contribution of different greenhouse gases to climate and forms a basis for the monetary valuation of the climate regulation service ecosystems provide.  相似文献   

5.
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   

6.
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   

7.
The interest in the national levels of the terrestrial carbon sink and its spatial and temporal variability with the climate and CO2 concentrations has been increasing. How the climate and the increasing atmospheric CO2 concentrations in the last century affect the carbon storage in continental China was investigated in this study by using the Modified Sheffield Dynamic Global Vegetation Model (M-SDGVM). The estimates of the M-SDGVM indicated that during the past 100 years a combination of increasing CO2 with historical temperature and precipitation variability in continental China have caused the total vegetation carbon storage to increase by 2.04 Pg C, with 2.07 Pg C gained in the vegetation biomass but 0.03 Pg C lost from the organic soil carbon matter. The increasing CO2 concentration in the 20th century is primarily responsible for the increase of the total potential vegetation carbon. These factorial experiments show that temperature variability alone decreases the total carbon storage by 1.36 Pg C and precipitation variability alone causes a loss of 1.99 Pg C. The effect of the increasing CO2 concentration alone increased the total carbon storage in the potential vegetation of China by 3.22 Pg C over the past 100 years. With the changing of the climate, the CO2 fertilization on China's ecosystems is the result of the enhanced net biome production (NBP), which is caused by a greater stimulation of the gross primary production (GPP) than the total soil-vegetation respiration. Our study also shows notable interannual and decadal variations in the net carbon exchange between the atmosphere and terrestrial ecosystems in China due to the historical climate variability.  相似文献   

8.
陆地生态系统模型及其与气候模式耦合的回顾   总被引：5，自引：2，他引：3  
陆地生态系统和气候系统通过能量通量、水汽通量、物质交换相互影响、作用。作者对陆地生态系统模型及其与气候模式耦合的研究进行综述和讨论,总结了当代5类主要全球陆地生态系统模型,即生物地理模型、生物地球化学模型、森林林窗模型、陆面生物圈模型和动态全球植被模型,以及它们与气候模式耦合的研究进展。阐述了动态全球植被模型及其与气候模式耦合研究在全球变化研究的重要作用。最后,对未来模拟研究的方向进行了分析。  相似文献   

9.
Impacts of climate change on vegetation are often summarized in biome maps, representing the potential natural vegetation class for each cell of a grid under current and changed climate. The amount of change between two biome maps is usually measured by the fraction of cells that change class, or by the kappa statistic. Neither measure takes account of varying structural and floristic dissimilarity among biomes. An attribute-based measure of dissimilarity (V) between vegetation classes is therefore introduced. V is based on (a) the relative importance of different plant life forms (e.g. tree, grass) in each class, and (b) a series of attributes (e.g. evergreen-deciduous, tropical-nontropical) of each life form with a weight for each attribute. V is implemented here for the most used biome model, BIOME 1 (Prentice, I. C. et al., 1992). Multidimensional scaling of pairwise V values verifies that the suggested importance values and attribute weights lead to a reasonable pattern of dissimilarities among biomes. Dissimilarity between two maps (V) is obtained by area-weighted averaging of V over the model grid. Using V, present global biome distribution from climatology is compared with anomaly-based scenarios for a doubling of atmospheric CO2 concentration (2 × CO2), and for extreme glacial and interglacial conditions. All scenarios are obtained from equilibrium simulations with an atmospheric general circulation model coupled to a mixed-layer ocean model. The 2 × CO2 simulations are the widely used OSU and GFDL runs from the 1980's, representing models with low and high climate sensitivity, respectively. The palaeoclimate simulations were made with CCM1, with sensitivity similar to GFDL. V values for the comparisons of 2 × CO2 with present climate are similar to values for the comparisons of the last interglacial and mid-Holocene with present climate. However, the two simulated 2 × CO2 cases are much more like each other than they are to the simulated interglacial cases. The largest V values were between the last glacial maximum and all other cases, including the present. These examples illustrate the potential of V in comparing the impacts of different climate change scenarios, and the possibility of calibrating climate change impacts against a palaeoclimatic benchmark.  相似文献   

10.
The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941  相似文献   

11.
The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.  相似文献   

12.
The Mediterranean area is one of the regions of the world where GCMs agree the most on precipitation changes due to climate change. In this study we aim to assess the impact of recent climate change on drought features of Mediterranean ecosystems in Southern France. Regional climatic trends for the 1971–2006 period are compared to drought trends based on a water balance model accounting for soil properties, vegetation structure and functioning. Drought, defined here as periods when soil water potentials drop below ??0.5 MPa, is described in terms of intensity, duration and timing, which are integrative of both climate variability and site conditions. Temporal trends in precipitation, temperature and solar radiation lead altogether to drier and warmer conditions over the region but with a high spatial heterogeneity; for similar climatic trends, a significant increase in drought intensity was detected in the wettest areas of the region, whereas drought intensity in the driest areas did not change. Indeed, in the wettest areas, we observed an earlier onset of drought by about 1 month, but a constant end of drought. In the driest areas of the region, we observed the same earlier onset of drought but combined with an earlier end of drought, thus leading to a shift of the dry season without increasing its duration. The definition of drought features both in terms of intensity but also of seasonal timing appears relevant to capture historical or forecasted changes in ecosystem functioning. Studies concerning climate change impacts on forested ecosystems should be interpreted with caution when using climate proxies alone.  相似文献   

13.
A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.  相似文献   

14.
The signatories to United Nations Framework Convention on Climate Change are charged with stabilizing the concentrations of greenhouse gases in the atmosphere at a level that prevents dangerous interference with the climate system. A number of nations, organizations and scientists have suggested that global mean temperature should not rise over 2 °C above preindustrial levels. However, even a relatively moderate target of 2 °C has serious implications for the Arctic, where temperatures are predicted to increase at least 1.5 to 2 times as fast as global temperatures. High latitude vegetation plays a significant role in the lives of humans and animals, and in the global energy balance and carbon budget. These ecosystems are expected to be among the most strongly impacted by climate change over the next century. To investigate the potential impact of stabilization of global temperature at 2 °C, we performed a study using data from six Global Climate Models (GCMs) forced by four greenhouse gas emissions scenarios, the BIOME4 biogeochemistry-biogeography model, and remote sensing data. GCM data were used to predict the timing and patterns of Arctic climate change under a global mean warming of 2 °C. A unified circumpolar classification recognizing five types of tundra and six forest biomes was used to develop a map of observed Arctic vegetation. BIOME4 was used to simulate the vegetation distributions over the Arctic at the present and for a range of 2 °C global warming scenarios. The GCMs simulations indicate that the earth will have warmed by 2 °C relative to preindustrial temperatures by between 2026 and 2060, by which stage the area-mean annual temperature over the Arctic (60–90°N) will have increased by between 3.2 and 6.6 °C. Forest extent is predicted by BIOME4 to increase in the Arctic on the order of 3 × 106 km2 or 55% with a corresponding 42% reduction in tundra area. Tundra types generally also shift north with the largest reductions in the prostrate dwarf-shrub tundra, where nearly 60% of habitat is lost. Modeled shifts in the potential northern limit of trees reach up to 400 km from the present tree line, which may be limited by dispersion rates. Simulated physiological effects of the CO2 increase (to ca. 475 ppm) at high latitudes were small compared with the effects of the change in climate. The increase in forest area of the Arctic could sequester 600 Pg of additional carbon, though this effect is unlikely to be realized over next century.  相似文献   

15.
Dynamical downscaling has been recognized as a useful tool not only for the climate community, but also for associated application communities such as the environmental and hydrological societies. Although climate projection data are available in lower-resolution general circulation models (GCMs), higher-resolution climate projections using regional climate models (RCMs) have been obtained over various regions of the globe. Various model outputs from RCMs with a high resolution of even as high as a few km have become available with heavy weight on applications. However, from a scientific point of view in numerical atmospheric modeling, it is not clear how to objectively judge the degree of added value in the RCM output against the corresponding GCM results. A key factor responsible for skepticism is based on the fundamental limitations in the nesting approach between GCMs and RCMs. In this article, we review the current status of the dynamical downscaling for climate prediction, focusing on basic assumptions that are scrutinized from a numerical weather prediction (NWP) point of view. Uncertainties in downscaling due to the inconsistencies in the physics packages between GCMs and RCMs were revealed. Recommendations on how to tackle the ultimate goal of dynamical downscaling were also described.  相似文献   

16.
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   

17.
We use a georeferenced model of ecosystem carbon dynamics to explore the sensitivity of global terrestrial carbon storage to changes in atmospheric CO2 and climate. We model changes in ecosystem carbon density, but we do not model shifts in vegetation type. A model of annual NPP is coupled with a model of carbon allocation in vegetation and a model of decomposition and soil carbon dynamics. NPP is a function of climate and atmospheric CO2 concentration. The CO2 response is derived from a biochemical model of photosynthesis. With no change in climate, a doubling of atmospheric CO2 from 280 ppm to 560 ppm enhances equilibrium global NPP by 16.9%; equilibrium global terrestrial ecosystem carbon (TEC) increases by 14.9%. Simulations with no change in atmospheric CO2 concentration but changes in climate from five atmospheric general circulation models yield increases in global NPP of 10.0–14.8%. The changes in NPP are very nearly balanced by changes in decomposition, and the resulting changes in TEC range from an increase of 1.1% to a decrease of 1.1%. These results are similar to those from analyses using bioclimatic biome models that simulate shifts in ecosystem distribution but do not model changes in carbon density within vegetation types. With changes in both climate and a doubling of atmospheric CO2, our model generates increases in NPP of 30.2–36.5%. The increases in NPP and litter inputs to the soil more than compensate for any climate stimulation of decomposition and lead to increases in global TEC of 15.4–18.2%.  相似文献   

18.
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   

19.
Direct observations as well as Normalized Difference Vegetation Index (NDVI) data from satellites have shown earlier leaf appearance in the northern hemisphere, which is believed to result from climate warming. The advance of leaf out to earlier times in the year could be limited or even reversed, however, as temperate and boreal trees require a certain amount of chilling in winter for rapid leaf out in spring. If this chilling requirement is not fulfilled, an increasing amount of warming is required. Implications of these chilling requirements at the biome level are not clear. One approach to estimate their importance is to generalize the exponential relationships between chilling and warming established for single species. Previous work using NDVI data suggests that this is indeed feasible but much has been limited to specific biomes or a very few years of data for the modelling. We find chilling requirements for northern temperate and boreal biomes by fitting various phenology models to green-up dates determined from NDVI using various methods and 12 years of data. The models predict that in northern middle and high latitudes the advance of green-up will be limited to a total of 4 to 5 days on average (but up to 15 days regionally) over the time period 2000–2060 as estimated using two contrasting climate simulations. This results from the exponentially increasing warming requirements for leaf out when winter chilling falls below a threshold as shown by a comparison with models that consider only spring warming. The model evaluation suggests an element of regional adaptation of the warming required for leaf out in large biomes.  相似文献   

20.
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   

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