共查询到20条相似文献,搜索用时 31 毫秒
1.
Kirsti Jylhä Stefan Fronzek Heikki Tuomenvirta Timothy R. Carter Kimmo Ruosteenoja 《Climatic change》2008,86(3-4):441-462
Changes in indices related to frost and snow in Europe by the end of the twenty-first century were analyzed based on experiments
performed with seven regional climate models (RCMs). All the RCMs regionalized information from the same general circulation
model (GCM), applying the IPCC-SRES A2 radiative forcing scenario. In addition, some simulations used SRES B2 radiative forcing
and/or boundary conditions provided by an alternative GCM. Ice cover over the Baltic Sea was examined using a statistical
model that related the annual maximum extent of ice to wintertime coastal temperatures. Fewer days with frost and snow, shorter
frost seasons, a smaller liquid water equivalent of snow, and milder sea ice conditions were produced by all model simulations,
irrespective of the forcing scenario and the driving GCM. The projected changes have implications across a diverse range of
human activities. Details of the projections were subject to differences in RCM design, deviations between the boundary conditions
of the driving GCMs, uncertainties in future emissions and random effects due to internal climate variability. A larger number
of GCMs as drivers of the RCMs would most likely have resulted in somewhat wider ranges in the frost, snow and sea ice estimates
than those presented in this paper. 相似文献
2.
Kristina Blennow Mikael Andersson Johan Bergh Ola Sallnäs Erika Olofsson 《Climatic change》2010,99(1-2):261-278
We estimated how the possible changes in wind climate and state of the forest due to climate change may affect the probability of exceeding critical wind speeds expected to cause wind damage within a forest management unit located in Southern Sweden. The topography of the management unit was relatively gentle and the forests were dominated by Norway spruce (Picea abies (L.) Karst.). We incorporated a model relating the site index (SI) to the site productivity into the forest projection model FTM. Using estimated changes in the net primary production (NPP) due to climate change and assuming a relative change in NPP equal to a relative change in the site productivity, we simulated possible future states of the forest under gradual adjustment of SI in response to climate change. We estimated changes in NPP by combining the boreal-adapted BIOMASS model with four regional climate change scenarios calculated using the RCAO model for the period 2071–2100 and two control period scenarios for the period 1961–1990. The modified WINDA model was used to calculate the probability of wind damage for individual forest stands in simulated future states of the forest. The climate change scenarios used represent non-extreme projections on a 100-year time scale in terms of global mean warming. A 15–40% increase in NPP was estimated to result from climate change until the period 2071–2100. Increasing sensitivity of the forest to wind was indicated when the management rules of today were applied. A greater proportion of the calculated change in probability of wind damage was due to changes in wind climate than to changes in the sensitivity of the forest to wind. While regional climate scenarios based on the HadAM3H general circulation model (GCM) indicated no change (SRES A2 emission scenario) or a slightly reduced (SRES B2 emission scenario) probability of wind damage, scenarios based on the ECHAM4/OPYC3 GCM indicated increased probability of wind damage. The assessment should, however, be reviewed as the simulation of forest growth under climate change as well as climate change scenarios are refined. 相似文献
3.
Assessments of the impacts of global change on carbon stocks in mountain regions have received little attention to date, in
spite of the considerable role of these areas for the global carbon cycle. We used the regional hydro-ecological simulation
system RHESSys in five case study catchments from different climatic zones in the European Alps to investigate the behavior
of the carbon cycle under changing climatic and land cover conditions derived from the SRES scenarios of the IPCC. The focus
of this study was on analyzing the differences in carbon cycling across various climatic zones of the Alps, and to explore
the differences between the impacts of various SRES scenarios (A1FI, A2, B1, B2), and between several global circulation models
(GCMs, i.e., HadCM3, CGCM2, CSIRO2, PCM). The simulation results indicate that the warming trend generally enhances carbon
sequestration in these catchments over the first half of the twenty-first century, particularly in forests just below treeline.
Thereafter, forests at low elevations increasingly release carbon as a consequence of the changed balance between growth and
respiration processes, resulting in a net carbon source at the catchment scale. Land cover changes have a strong modifying
effect on these climate-induced patterns. While the simulated temporal pattern of carbon cycling is qualitatively similar
across the five catchments, quantitative differences exist due to the regional differences of the climate and land cover scenarios,
with land cover exerting a stronger influence. The differences in the simulations with scenarios derived from several GCMs
under one SRES scenario are of the same magnitude as the differences between various SRES scenarios derived from one single
GCM, suggesting that the uncertainty in climate model projections needs to be narrowed before accurate impact assessments
under the various SRES scenarios can be made at the local to regional scale. We conclude that the carbon balance of the European
Alps is likely to shift strongly in the future, driven mainly by land cover changes, but also by changes of the climate. We
recommend that assessments of carbon cycling at regional to continental scales should make sure to adequately include sub-regional
differences of changes in climate and land cover, particularly in areas with a complex topography. 相似文献
4.
Although representation of hydrology is included in all regional climate models (RCMs), the utility of hydrological results from RCMs varies considerably from model to model. Studies to evaluate and compare the hydrological components of a suite of RCMs and their use in assessing hydrological impacts from future climate change were carried out over Europe. This included using different methods to transfer RCM runoff directly to river discharge and coupling different RCMs to offline hydrological models using different methods to transfer the climate change signal between models. The work focused on drainage areas to the Baltic Basin, the Bothnian Bay Basin and the Rhine Basin. A total of 20 anthropogenic climate change scenario simulations from 11 different RCMs were used. One conclusion is that choice of GCM (global climate model) has a larger impact on projected hydrological change than either selection of emissions scenario or RCM used for downscaling. 相似文献
5.
Use of general circulation model output in the creation of climate change scenarios for impact analysis 总被引:1,自引:0,他引:1
Alan Robock Richard P. Turco Mark A. Harwell Thomas P. Ackerman Rigoberto Andressen Hsin-Shih Chang M. V. K. Sivakumar 《Climatic change》1993,23(4):293-335
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
6.
Tobias Lung Alessandro Dosio William Becker Carlo Lavalle Laurens M. Bouwer 《Climatic change》2013,120(1-2):211-227
Despite an increasing understanding of potential climate change impacts in Europe, the associated uncertainties remain a key challenge. In many impact studies, the assessment of uncertainties is underemphasised, or is not performed quantitatively. A key source of uncertainty is the variability of climate change projections across different regional climate models (RCMs) forced by different global circulation models (GCMs). This study builds upon an indicator-based NUTS-2 level assessment that quantified potential changes for three climate-related hazards: heat stress, river flood risk, and forest fire risk, based on five GCM/RCM combinations, and non-climatic factors. First, a sensitivity analysis is performed to determine the fractional contribution of each single input factor to the spatial variance of the hazard indicators, followed by an evaluation of uncertainties in terms of spread in hazard indicator values due to inter-model climate variability, with respect to (changes in) impacts for the period 2041–70. The results show that different GCM/RCM combinations lead to substantially varying impact indicators across all three hazards. Furthermore, a strong influence of inter-model variability on the spatial patterns of uncertainties is revealed. For instance, for river flood risk, uncertainties appear to be particularly high in the Mediterranean, whereas model agreement is higher for central Europe. The findings allow for a hazard-specific identification of areas with low vs. high model agreement (and thus confidence of projected impacts) within Europe, which is of key importance for decision makers when prioritising adaptation options. 相似文献
7.
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
8.
This paper investigates how using different regional climate model (RCM) simulations affects climate change impacts on hydrology in northern Europe using an offline hydrological model. Climate change scenarios from an ensemble of seven RCMs, two global climate models (GCMs), two global emissions scenarios and two RCMs of varying resolution were used. A total of 15 climate change simulations were included in studies on the Lule River basin in Northern Sweden. Two different approaches to transfer climate change from the RCMs to hydrological models were tested. A rudimentary estimate of change in hydropower potential on the Lule River due to climate change was also made. The results indicate an overall increase in river flow, earlier spring peak flows and an increase in hydropower potential. The two approaches for transferring the signal of climate change to the hydrological impacts model gave similar mean results, but considerably different seasonal dynamics, a result that is highly relevant for other types of climate change impacts studies. 相似文献
9.
Future changes of terrestrial ecosystems due to changes in atmospheric CO2 concentration and climate are subject to a large degree of uncertainty, especially for vegetation in the Tropics. Here, we evaluate the natural vegetation response to projected future changes using an improved version of a dynamic vegetation model (CLM-CN-DV) driven with climate change projections from 19 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The simulated equilibrium vegetation distribution under historical climate (1981–2000) has been compared with that under the projected future climate (2081–2100) scenario for Representative Concentration Pathway 8.5 (RCP8.5) to qualitatively assess how natural potential vegetation might change in the future. With one outlier excluded, the ensemble average of vegetation changes corresponding to climates of 18 GCMs shows a poleward shift of forests in northern Eurasia and North America, which is consistent with findings from previous studies. It also shows a general “upgrade” of vegetation type in the Tropics and most of the temperate zones, in the form of deciduous trees and shrubs taking over C3 grass in Europe and broadleaf deciduous trees taking over C4 grasses in Central Africa and the Amazon. LAI and NPP are projected to increase in the high latitudes, southeastern Asia, southeastern North America, and Central Africa. This results from CO2 fertilization, enhanced water use efficiency, and in the extra-tropics warming. However, both LAI and NPP are projected to decrease in the Amazon due to drought. The competing impacts of climate change and CO2 fertilization lead to large uncertainties in the projection of future vegetation changes in the Tropics. 相似文献
10.
First-order impacts on winter and summer crops assessed with various high-resolution climate models in the Iberian Peninsula 总被引:1,自引:0,他引:1
María Inés Mínguez Margarita Ruiz-Ramos Carlos H. Díaz-Ambrona Miguel Quemada Federico Sau 《Climatic change》2007,81(1):343-355
The first-order or initial agricultural impacts of climate change in the Iberian Peninsula were evaluated by linking crop simulation models to several high-resolution climate models (RCMs). The RCMs provided the daily weather data for control, and the A2 and B2 IPCC scenarios. All RCMs used boundary conditions from the atmospheric general circulation model (AGCM) HadAM3 while two were also bounded to two other AGCMs. The analyses were standardised to control the sources of variation and uncertainties that were added in the process. Climatic impacts on wheat and maize of climate were derived from the A2 scenario generated by RCMs bounded to HadAM3. Some results derived from B2 scenarios are included for comparisons together with impacts derived from RCMs using different boundary conditions. Crop models were used as impact models and yield was used as an indicator that summarised the effects of climate to quantify initial impacts and differentiate among regions. Comparison among RCMs was made through the choice of different crop management options. All RCM-crop model combinations detected crop failures for winter wheat in the South under control and future scenarios, and projected yield increases for spring wheat in northern and high altitude areas. Although projected impacts differed among RCMs, similar trends emerged for relative yields for some regions. RCM-crop model outputs compared favourably to others using European Re-Analysis data (ERA-15), establishing the feasibility of using direct daily outputs from RCM for impact analysis. Uncertainties were quantified as the standard deviation of the mean obtained for all RCMs in each location and differed greatly between winter (wheat) and summer (maize) seasons, being smaller in the latter. 相似文献
11.
Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia 总被引:1,自引:0,他引:1
This paper outlines a new statistical downscaling method based on a stochastic weather generator. The monthly climate projections from global climate models (GCMs) are first downscaled to specific sites using an inverse distance-weighted interpolation method. A bias correction procedure is then applied to the monthly GCM values of each site. Daily climate projections for the site are generated by using a stochastic weather generator, WGEN. For downscaling WGEN parameters, historical climate data from 1889 to 2008 are sorted, in an ascending order, into 6 climate groups. The WGEN parameters are downscaled based on the linear and non-linear relationships derived from the 6 groups of historical climates and future GCM projections. The overall averaged confidence intervals for these significant linear relationships between parameters and climate variables are 0.08 and 0.11 (the range of these parameters are up to a value of 1.0) at the observed mean and maximum values of climate variables, revealing a high confidence in extrapolating parameters for downscaling future climate. An evaluation procedure is set up to ensure that the downscaled daily sequences are consistent with monthly GCM output in terms of monthly means or totals. The performance of this model is evaluated through the comparison between the distributions of measured and downscaled climate data. Kruskall-Wallis rank (K-W) and Siegel-Tukey rank sum dispersion (S-T) tests are used. The results show that the method can reproduce the climate statistics at annual, monthly and daily time scales for both training and validation periods. The method is applied to 1062 sites across New South Wales (NSW) for 9 GCMs and three IPCC SRES emission scenarios, B1, A1B and A2, for the period of 1900–2099. Projected climate changes by 7 GCMs are also analyzed for the A2 emission scenario based on the downscaling results. 相似文献
12.
The spread amongst ENSEMBLES regional scenarios: regional climate models, driving general circulation models and interannual variability 总被引:3,自引:1,他引:3
M. Déqué S. Somot E. Sanchez-Gomez C. M. Goodess D. Jacob G. Lenderink O. B. Christensen 《Climate Dynamics》2012,38(5-6):951-964
Various combinations of thirteen regional climate models (RCM) and six general circulation models (GCM) were used in FP6-ENSEMBLES. The response to the SRES-A1B greenhouse gas concentration scenario over Europe, calculated as the difference between the 2021–2050 and the 1961–1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance explained for temperature and precipitation changes over eight European sub-areas. Three sources of uncertainty can be evaluated from the ENSEMBLES database. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30) despite a non-negligible interannual variability. Regional model uncertainty is due to the fact that the RCMs use different techniques to discretize the equations and to represent sub-grid effects. Global model uncertainty is due to the fact that the RCMs have been driven by different GCMs. Two methods are presented to fill the many empty cells of the ENSEMBLES RCM?×?GCM matrix. The first one is based on the same approach as in FP5-PRUDENCE. The second one uses the concept of weather regimes to attempt to separate the contribution of the GCM and the RCM. The variance of the climate response is analyzed with respect to the contribution of the GCM and the RCM. The two filling methods agree that the main contributor to the spread is the choice of the GCM, except for summer precipitation where the choice of the RCM dominates the uncertainty. Of course the implication of the GCM to the spread varies with the region, being maximum in the South-western part of Europe, whereas the continental parts are more sensitive to the choice of the RCM. The third cause of spread is systematically the interannual variability. The total uncertainty about temperature is not large enough to mask the 2021–2050 response which shows a similar pattern to the one obtained for 2071–2100 in PRUDENCE. The uncertainty about precipitation prevents any quantitative assessment on the response at grid point level for the 2021–2050 period. One can however see, as in PRUDENCE, a positive response in winter (more rain in the scenario than in the reference) in northern Europe and a negative summer response in southern Europe. 相似文献
13.
The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. 相似文献
14.
The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies. 相似文献
15.
Michelle T. H. van Vliet Stephen Blenkinsop Aidan Burton Colin Harpham Hans Peter Broers Hayley J. Fowler 《Climatic change》2012,111(2):249-277
Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate
some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model
ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and
potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km2) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator
have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional
Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios
show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion
of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected.
The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for
the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to
increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections
are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore,
a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation,
temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale. 相似文献
16.
利用5个全球气候模式和中国东北地区162个站点地面温度实测资料,评估全球气候模式和多模式集合平均对中国东北地区地面温度的模拟能力,并对SRES B1、A1B和A2排放情景下,中国东北地区未来地面温度变化进行预估。结果表明:全球气候模式能够较好地再现了东北地区地面温度的年变化和空间分布特征,但存在系统性冷偏差,模式对夏季地面温度模拟偏低1.16 ℃,优于冬季。预估结果表明,3种排放情景下21世纪中期和末期东北地区地面温度均将升高,末期增幅高于中期,冬季增幅高于其他季节, SRES A2排放情景下增幅最大,B1排放情景下最小;增温幅度自南向北逐渐增大,增温最显著地区位于黑龙江小兴安岭;21世纪末期3种情景下中国东北地区年平均地面温度将分别升高2.39 ℃(SRES B1)、3.62 ℃(SRES A1B)和4.43 ℃(SRES A2)。 相似文献
17.
Making use of the Köppen–Trewartha (K–T) climate classification, we have found that a set of nine high-resolution regional climate models (RCM) are fairly capable of reproducing the current climate in Europe. The percentage of grid-point to grid-point coincidences between climate subtypes based on the control simulations and those of the Climate Research Unit (CRU) climatology varied between 73 and 82%. The best agreement with the CRU climatology corresponds to the RCM “ensemble mean”. The K–T classification was then used to elucidate scenarios of climate change for 2071–2100 under the SRES A2 emission scenario. The percentage of land grid-points with unchanged K–T subtypes ranged from 41 to 49%, while those with a shift from the current climate subtypes towards warmer or drier ones ranged from 51 to 59%. As a first approximation, one may assume that in regions with a shift of two or more climate subtypes, ecosystems might be at risk. Excluding northern Scandinavia, such regions were projected to cover about 12% of the European land area. 相似文献
18.
Seasonal GCM-based temperature and precipitation projections for the end of the 21st century are presented for five European regions; projections are compared with corresponding estimates given by the PRUDENCE RCMs. For most of the six global GCMs studied, only responses to the SRES A2 and B2 forcing scenarios are available. To formulate projections for the A1FI and B1 forcing scenarios, a super-ensemble pattern-scaling technique has been developed. This method uses linear regression to represent the relationship between the local GCM-simulated response and the global mean temperature change simulated by a simple climate model. The method has several advantages: e.g., the noise caused by internal variability is reduced, and the information provided by GCM runs performed with various forcing scenarios is utilized effectively. The super-ensemble method proved especially useful when only one A2 and one B2 simulation is available for an individual GCM. Next, 95% probability intervals were constructed for regional temperature and precipitation change, separately for the four forcing scenarios, by fitting a normal distribution to the set of projections calculated by the GCMs. For the high-end of the A1FI uncertainty interval, temperature increases close to 10°C could be expected in the southern European summer and northern European winter. Conversely, the low-end warming estimates for the B1 scenario are ~ 1°C. The uncertainty intervals of precipitation change are quite broad, but the mean estimate is one of a marked increase in the north in winter and a drastic reduction in the south in summer. In the RCM simulations driven by a single global model, the spread of the temperature and precipitation projections tends to be smaller than that in the GCM simulations, but it is possible to reduce this disparity by employing several driving models for all RCMs. In the present suite of simulations, the difference between the mean GCM and RCM projections is fairly small, regardless of the number or driving models applied. 相似文献
19.
Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data 总被引:1,自引:1,他引:0
The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for daily maxima than minima. RCMs qualitatively reproduce these relationships. Effects of the driving model biases were found on RCMs’ performance in reproducing not only atmospheric circulation but also the links to surface temperature. However, the RCM formulation appears to be more important than the driving data in representing the latter. Differences of the circulation-to-temperature links among the RCA simulations are smaller and the links tend to be more realistic compared to the driving GCMs. 相似文献
20.
Jan Kyselý Ladislav Gaál Romana Beranová Eva Plavcová 《Theoretical and Applied Climatology》2011,104(3-4):529-542
The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available. 相似文献