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1.
The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique.  相似文献   

2.
An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO2 concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO2. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.  相似文献   

3.
We diagnose climate feedback parameters and CO2 forcing including rapid adjustment in twelve atmosphere/mixed-layer-ocean (“slab”) climate models from the CMIP3/CFMIP-1 project (the AR4 ensemble) and fifteen parameter-perturbed versions of the HadSM3 slab model (the PPE). In both ensembles, differences in climate feedbacks can account for approximately twice as much of the range in climate sensitivity as differences in CO2 forcing. In the AR4 ensemble, cloud effects can explain the full range of climate sensitivities, and cloud feedback components contribute four times as much as cloud components of CO2 forcing to the range. Non-cloud feedbacks are required to fully account for the high sensitivities of some models however. The largest contribution to the high sensitivity of HadGEM1 is from a high latitude clear-sky shortwave feedback, and clear-sky longwave feedbacks contribute substantially to the highest sensitivity members of the PPE. Differences in low latitude ocean regions (30°N/S) contribute more to the range than those in mid-latitude oceans (30–55°N/S), low/mid latitude land (55°N/S) or high latitude ocean/land (55–90°N/S), but contributions from these other regions are required to account fully for the higher model sensitivities, for example from land areas in IPSL CM4. Net cloud feedback components over the low latitude oceans sorted into percentile ranges of lower tropospheric stability (LTS) show largest differences among models in stable regions, mainly due to their shortwave components, most of which are positive in spite of increasing LTS. Differences in the mid-stability range are smaller, but cover a larger area, contributing a comparable amount to the range in climate sensitivity. These are strongly anti-correlated with changes in subsidence. Cloud components of CO2 forcing also show the largest differences in stable regions, and are strongly anticorrelated with changes in estimated inversion strength (EIS). This is qualitatively consistent with what would be expected from observed relationships between EIS and low-level cloud fraction. We identify a number of cases where individual models show unusually strong forcings and feedbacks compared to other members of the ensemble. We encourage modelling groups to investigate unusual model behaviours further with sensitivity experiments. Most of the models fail to correctly reproduce the observed relationships between stability and cloud radiative effect in the subtropics, indicating that there remains considerable room for model improvements in the future.  相似文献   

4.
A linear analysis is applied to a multi-thousand member “perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction.net . A principal component analysis of model radiative response reveals two dominant independent feedback processes, each largely controlled by a single parameter change. The leading EOF was well correlated with the value of the entrainment coefficient—a parameter in the model’s atmospheric convection scheme. Reducing this parameter increases high vertical level moisture causing an enhanced clear sky greenhouse effect both in the control simulation and in the response to greenhouse gas forcing. This effect is compensated by an increase in reflected solar radiation from low level cloud upon warming. A set of ‘secondary’ cloud formation parameters partly modulate the degree of shortwave compensation from low cloud formation. The second EOF was correlated with the scaling of ice fall speed in clouds which affects the extent of cloud cover in the control simulation. The most prominent feature in the EOF was an increase in longwave cloud forcing. The two leading EOFs account for 70% of the ensemble variance in λ—the global feedback parameter. Linear predictors of feedback strength from model climatology are applied to observational datasets to estimate real world values of the overall climate feedback parameter. The predictors are found using correlations across the ensemble. Differences between predictions are largely due to the differences in observational estimates for top of atmosphere shortwave fluxes. Our validation does not rule out all the strong tropical convective feedbacks leading to a large climate sensitivity.  相似文献   

5.
世界气候研究计划(WCRP)于2003年支持开展云反馈模式比较计划（CFMIP)。目前已经开展到第三阶段（CFMIP-3)。相比前两阶段的试验,CFMIP-3试验设计更加丰富、具体,除增加CMIP6 DECK和Historical试验的观测模拟器（COSP）输出外,还围绕着回答7个云反馈相关的科学问题,设计了Tier-1（必做）和Tier-2（可选）两类试验。CFMIP将气候模拟、观测研究和过程模拟等几个研究方向更紧密地联系在一起,并为理解和模拟云及其辐射反馈的气候贡献提供更深刻的认识和分析手段。  相似文献   

6.
This study diagnoses the climate sensitivity, radiative forcing and climate feedback estimates from eleven general circulation models participating in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), and analyzes inter-model differences. This is done by taking into account the fact that the climate response to increased carbon dioxide (CO2) is not necessarily only mediated by surface temperature changes, but can also result from fast land warming and tropospheric adjustments to the CO2 radiative forcing. By considering tropospheric adjustments to CO2 as part of the forcing rather than as feedbacks, and by using the radiative kernels approach, we decompose climate sensitivity estimates in terms of feedbacks and adjustments associated with water vapor, temperature lapse rate, surface albedo and clouds. Cloud adjustment to CO2 is, with one exception, generally positive, and is associated with a reduced strength of the cloud feedback; the multi-model mean cloud feedback is about 33 % weaker. Non-cloud adjustments associated with temperature, water vapor and albedo seem, however, to be better understood as responses to land surface warming. Separating out the tropospheric adjustments does not significantly affect the spread in climate sensitivity estimates, which primarily results from differing climate feedbacks. About 70 % of the spread stems from the cloud feedback, which remains the major source of inter-model spread in climate sensitivity, with a large contribution from the tropics. Differences in tropical cloud feedbacks between low-sensitivity and high-sensitivity models occur over a large range of dynamical regimes, but primarily arise from the regimes associated with a predominance of shallow cumulus and stratocumulus clouds. The combined water vapor plus lapse rate feedback also contributes to the spread of climate sensitivity estimates, with inter-model differences arising primarily from the relative humidity responses throughout the troposphere. Finally, this study points to a substantial role of nonlinearities in the calculation of adjustments and feedbacks for the interpretation of inter-model spread in climate sensitivity estimates. We show that in climate model simulations with large forcing (e.g., 4 × CO2), nonlinearities cannot be assumed minor nor neglected. Having said that, most results presented here are consistent with a number of previous feedback studies, despite the very different nature of the methodologies and all the uncertainties associated with them.  相似文献   

7.
R. A. Colman 《Climate Dynamics》2001,17(5-6):391-405
This study addresses the question: what vertical regions contribute the most to water vapor, surface temperature, lapse rate and cloud fraction feedback strengths in a general circulation model? Multi-level offline radiation perturbation calculations are used to diagnose the feedback contribution from each model level. As a first step, to locate regions of maximum radiative sensitivity to climate changes, the top of atmosphere radiative impact for each feedback is explored for each process by means of idealized parameter perturbations on top of a control (1?×?CO2) model climate. As a second step, the actual feedbacks themselves are calculated using the changes modelled from a 2?×?CO2 experiment. The impact of clouds on water vapor and lapse rate feedbacks is also isolated using `clear sky' calculations. Considering the idealized changes, it is found that the radiative sensitivity to water vapor changes is a maximum in the tropical lower troposphere. The sensitivity to temperature changes has both upper and lower tropospheric maxima. The sensitivity to idealized cloud changes is positive (warming) for upper level cloud increases but negative (cooling) for lower level increases, due to competing long and shortwave effects. Considering the actual feedbacks, it is found that water vapor feedback is a maximum in the tropical upper troposphere, due to the large relative increases in specific humidity which occur there. The actual lapse rate feedback changes sign with latitude and is a maximum (negative) again in the tropical upper troposphere. Cloud feedbacks reflect the general decrease in low- to mid-level low-latitude cloud, with an increase in the very highest cloud. This produces a net positive (negative) shortwave (longwave) cloud feedback. The role of clouds in the strength of the water vapor and lapse rate feedbacks is also discussed.  相似文献   

8.
基于云和地球辐射能量系统观测数据集（CERES),对比分析了耦合模式比较计划第五（CMIP5）和第六阶段（CMIP6）模拟的历史大气层顶和地表辐射收支的年际变化和空间分布,明确了多模式间不确定性大的关键区域。结果表明：在年际尺度上,除地表向上长波辐射外,CMIP6的辐射分量的集合均值较CMIP5更接近于CERES观测值,全球地表向下短波辐射的高估和大气逆辐射的低估在CMIP6中分别降低了1.9 W/m2和3.3 W/m2。除大气逆辐射外,CMIP6的辐射分量在多模式间的一致性较CMIP5提高。在北极,CMIP6对大气层顶反射短波、大气层顶出射长波和地表向下短波辐射的模拟偏差较CMIP5大。在南北纬60°,CMIP6对大气逆辐射的模拟偏差较CMIP5大。其他区域CMIP6的辐射分量更接近CERES观测值。CMIP6模拟的地表向下短波辐射和大气逆辐射的不确定性较大区域面积较CMIP5减小,但不确定性极大区域面积无变化。地表净辐射的不确定性空间分布在两代CMIP间变化甚小。青藏高原、赤道太平洋、热带雨林、阿拉伯半岛和南极洲沿海依然是地球系统模式模拟辐射收支不确定性极大的关键区域。  相似文献   

9.
Summary Satellite-derived datasets are used to verify the cloud cover and radiation field generated by a T62 (horizontal resolution) version of the operational global model at the National Meteorological Centre (NMC). An ensemble of five day forecasts for July 1985 is used, as well as 30 day climatological forecasts for July 1985, October 1985, January 1986, and April 1986.Monthly averages of radiation fields are compared with Earth Radiation Budget Experiment (ERBE) data. For the four months examined, clear-sky outgoing longwave radiation (clear-sky OLR) and absorbed shortwave radiation (clear-sky SW) tend to agree roughly with ERBE. Model global mean OLR, however, exceeds that of ERBE by 10 W m–2.Comparison of effective cloud cover to corresponding fields cataloged by the International Satellite Cloud Climatology Project (ISCCP C1) reveals deficiencies in the amount of supersaturation cloudiness and the vertical distribution of convective clouds. Large inaccuracies in model radiation fields are closely related to deficiencies in the cloud parameterization. An inventory of model cloudiness, in comparison to satellite data, is conducted.With 18 Figures  相似文献   

10.
A quantitative performance assessment of cloud regimes in climate models   总被引：4，自引：3，他引：1  
Differences in the radiative feedback from clouds account for much of the variation in climate sensitivity amongst General Circulation Models (GCMs). Therefore metrics of model performance which are demonstrated to be relevant to the cloud response to climate change form an important contribution to the overall evaluation of GCMs. In this paper we demonstrate an alternative method for assigning model data to observed cloud regimes obtained from clustering histograms of cloud amount in joint cloud optical depth—cloud top pressure classes. The method removes some of the subjectivity that exists in previous GCM cloud clustering studies. We apply the method to ten GCMs submitted to the Cloud Feedback Model Intercomparison Project (CFMIP), evaluate the simulated cloud regimes and analyse the climate change response in the context of these regimes. We also propose two cloud regime metrics, one of which is specifically targeted at assessing GCMs for the purpose of obtaining the global cloud radiative response to climate change. Most of the global variance in the cloud radiative response between GCMs is due to low clouds, with 47% arising from the stratocumulus regime and 18% due to the regime characterised by clouds undergoing transition from stratocumulus to cumulus. This result is found to be dominated by two structurally similar GCMs. The shallow cumulus regime, though widespread, has a smaller contribution and reduces the variance. For the stratocumulus and transition regimes, part of the variance results from a large model spread in the radiative properties of the regime in the control simulation. Comparison with observations reveals a systematic bias for both the stratocumulus and transition regimes to be overly reflective. If this bias was corrected with all other aspects of the response unchanged, the variance in the low cloud response would reduce. The response of some regimes with high cloud tops differ between the GCMs. These regimes are simulated too infrequently in a few of the models. If the frequency in the control simulation were more realistic and changes within the regimes were unaltered, the variance in the cloud radiative response from high-top clouds would increase. As a result, use of observations of the mean present-day cloud regimes suggests that whilst improvements in the simulation of the cloud regimes would impact the climate sensitivity, the inter-model variance may not reduce. When the cloud regime metric is calculated for the GCMs analysed here, only one model is on average consistent with observations within their uncertainty (and even this model is not consistent with the observations for all regimes), indicating scope for improvement in the simulation of cloud regimes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.  相似文献   

11.
 This study performs a comprehensive feedback analysis on the Bureau of Meteorology Research Centre General Circulation Model, quantifying all important feedbacks operating under an increase in atmospheric CO2. The individual feedbacks are analysed in detail, using an offline radiation perturbation method, looking at long- and shortwave components, latitudinal distributions, cloud impacts, non-linearities under 2xCO2 and 4xCO2 warmings and at interannual variability. The water vapour feedback is divided into terms due to moisture height and amount changes. The net cloud feedback is separated into terms due to cloud amount, height, water content, water phase, physical thickness and convective cloud fraction. Globally the most important feedbacks were found to be (from strongest positive to strongest negative) those due to water vapour, clouds, surface albedo, lapse rate and surface temperature. For the longwave (LW) response the most important term of the cloud ‘optical property’ feedbacks is due to the water content. In the shortwave (SW), both water content and water phase changes are important. Cloud amount and height terms are also important for both LW and SW. Feedbacks due to physical cloud thickness and convective cloud fraction are found to be relatively small. All cloud component feedbacks (other than height) produce conflicting LW/SW feedbacks in the model. Furthermore, the optical property and cloud fraction feedbacks are also of opposite sign. The result is that the net cloud feedback is the (relatively small) product of conflicting physical processes. Non-linearities in the feedbacks are found to be relatively small for all but the surface albedo response and some cloud component contributions. The cloud impact on non-cloud feedbacks is also discussed: greatest impact is on the surface albedo, but impact on water vapour feedback is also significant. The analysis method here proves to be a␣powerful tool for detailing the contributions from different model processes (and particularly those of the clouds) to the final climate model sensitivity. Received: 15 June 2000 / Accepted: 10 January 2001  相似文献   

12.
In an ensemble of general circulation models, the global mean albedo significantly decreases in response to strong CO2 forcing. In some of the models, the magnitude of this positive feedback is as large as the CO2 forcing itself. The models agree well on the surface contribution to the trend, due to retreating snow and ice cover, but display large differences when it comes to the contribution from shortwave radiative effects of clouds. The ??cloud contribution?? defined as the difference between clear-sky and all-sky albedo anomalies and denoted as ??CC is correlated with equilibrium climate sensitivity in the models (correlation coefficient 0.76), indicating that in high sensitivity models the clouds to a greater extent act to enhance the negative clear-sky albedo trend, whereas in low sensitivity models the clouds rather counteract this trend. As a consequence, the total albedo trend is more negative in more sensitive models (correlation coefficient 0.73). This illustrates in a new way the importance of cloud response to global warming in determining climate sensitivity in models. The cloud contribution to the albedo trend can primarily be ascribed to changes in total cloud fraction, but changes in cloud albedo may also be of importance.  相似文献   

13.
 This study compares radiative fluxes and cloudiness fields from three general circulation models (the HadAM4 version of the Hadley Centre Unified model, cycle 16r2 of the ECMWF model and version LMDZ 2.0 of the LMD GCM), using a combination of satellite observations from the Earth Radiation Budget Experiment (ERBE) and the International Satellite Cloud Climatology Project (ISCCP). To facilitate a meaningful comparison with the ISCCP C1 data, values of column cloud optical thickness and cloud top pressure are diagnosed from the models in a manner consistent with the satellite view from space. Decomposing the cloud radiative effect into contributions from low-medium- and high-level clouds reveals a tendency for the models' low-level clouds to compensate for underestimates in the shortwave cloud radiative effect caused by a lack of high-level or mid-level clouds. The low clouds fail to compensate for the associated errors in the longwave. Consequently, disproportionate errors in the longwave and shortwave cloud radiative effect in models may be taken as an indication that compensating errors are likely to be present. Mid-level cloud errors in the mid-latitudes appear to depend as much on the choice of the convection scheme as on the cloud scheme. Convective and boundary layer mixing schemes require as much consideration as cloud and precipitation schemes when it comes to assessing the simulation of clouds by models. Two distinct types of cloud feedback are discussed. While there is reason to doubt that current models are able to simulate potential `cloud regime' type feedbacks with skill, there is hope that a model capable of simulating potential `cloud amount' type feedbacks will be achievable once the reasons for the remaining differences between the models are understood. Received: 23 January 2000 / Accepted: 24 January 2001  相似文献   

14.
The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(T_(as)) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(T_s) over the TP. The cold biases are larger in T_(as) than in T_s, and are larger over the western TP. By decomposing the T_s bias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models.  相似文献   

15.
The performance of several state-of-the-art climate model ensembles, including two multi-model ensembles (MMEs) and four structurally different (perturbed parameter) single model ensembles (SMEs), are investigated for the first time using the rank histogram approach. In this method, the reliability of a model ensemble is evaluated from the point of view of whether the observations can be regarded as being sampled from the ensemble. Our analysis reveals that, in the MMEs, the climate variables we investigated are broadly reliable on the global scale, with a tendency towards overdispersion. On the other hand, in the SMEs, the reliability differs depending on the ensemble and variable field considered. In general, the mean state and historical trend of surface air temperature, and mean state of precipitation are reliable in the SMEs. However, variables such as sea level pressure or top-of-atmosphere clear-sky shortwave radiation do not cover a sufficiently wide range in some. It is not possible to assess whether this is a fundamental feature of SMEs generated with particular model, or a consequence of the algorithm used to select and perturb the values of the parameters. As under-dispersion is a potentially more serious issue when using ensembles to make projections, we recommend the application of rank histograms to assess reliability when designing and running perturbed physics SMEs.  相似文献   

16.
A version of the National Centre for Atmospheric Research (NCAR) coupled climate model is integrated under current climate conditions and in a series of experiments with climate forcings ranging from modest to very strong. The purpose of the experiments is to investigate the nature and behaviour of the climate feedback/sensitivity of the model, its evolution with time and climate state, the robustness of model parameterizations as forcing levels increase, and the possibility of a “runaway” warming under strong forcing. The model is integrated for 50 years, or to failure, after increasing the solar constant by 2.5, 10, 15, 25, 35, and 45% of its control value. The model successfully completes 50 years of integration for the 2.5, 10, 15, and 25% solar constant increases but fails for increases of 35% and 45%. The effective global climate sensitivity evolves with time and analysis indicates that a new equilibrium will be obtained for the 2.5, 10, and 15% cases but that runaway warming is underway for the 25% increase in solar constant. Feedback processes are analysed both locally and globally in terms of longwave and shortwave, clear-sky/surface, and cloud forcing components. Feedbacks in the system must be negative overall and of sufficient strength to balance the positive forcing if the system is to attain a new equilibrium. Longwave negative feedback processes strengthen in a reasonably linear fashion as temperature increases but shortwave feedback processes do not. In particular, solar cloud feedback becomes less negative and, for the 25% forcing case, eventually becomes positive, resulting in temperatures that “run away”. The conditions under which a runaway climate warming might occur have previously been investigated using simpler models. For sufficiently strong forcing, the greenhouse effect of increasing water vapour in a warmer atmosphere is expected to overwhelm the negative feedback of the longwave cooling to space as temperature increases. This is not, however, the reason for the climate instability experienced in the GCM. Instead, the model experiences a “cloud feedback” warming whereby the decrease in cloudiness that occurs when temperature increases beyond a critical value results in an increased absorption of solar radiation by the system, leading to the runaway warming.  相似文献   

17.
Arctic sea ice mass budgets for the twentieth century and projected changes through the twenty-first century are assessed from 14 coupled global climate models. Large inter-model scatter in contemporary mass budgets is strongly related to variations in absorbed solar radiation, due in large part to differences in the surface albedo simulation. Over the twenty-first century, all models simulate a decrease in ice volume resulting from increased annual net melt (melt minus growth), partially compensated by reduced transport to lower latitudes. Despite this general agreement, the models vary considerably regarding the magnitude of ice volume loss and the relative roles of changing melt and growth in driving it. Projected changes in sea ice mass budgets depend in part on the initial (mid twentieth century) ice conditions; models with thicker initial ice generally exhibit larger volume losses. Pointing to the importance of evolving surface albedo and cloud properties, inter-model scatter in changing net ice melt is significantly related to changes in downwelling longwave and absorbed shortwave radiation. These factors, along with the simulated mean and spatial distribution of ice thickness, contribute to a large inter-model scatter in the projected onset of seasonally ice-free conditions.  相似文献   

18.
The influence of prescribed changes in vegetation on the climate of the North American monsoon region is examined using the National Center for Atmospheric Research Community Climate System Model Version 3.5 (NCAR CCSM3.5). Initial value ensemble experiments are performed in which the vegetation cover fraction over the North American monsoon region is reduced by 0.2 and the intra-annual climatic response is assessed probabilistically in each one-year ensemble experiment. Changes in the surface radiation budget include decreases in sensible and latent heat fluxes and increases in upward longwave and downward shortwave radiation fluxes, with small net changes in surface albedo. The climatic responses to reduced vegetation cover fraction include year-round increases in ground and surface air temperature, a dampened hydrologic cycle with decreased springtime evaporation, springtime and autumnal precipitation, and autumnal cloud cover, and enhanced atmospheric subsidence in late autumn. Decreased vegetation shifts the monsoon season over the Southwest United States earlier in the year. Within the North American monsoon region, the most robust vegetation feedbacks to climate are found over woody landscapes.  相似文献   

19.
The Cloud-Aerosol-Radiation (CAR) ensemble modeling system has recently been built to better understand cloud/aerosol/radiation processes and determine the uncertainties caused by different treatments of cloud/aerosol/radiation in climate models. The CAR system comprises a large scheme collection of cloud, aerosol, and radiation processes available in the literature, including those commonly used by the world's leading GCMs. In this study, detailed analyses of the overall accuracy and efficiency of the CAR system were performed. Despite the different observations used, the overall accuracies of the CAR ensemble means were found to be very good for both shortwave (SW) and longwave (LW) radiation calculations. Taking the percentage errors for July 2004 compared to ISCCP (International Satellite Cloud Climatology Project) data over (60°N, 60°S) as an example, even among the 448 CAR members selected here, those errors of the CAR ensemble means were only about-0.67% (-0.6 W m-2 ) and-0.82% (-2.0 W m-2 ) for SW and LW upward fluxes at the top of atmosphere, and 0.06% (0.1 W m-2 ) and -2.12% (-7.8 W m-2 ) for SW and LW downward fluxes at the surface, respectively. Furthermore, model SW frequency distributions in July 2004 covered the observational ranges entirely, with ensemble means located in the middle of the ranges. Moreover, it was found that the accuracy of radiative transfer calculations can be significantly enhanced by using certain combinations of cloud schemes for the cloud cover fraction, particle effective size, water path, and optical properties, along with better explicit treatments for unresolved cloud structures.  相似文献   

20.
A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model (FGOALS-gl) developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). The model presents a reasonable performance in comparison with reconstructions of surface temperature. Differentiated from significant changes in the 20th century at the global scale, changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere. Seasonally, modeled significant changes are more pronounced during the wintertime at higher latitudes. This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback. The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period, especially at decadal timescales. Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability. The model response to specified external forcings is modulated by cloud radiative forcing (CRF). The CRF acts against the fluctuations of external forcings. Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period, but mainly in longwave radiation by a decrease in cloud amount in the anthropogenic-forcing-dominant period.  相似文献   

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