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1.
Yoko Tsushima S. Emori T. Ogura M. Kimoto M. J. Webb K. D. Williams M. A. Ringer B. J. Soden B. Li N. Andronova 《Climate Dynamics》2006,27(2-3):113-126
We have conducted a multi-model intercomparison of cloud-water in five state-of-the-art AGCMs run for control and doubled carbon dioxide climates. The most notable feature of the differences between the control and doubled carbon dioxide climates is in the distribution of cloud-water in the mixed-phase temperature band. The difference is greatest at mid and high latitudes. We found that the amount of cloud ice in the mixed phase layer in the control climate largely determines how much the cloud-water distribution changes for the doubled carbon dioxide climate. Therefore evaluation of the cloud ice distribution by comparison with data is important for future climate sensitivity studies. Cloud ice and cloud liquid both decrease in the layer below the melting layer, but only cloud liquid increases in the mixed-phase layer. Although the decrease in cloud-water below the melting layer occurs at all latitudes, the increase in cloud liquid in the mixed-phase layer is restricted to those latitudes where there is a large amount of cloud ice in the mixed-phase layer. If the cloud ice in the mixed-phase layer is concentrated at high latitudes, doubling of carbon dioxide might shift the center of cloud water distribution poleward which could decrease solar reflection because solar insolation is less at higher latitude. The magnitude of this poleward shift of cloud water appears to be larger for the higher climate sensitivity models, and it is consistent with the associated changes in cloud albedo forcing. For the control climate there is a clear relationship between the differences in cloud-water and relative humidity between the different models, for both magnitude and distribution. On the other hand the ratio of cloud ice to cloud-water follows the threshold temperature which is determined in each model. Improved measurements of relative humidity could be used to constrain the modeled representation of cloud water. At the same time, comparative analysis in global cloud resolving model simulations is necessary for further understanding of the relationships suggested in this paper. 相似文献
2.
Hideo Shiogama Masahiro Watanabe Masakazu Yoshimori Tokuta Yokohata Tomoo Ogura James D. Annan Julia C. Hargreaves Manabu Abe Youichi Kamae Ryouta O’ishi Rei Nobui Seita Emori Toru Nozawa Ayako Abe-Ouchi Masahide Kimoto 《Climate Dynamics》2012,39(12):3041-3056
In this study, we constructed a perturbed physics ensemble (PPE) for the MIROC5 coupled atmosphere–ocean general circulation model (CGCM) to investigate the parametric uncertainty of climate sensitivity (CS). Previous studies of PPEs have mainly used the atmosphere-slab ocean models. A few PPE studies using a CGCM applied flux corrections, because perturbations in parameters can lead to large radiation imbalances at the top of the atmosphere and climate drifts. We developed a method to prevent climate drifts in PPE experiments using the MIROC5 CGCM without flux corrections. We simultaneously swept 10 parameters in atmosphere and surface schemes. The range of CS (estimated from our 35 ensemble members) was not wide (2.2–3.2?°C). The shortwave cloud feedback related to changes in middle-level cloud albedo dominated the variations in the total feedback. We found three performance metrics for the present climate simulations of middle-level cloud albedo, precipitation, and ENSO amplitude that systematically relate to the variations in shortwave cloud feedback in this PPE. 相似文献
3.
Masahiro Watanabe Hideo Shiogama Masakazu Yoshimori Tomoo Ogura Tokuta Yokohata Hajime Okamoto Seita Emori Masahide Kimoto 《Climate Dynamics》2012,39(7-8):1627-1641
To obtain physical insights into the response and feedback of low clouds (C l ) to global warming, ensemble 4?×?CO2 experiments were carried out with two climate models, the Model for Interdisciplinary Research on Climate (MIROC) versions 3.2 and 5. For quadrupling CO2, tropical-mean C l decreases, and hence, acts as positive feedback in MIROC3, whereas it increases and serves as negative feedback in MIROC5. Three time scales of tropical-mean C l change were identified—an initial adjustment without change in the global-mean surface air temperature, a slow response emerging after 10–20?years, and a fast response in between. The two models share common features for the former two changes in which C l decreases. The slow response reflects the variability of C l associated with the El Ni?o-Southern Oscillation in the control integration, and may therefore be constrained by observations. However, the fast response is opposite in the two models and dominates the total response of C l . Its sign is determined by a subtle residual of the C l increase and decrease over the ascending and subsidence regions, respectively. The regional C l increase is consistent with a more frequent occurrence of a stable condition, and vice versa, as measured by lower-tropospheric stability (LTS). The above frequency change in LTS is similarly found in six other climate models despite a large difference in both the mean and the changes in the low-cloud fraction for a given LTS. This suggests that the response of the thermodynamic constraint for C l to increasing CO2 concentrations is a robust part of the climate change. 相似文献
4.
On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles 总被引：3，自引：15，他引：3
M. J. Webb C. A. Senior D. M. H. Sexton W. J. Ingram K. D. Williams M. A. Ringer B. J. McAvaney R. Colman B. J. Soden R. Gudgel T. Knutson S. Emori T. Ogura Y. Tsushima N. Andronova B. Li I. Musat S. Bony K. E. Taylor 《Climate Dynamics》2006,27(1):17-38
Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%. 相似文献
5.
In this study, we focused on the difference in appearances of the convectively coupled equatorial waves (CCEWs) in a simulation with the CCSR/NIES/FRCGC AGCM, between two experiments, one with and the other without implementation of the convective suppression scheme (CSS) in the prognostic Arakawa–Schubert cumulus parameterization. Realistic CCEW modes, i.e., Kelvin, Rossby, mixed Rossby-gravity (MRG), and n = 0 eastward inertio-gravity (EIG) wave modes, were reproduced in the with-CSS experiment, while only Rossby-wave-like signals appeared in the without-CSS experiment.By comparing the structures of the Kelvin wave mode and the Rossby wave mode in two runs, it was suggested that the structural difference between these two modes in conjunction with the difference in the controlling factor of cumulus convection determines the CCEW features. The CSS implemented here is such that cumulus convection is suppressed until the cloud-layer-averaged relative humidity exceeds the threshold of 80%. In the without-CSS model, only Rossby wave modes are coupled with the convection. This is because CAPE controls cumulus convection in this model, and the larger frictional convergence of Rossby wave mode prepares CAPE to generate favorable condition for cumulus convection. In the case of the with-CSS model, on the other hand, cumulus convection is largely controlled by the humidity in the free atmosphere. The convergence associated with the equatorial waves can produce the moisture anomaly to overcome the relative humidity threshold, and maintains the favorable condition for cumulus convection once it starts. In this case, not only Rossby waves but also Kelvin, MRG, and n = 0 EIG waves are reproduced more realistically. It is suggested that inclusion of some kind of mechanism connecting the free tropospheric moisture with the convection under the condition of abundant convective available potential energy could be a key factor for realistic coupling between large-scale atmospheric waves and convection. 相似文献
6.
The surface flux calculation method proposed by Louis (1979) is extended by allowing momentum and heat to have different roughness lengths (z
0 andz
T respectively). Our approach is to extend the traditional analysis by a more careful consideration of potential temperature structure near the surface. This consideration leads to a redefinition of the bulk Richardson number. For bulk transfer coefficients, our method shows a significant improvement over the original Louis method when compared with the theoretical surface-layer model applied to rough surfaces. Numerical experiments simulating sea breezes in 2D show that our extension is crucially important in simulating light wind and low humidity conditions. 相似文献
7.
利用一套新的遥感信息反演的叶面积指数(LAI)数据和生物气候数据,建立了全球尺度的LAI与降水及温度的总体相关和距平相关,用以揭示全球尺度的植被季节和年际的变化对气候变化的响应特征.结果发现,全球尺度植被与气候因子的季节和年际变化随不同的生态系统差异明显.植被LAI与温度的总体正相关的最大值出现在北半球的中高纬度地区;LAI与降水的总体正相关高值(＞0.8)出现在亚洲东部、北美洲北部腹地和热带非洲北部的Sahel地区;最大的LAI与温度的正距平相关(0.4-0.6)出现在东南亚南部、非洲Sahel地区的南部和巴西东部等热带地区;而从LAI与降水的距平相关来看,最明显的特征是出现在西伯利亚、亚洲北部和北美西北部的强的负距平相关.本文进一步阐明了出现相关特征差异的陆-气过程物理机制. 相似文献
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9.
Tokuta Yokohata James D. Annan Matthew Collins Charles S. Jackson Hideo Shiogama Masahiro Watanabe Seita Emori Masakazu Yoshimori Manabu Abe Mark J. Webb Julia C. Hargreaves 《Climate Dynamics》2013,41(9-10):2745-2763
We investigate the performance of the newest generation multi-model ensemble (MME) from the Coupled Model Intercomparison Project (CMIP5). We compare the ensemble to the previous generation models (CMIP3) as well as several single model ensembles (SMEs), which are constructed by varying components of single models. These SMEs range from ensembles where parameter uncertainties are sampled (perturbed physics ensembles) through to an ensemble where a number of the physical schemes are switched (multi-physics ensemble). We focus on assessing reliability against present-day climatology with rank histograms, but also investigate the effective degrees of freedom (EDoF) of the fields of variables which makes the statistical test of reliability more rigorous, and consider the distances between the observation and ensemble members. We find that the features of the CMIP5 rank histograms, of general reliability on broad scales, are consistent with those of CMIP3, suggesting a similar level of performance for present-day climatology. The spread of MMEs tends towards being “over-dispersed” rather than “under-dispersed”. In general, the SMEs examined tend towards insufficient dispersion and the rank histogram analysis identifies them as being statistically distinguishable from many of the observations. The EDoFs of the MMEs are generally greater than those of SMEs, suggesting that structural changes lead to a characteristically richer range of model behaviours than is obtained with parametric/physical-scheme-switching ensembles. For distance measures, the observations and models ensemble members are similarly spaced from each other for MMEs, whereas for the SMEs, the observations are generally well outside the ensemble. We suggest that multi-model ensembles should represent an important component of uncertainty analysis. 相似文献
10.
K. D. Williams M. A. Ringer C. A. Senior M. J. Webb B. J. McAvaney N. Andronova S. Bony J. -L. Dufresne S. Emori R. Gudgel T. Knutson B. Li K. Lo I. Musat J. Wegner A. Slingo J. F. B. Mitchell 《Climate Dynamics》2006,26(2-3):145-165
Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO2 and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change. 相似文献