Quantitative analysis of the feedback induced by the freshwater flux in the tropical Pacific using CMIP5

Freshwater flux (FWF) directly affects sea surface salinity (SSS) and hence modulates sea surface temperature (SST) in the tropical Pacific. This paper quantifies a positive correlation between FWF and SST using observations and simulations of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) to analyze the interannual variability in the tropical Pacific. Comparisons among the displacements of FWF, SSS and SST interannual variabilities illustrate that a large FWF variability is located in the west-central equatorial Pacific, covarying with a large SSS variability, whereas a large SST variability is located in the eastern equatorial Pacific. Most CMIP5 models can reproduce the fact that FWF leads to positive feedback to SST through an SSS anomaly as observed. However, the difference in each model's performance results from different simulation capabilities of the CMIP5 models in the magnitudes and positions of the interannual variabilities, including the mixed layer depth and the buoyancy flux in the equatorial Pacific. SSS anomalies simulated from the CMIP5 multi-model are sensitive to FWF interannual anomalies, which can lead to differences in feedback to interannual SST variabilities. The relationships among the FWF, SSS and SST interannual variabilities can be derived using linear quantitative measures from observations and the CMIP5 multi-model simulations. A 1 mm d-1 FWF anomaly corresponds to an SSS anomaly of nearly 0.12 psu in the western tropical Pacific and a 0.11°C SST anomaly in the eastern tropical Pacific.     

DISCREPANCY OF THE GLOBAL AIR MASS AND WATER BUDGETS AMONG 20 CMIP5 CLIMATE MODELS

The consistency of global atmospheric mass and water budget performance in 20 state-of-the-art ocean–atmosphere Coupled Model Intercomparison Project Phase 5 (CMIP5) coupled models has been assessed in a historical experiment. All the models realistically reproduce a climatological annual mean of global air mass (AM) close to the ERA-Interim AM during 1989–2005. Surprisingly, the global AM in half of the models shows nearly no seasonal variation, which does not agree with the seasonal processes of global precipitable water or water vapor, given the mass conservation constraint. To better understand the inconsistencies, we evaluated the seasonal cycles of global AM tendency and water vapor source (evaporation minus precipitation). The results suggest that the inconsistencies result from the poor balance between global AM tendency and water vapor source based on the global AM budget equation. Moreover, the cross-equatorial dry air mass ?ux, or hemispheric dry mass divergence, is not well represented in any of the 20 CMIP5 models, which show a poorly matched seasonal cycle and notably larger amplitude, compared with the hemispheric tendencies of dry AM in both the Northern Hemisphere and Southern Hemisphere. Pronounced erroneous estimations of tropical precipitation also occur in these models. We speculate that the large inaccuracy of precipitation and possibly evaporation in the tropics is one of the key factors for the inconsistent cross-equatorial mass ?ux. A reasonable cross-equatorial mass ?ux in well-balanced hemispheric air mass and moisture budgets remains a challenge for both reanalysis assimilation systems and climate modeling.     

基于贝叶斯模型的器测、古气候重建与气候模拟数据的融合试验

气象部门馆藏的西部最早的器测气象资料始于20世纪30年代,不能满足建立20世纪以来中国气候变化序列的需求,而古气候重建或气候模拟资料则可以延伸到器测时代以前。为了探讨长序列多源气候资料序列融合方法,采用贝叶斯方法对中国北疆地区8条树轮气温重建资料、器测资料与国际耦合模式比较计划第5阶段（CMIP5）模式模拟资料进行了融合试验。首先利用器测资料对气温代用资料进行校验与网格重建,并以此作为贝叶斯模型的先验分布,然后,用泰勒图选出了该区域气候模拟效果最佳的几个模式;最后将网格重建和气候模拟序列用贝叶斯模型进行了融合试验。结果表明,贝叶斯融合模型能有效提取各种数据来源的有用信息进行融合,融合结果的长期变化（线性）趋势更接近器测气候序列,并在一定程度上提高了序列的精度,减小了结果的不确定性;并且,融合结果能够纠正先验分布及气候模拟数据的明显偏差,为长年代气候序列重建提供了一个可行的思路。      

FIO-ESM v2.0 CORE2-forced experiment for the CMIP6 Ocean Model Intercomparison Project

We introduced the Coupled Model Intercomparison Project Phase 6 (CMIP6) Ocean Model Intercomparison Project CORE2-forced (OMIP-1) experiment by using the First Institute of Oceanography Earth System Model version 2.0 (FIO-ESM v2.0), and comprehensively evaluated the simulation results. Unlike other OMIP models, FIO-ESM v2.0 includes a coupled ocean surface wave component model that takes into account non-breaking surface wave-induced vertical mixing in the ocean and effect of surface wave Stokes drift on air-sea momentum and heat fluxes in the climate system. A sub-layer sea surface temperature (SST) diurnal cycle parameterization was also employed to take into account effect of SST diurnal cycle on air-sea heat ?uxes to improve simulations of air-sea interactions. Evaluations show that mean values and long-term trends of significant wave height were adequately reproduced in the FIO-ESM v2.0 OMIP-1 simulations, and there is a reasonable fit between the SST diurnal cycle obtained from in situ observations and that parameterized by FIO-ESM v2.0. Evaluations of model drift, temperature, salinity, mixed layer depth, and the Atlantic Meridional Overturning Circulation show that the model performs well in the FIO-ESM v2.0 OMIP-1 simulation. However, the summer sea ice extent of the Arctic and Antarctic is underestimated.     

Comparison of coupled and uncoupled models in simulating Monsoon Intraseasonal Oscillation from CMIP6

The monsoon intraseasonal oscillation (MISO) is the dominant variability over the Indian Ocean during the Indian summer monsoon (ISM) season and is characterized by pronounced northward propagation. Previous studies have shown that general circulation models (GCMs) still have difficulty in simulating the northward-propagating MISO, and that the role of air-sea interaction in MISO is unclear. In this study, 14 atmosphere-ocean coupled GCMs (CGCMs) and the corresponding atmosphere-only GCMs (AGCMs) are selected from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) to assess their performance in reproducing MISO and the associated vortex tilting mechanism. The results show that both CGCMs and AGCMs are able to well simulate the significant relationship between MISO and vortex tilting. However, 80% of CGCMs show better simulation skills for MISO than AGCMs in CMIP6. In AGCMs, the poor model fidelity in MISO is due to the failure simulation of vortex tilting. Moreover, it is found that failure to simulate the downward motion to the north of convection is responsible for the poor simulation of vortex tilting in AGCMs. In addition, it is observed that there is a significant relationship between the simulated sea surface temperature gradient and simulated vertical velocity shear in the meridional direction. These findings indicate that air-sea interaction may play a vital role in simulating vertical motions in tilting and MISO processes. This work offers us a specific target to improve the MISO simulation and further studies are needed to elucidate the physical processes of this air-sea interaction coupling with vortex tilting.     

CMIP5全球气候模式对中国地区干旱变化模拟能力评估

利用东亚地区1961～2005年高分辨率（0．5°×0．5°）降水格点数据和参加CMIP5的42个全球气候模式数值模拟结果,通过对简单降水强度指数（降水距平百分率）的计算,对比分析了观测和多模式集合的中国地区干旱面积、干旱频率的时空分布以及干旱分布型的变化,评估了全球气候模式的模拟能力。结果表明：多个全球气候模式的集合结果对中国区域的干旱变化特征有一定的模拟能力,能较好地模拟出中国年平均干旱指数的时间变化趋势,但模拟的干旱强度偏弱;多模式集合模拟的严重干旱面积与观测值的变化趋势基本一致,与观测相比,模拟的长江以南干旱强度偏强,西北干旱强度偏弱;通过EOF的分析表明,多模式集合可以较好地模拟出西北与长江以南呈反位相及我国东部地区的“旱-涝-旱”或“涝-旱-涝”的分布型。     

Robustness of Precipitation Projections in China:Comparison between CMIP5 and CMIP3 Models

Three sources of uncertainty in model projections of precipitation change in China for the 21st century were separated and quantified: internal variability,inter-model variability,and scenario uncertainty.Simulations from models involved in the third phase and the fifth phase of the Coupled Model Intercomparison Project(CMIP3 and CMIP5) were compared to identify improvements in the robustness of projections from the latest generation of models.No significant differences were found between CMIP3 and CMIP5 in terms of future precipitation projections over China,with the two datasets both showing future increases.The uncertainty can be attributed firstly to internal variability,and then to both inter-model and internal variability.Quantification analysis revealed that the uncertainty in CMIP5 models has increased by about 10%–60% with respect to CMIP3,despite significant improvements in the latest generation of models.The increase is mainly due to the increase of internal variability in the initial decades,and then mainly due to the increase of inter-model variability thereafter,especially by the end of this century.The change in scenario uncertainty shows no major role,but makes a negative contribution to begin with,and then an increase later.     

Assessment of Historical Climate Trends of Surface Air Temperature in CMIP5 Models

This study assesses the historical climate trends of surface air temperature（SAT）, their spatial distributions, and the hindcast skills for SAT during 1901– 2000 from 24 Coupled Model Intercomparison Project Phase 5（CMIP5） models. For the global averaged SAT, most of the models（17/24） effectively captured the increasing trends（0.64°C/century for the ensemble mean） as the observed values（- 0.6°C/century） during the period of 1901–2000, particularly during a rapid warming period of 1970–2000 with the small model spread. In addition, most of the models（22/24） showed high hindcast skills（the correlation coefficient, R 〉 0.8）. For the spatial pattern of SAT, the models better simulated the relatively larger warming at the middle-to-high latitudes in the Northern Hemisphere than that in the Southern Hemisphere and the greater warming on the land than that in the ocean between 40°S and 40°N. The simulations underestimated the warming along some ocean boundaries but overestimated warming in the Arctic Ocean. Most of the coupled models were able to reproduce the large-scale features of SAT trends in most regions excluding Antarctica, some parts of the Pacific Ocean, the North Atlantic Ocean near Greenland, the southwestern Indian Ocean, and the Arctic Ocean. The outgoing longwave radiation（OLR） and incoming shortwave radiation（ISR） at the top of the atmosphere（TOA） and the downward longwave（LW） radiation and sensible heat flux at the surface had positive contributions to the increasing trends in most of the models.     

The Role of the Aerosol Indirect Effect in the Northern Indian Ocean Warming Simulated by CMIP5 Models

The northern Indian Ocean （NIO） experienced a decadal-scale persistent warming from 1950 to 2000, which has influenced both regional and global climate. Because the NIO is a region susceptible to aerosols emis- sion changes, and there are still large uncertainties in the representation of the aerosol indirect effect （ALE） in CMIP5 （Coupled Model Intercomparison Project Phase 5） models, it is necessary to investigate the role of the AIE in the NIO warming simulated by these models. In this study, the authors select seven CMIP5 models with both the aerosol direct and indirect effects to investigate their performance in simulating the basin-wide decadal-scale NIO warming. The results show that the decreasing trend of the downwelling shortwave flux （FSDS） at the surface has the major damping effect on the SST increasing trend, which counteracts the warming effect of greenhouse gases （GHGs）. The FSDS decreasing trend is mostly contrib- uted by the decreasing trend of cloudy-sky surface downwelling shortwave flux （FSDSCL）, a metric used to measure the strength of the AIE, and partly by the clear-sky surface downwelling shortwave flux （FSDSC）. Models with a relatively weaker AIE can simulate well the SST increasing trend, as compared to observation. In contrast, models with a relatively stronger AIE produce a much smaller magnitude of the increasing trend, indicat- ing that the strength of the AIE in these models may be overestimated in the NIO.     

CMIP5/AMIP GCM simulations of East Asian summer monsoon

The East Asian summer monsoon （EASM） is a distinctive component of the Asian climate system and critically influences the economy and society of the region.To understand the ability of AGCMs in capturing the major features of EASM,10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project （CMIP5/AMIP）,which used observational SST and sea ice to drive AGCMs during the period 1979-2008,were evaluated by comparing with observations and AMIP Ⅱ simulations.The results indicated that the multi-model ensemble （MME） of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation,and shows the best skill in EASM simulation,better than the AMIP Ⅱ MME.As for the Meiyu/Changma/Baiyu rainbelt,the intensity of rainfall is underestimated in all the models.The biases are caused by a weak western Pacific subtropical high （WPSH） and accompanying eastward southwesterly winds in group Ⅰ models,and by a too strong and west-extended WPSH as well as westerly winds in group Ⅱ models.Considerable systematic errors exist in the simulated seasonal migration of rainfall,and the notable northward jumps and rainfall persistence remain a challenge for all the models.However,the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index （WNPMI）.