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1.
The impact of the interannual variability (IAV) of vegetation on the IAV of evapotranspiration is investigated with the Community Land Model (CLM3.0) and modified Dynamic Global Vegetation Model (DGVM). Two sets of 50-year off-line simulations are used in this study. The simulations begin with the same initial surface-water and heat states and are driven by the same atmospheric forcing data. The vegetation exhibits interannual variability in one simulation but not in the other simulation. However, the climatological means for the vegetation are the same. The IAV of the 50-year annual total evapotranspiration and its three partitions (ground evaporation, canopy evaporation, and transpiration) are analyzed. The global distribution of the evapotranspiration IAV and the statistics of evapotranspiration and its components in different ecosystems show that the IAV of ground evaporation is generally large in areas dominated by grass and deciduous trees, whereas the IAV of canopy evaporation and transpiration is large in areas dominated by bare soil and shrubs. For ground evaporation, canopy evaporation, and transpiration, the changes in IAV are larger than the mean state over most grasslands and shrublands. The study of two sites with the same IAV in the leaf area index (LAI) shows that the component with the smaller contribution to the total evapotranspiration is more sensitive to the IAV of vegetation. The IAV of the three components of evapotranspiration increases with the IAV of the fractional coverage (FC) and the LAI. The ground evaporation IAV shows the greatest increase, whereas the canopy evaporation shows the smallest increase.  相似文献   

2.
植被覆盖异常变化影响陆面状况的数值模拟   总被引：15，自引：2，他引：15  
利用NCAR最新的公用陆面模式CLM3．0，通过数值模拟初步研究了植被叶面积指数（LAI，leafareaindex）异常变化对陆面状况的可能影响，结果表明，植被LAI的异常变化能够引起地表能量平衡、地表水循环等陆面状况的异常。（1）植被LAI的异常变化主要影响太阳辐射在植被与地表之间的分配，以及地表的感热、潜热通量。植被LAI增大，能够引起植被吸收的太阳辐射增加，而到达土壤表面的太阳辐射减小，并导致植被的蒸发、蒸腾潜热通量增加，造成地表的蒸发潜热和感热通量不同程度的减小。（2）植被LAI增大时，植被对降水的拦截和植被叶面的蒸发增大，植被的蒸腾作用也明显增强；植被LAI增加会使得热带地区各个季节的土壤表面蒸发、地表径流减小，而土壤湿度有所增加；LAI增加造成中高纬度地区土壤蒸发的减少主要出现在夏季；LAI增加还能够引起中高纬地区冬、春积雪深度不同程度的增加，造成春末、夏初地表径流的增加。（3）植被LAI增加能够使得叶面和土壤温度有所下降，但植被LAI的变化对叶面、土壤温度的影响相对较小。  相似文献   

3.
Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model （NCEP/GCM T42L18） and the Simplified Simple Biosphere land surface scheme （SSiB） were carried out to investigate the climate impacts of fractional vegetation cover （FVC） and leaf area index （LAI） on East Asia summer precipitation, especially in the Yellow River Basin （YRB）. One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project （ISLSCP） for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature （SST） produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988 indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased, net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also contributed to the precipitation interannual variation.  相似文献   

4.
Many studies have investigated the influence of evapotranspiration and albedo and emphasize their separate effects but ignore their interactive influences by changing vegetation status in large amplitudes. This paper focuses on the comprehensive influence of evapotranspiration and albedo on surface temperature by changing the leaf area index(LAI) between 30–90 N.Two LAI datasets with seasonally different amplitudes of vegetation change between 30–90N were used in the simulations.Seasonal differences between the results of the simulations are compared, and the major findings are as follows.(1) The interactive effects of evapotranspiration and albedo on surface temperature were different over different regions during three seasons [March–April–May(MAM), June–July–August(JJA), and September–October–November(SON)], i.e., they were always the same over the southeastern United States during these three seasons but were opposite over most regions between30–90 N during JJA.(2) Either evapotranspiration or albedo tended to be dominant over different areas and during different seasons. For example, evapotranspiration dominated almost all regions between 30–90N during JJA, whereas albedo played a dominant role over northwestern Eurasia during MAM and over central Eurasia during SON.(3) The response of evapotranspiration and albedo to an increase in LAI with different ranges showed different paces and signals. With relatively small amplitudes of increased LAI, the rate of the relative increase in evapotranspiration was quick, and positive changes happened in albedo. But both relative changes in evapotranspiration and albedo tended to be gentle, and the ratio of negative changes of albedo increased with relatively large increased amplitudes of LAI.  相似文献   

5.
肖宇  马柱国  李明星 《大气科学》2017,41(1):132-146
本文将四个常见陆面模式CLM3.5（Community Land Model Version 3.5）、Noah_LSM（The Noah Land Surface Model）、VIC（Variable Infiltration Capacity）以及SSiB（The Simplified Simple Biosphere Model）中土壤湿度影响蒸散的参数化方案进行简化,并利用实验观测资料对不同参数化方案进行评估,探究不同陆面模式对土壤湿度与蒸散关系的模拟差异,从而为提高模式的模拟能力提供依据。结果表明,（1）CLM与SSiB中计算土壤湿度影响裸土蒸发的参数化方案较Noah_LSM和VIC更接近真实的物理过程,同时CLM与SSiB模式中土壤湿度对蒸发的影响程度较Noah_LSM和VIC大;而对于下垫面有植被条件下的蒸散而言,CLM中包含了植被光合作用、呼吸作用等生物物理学过程,与实际情况更为接近,并且CLM与SSiB中土壤湿度对植被蒸散的影响程度大于VIC,Noah_LSM最低;（2）根据干旱区、半干旱区、半湿润区以及湿润区各站点的分析可知,CLM、SSiB与Noah_LSM中土壤湿度影响蒸散的参数化方案的拟合效果较VIC好,同时在部分站点CLM与SSiB的参数化方案稍优于Noah_LSM。区域之间比较说明,四个模式对干旱半干旱区的模拟效果明显较半湿润区和湿润区好。  相似文献   

6.
The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM (“SPEEDY”) is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.  相似文献   

7.
Two land surface schemes, SCAM and CSIRO9, were used to model the measured energy fluxes during the OASIS (Observations At Several Interacting Scales) field program. The measurements were taken at six sites along a 100 km rainfall gradient. Two types of simulations were conducted: (1) offline simulations forced with measured atmospheric input data at each of the six sites, and (2) regional simulations with the two land surface schemes coupled to the regional climate model DARLAM.The two land surface schemes employ two different canopy modelling concepts: in SCAM the vegetation is conceptually above the ground surface, while CSIRO9 employs the more commonly used `horizontally tiled' approach in which the vegetation cover is modelled by conceptually placing it beside bare ground. Both schemes utilize the same below-ground components (soil hydrological and thermal models) to reduce the comparison to canopy processes only. However, the ground heat flux, soil evaporation and evapotranspiration are parameterised by the two canopy treatments somewhat differently.Both canopy concepts reproduce the measured energy fluxes. SCAM has a slightly higher root-mean standard error in the model-measurement comparison for the ground heat flux. The mean surface radiative temperature simulated by SCAM is approximately 1K lower than in the CSIRO9 simulations. However, the soil and vegetation temperatures (which contribute to the radiative temperature) varied more in the CSIRO9 simulations. These larger variations are due to the absence of a representation of the aerodynamic interactions between vegetation and ground.  相似文献   

8.
The abilities of 12 earth system models (ESMs) from the Coupled Model Intercomparison Project Phase5 (CMIP5) to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau (TP) were examined. The results show that most of the models tend to overestimate the observed leaf area index (LAI) and vegetation carbon above the ground, with the possible reasons being overestimation of photosynthesis and precipitation. The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005, while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions. Three of the models: CCSM4, CESM1-BGC, and NorESM1-ME, which share the same vegetation model, show some common strengths and weaknesses in their simulations according to our analysis. The model ensemble indicates a reasonable spatial distribution but overestimated land coverage, with a significant decreasing trend (-1.48% per decade) for tree coverage and a slight increasing trend (0.58% per decade) for bare ground during the period 1950-2005. No significant sign of variation is found for grass. To quantify the relative performance of the models in representing the observed mean state, seasonal cycle, and interannual variability, a model ranking method was performed with respect to simulated LAI. INMCM4, bcc-csm-1.1m, MPI-ESM-LR, IPSL CM5A-LR, HadGEM2-ES, and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.  相似文献   

9.
One deficiency of the NCAR Community Land Model (CLM3) is the disappearance of the simulated snow even in the middle of winter over a boreal grassland site due to unrealistically modeled high downward turbulent fluxes. This is caused by the inappropriate treatment of the vertical snow burial fraction for short vegetation. A new snow burial fraction formulation for short vegetation is then proposed and validated using in situ observations. This modification in the CLM3 largely removes the unrealistic surface turbulent fluxes, leading to a more reasonable snowmelt process, and improves the snow water equivalent (SWE) simulation. Moreover, global offline simulations show that the proposed formulation decreases sensible and latent heat fluxes as well as the ground temperature during the snowmelt season over short vegetation dominant regions. Correspondingly, the SWE is enhanced, leading to the increase in snowmelt-induced runoff during the same period. Furthermore, sensitivity tests indicate that these improvements are insensitive to the exact functional form or parameter values in the proposed formulation.  相似文献   

10.
ABSTRACT Canopy resistance substantially affects the partitioning of available energy over vegetated surfaces. This study analyzed the variability of canopy resistance and associated driving environmental factors over a desert steppe site in Inner Mongolia, China, through the use of eddy-flux and meteorological data collected from 2008 to 2010. Distinct seasonal and interannual variabilities in canopy resistance were identified within those three years, and these variabilities were controlled primarily by precipitation. Strong interannual variability was found in vapor pressure deficit （VPD）, similar to that of air temperature. Based on the principal component regression method, the analysis of the relative contribution of five major environmental factors [soil-water content （SWC）, leaf-area index （LAI）, photosynthetically active radiation （Kp）, VPD, and air temperature] to canopy resistance showed that the canopy-resistance variation was most responsive to SWC （with 〉 35% contribution）, followed by LAI, especially for water-stressed soil conditions （〉 20% influence）, and VPD （consistently with an influence of approximately 20%）. Canopy-resistance variations did not respond to Kp due to the small interannual variability in Kp during the three years. These analyses were used to develop a new exponential function of water stress for the widely used Jarvis scheme, which substantially improved the calculation of canopy resistance and latent heat fluxes, especially for moist and wet soils, and effectively reduced the high bias in evaporation estimated by the original Jarvis scheme. This study highlighted the important control of canopy resistance on plant evaporation and growth for the investigated desert steppe site with a relatively low LA1.  相似文献   

11.
The Met Office Hadley Centre Unified Model (HadAM3) with the tiled version of the Met Office Surface Exchange Scheme (MOSES2) land surface scheme is used to assess the impact of a comprehensive imposed vegetation annual cycle on global climate and hydrology. Two 25-year numerical experiments are completed: the first with structural vegetation characteristics (Leaf Area Index, LAI, canopy height, canopy water capacity, canopy heat capacity, albedo) held at annual mean values, the second with realistic seasonally varying vegetation characteristics. It is found that the seasonalities of latent heat flux and surface temperature are widely affected. The difference in latent heat flux between experiments is proportional to the difference in LAI. Summer growing season surface temperatures are between 1 and 4 K lower in the phenology experiment over a majority of grid points with a significant vegetation annual cycle. During winter, midlatitude surface temperatures are also cooler due to brighter surface albedo over low LAI surfaces whereas during the dry season in the tropics, characterized by dormant vegetation, surface temperatures are slightly warmer due to reduced transpiration. Precipitation is not as systematically affected as surface temperature by a vegetation annual cycle, but enhanced growing season precipitation rates are seen in regions where the latent heat flux (evaporation) difference is large. Differences between experiments in evapotranspiration, soil moisture storage, the timing of soil thaw, and canopy interception generate regional perturbations to surface and sub-surface runoff annual cycles in the model.  相似文献   

12.
Incorporating organic soil into a global climate model   总被引：3，自引：1，他引：2  
Organic matter significantly alters a soil’s thermal and hydraulic properties but is not typically included in land-surface schemes used in global climate models. This omission has consequences for ground thermal and moisture regimes, particularly in the high-latitudes where soil carbon content is generally high. Global soil carbon data is used to build a geographically distributed, profiled soil carbon density dataset for the Community Land Model (CLM). CLM parameterizations for soil thermal and hydraulic properties are modified to accommodate both mineral and organic soil matter. Offline simulations including organic soil are characterized by cooler annual mean soil temperatures (up to ∼2.5°C cooler for regions of high soil carbon content). Cooling is strong in summer due to modulation of early and mid-summer soil heat flux. Winter temperatures are slightly warmer as organic soils do not cool as efficiently during fall and winter. High porosity and hydraulic conductivity of organic soil leads to a wetter soil column but with comparatively low surface layer saturation levels and correspondingly low soil evaporation. When CLM is coupled to the Community Atmosphere Model, the reduced latent heat flux drives deeper boundary layers, associated reductions in low cloud fraction, and warmer summer air temperatures in the Arctic. Lastly, the insulative properties of organic soil reduce interannual soil temperature variability, but only marginally. This result suggests that, although the mean soil temperature cooling will delay the simulated date at which frozen soil begins to thaw, organic matter may provide only limited insulation from surface warming.  相似文献   

13.
The coupled models of both the Global Ocean-Atmosphere-Land System (GOALS) and the Atmosphere-Vegetation Interaction Model (GOALS-AVIM) are used to study the main characteristics of interannual variations. The simulated results are also used to investigate some significant interannual variability and correlation analysis of the atmospheric circulation and terrestrial ecosystem. By comparing the simulations of the climate model GOALS-AVIM and GOALS, it is known that the simulated results of the interannual variations of the spatial and temporal distributions of the surface air temperatures and precipitation are generally improved by using AVIM in GOALS-AVIM. The interannual variation displays some distinct characteristics of the geographical distribution. Both the Net Primary Production (NPP) and the Leap Area Index (LAI) have quasi 1-2-year cycles. Meanwhile, precipitation and the surface temperatures have 2--4-year cycles. Conditions when the spectrum density values of GOALS are less than those of GOALS-AVIM, tell us that the model coupled with AVIM enhances the simulative capability for interannual variability and makes the annual cycle variability more apparent. Using Singular Value Decomposition (SVD) analysis, the relationship between the ecosystem and the atmospheric circulation in East Asia is explored. The result shows that the strengthening and weakening of the East Asian monsoon, characterized by the geopotential heights at 500 hPa and the wind fields at 850 hPa, correspond to the spatiotemporal pattern of the NPP. The correlation between NPP and the air temperature, precipitation and solar radiation are different in interannual variability because of the variation in vegetation types.  相似文献   

14.
The Community Climate Model Version 3.6 is used to simulate the mean climate of West Africa during the Northern Hemisphere summer season (June-August). The climate model uses prescribed climatological sea surface temperatures (SSTs) and observed SSTs during the 1979-1993 period. Two important circulation features, the African Easterly Jet (AEJ) and the Tropical Easterly Jet (TEJ), are found in the simulations but a westerly wind bias is found with respect to 700 hPa winds. Consequently, easterly waves and rain rates are poorly simulated. The primary cause of the poorly simulated AEJ is the advection of cold air from Europe producing a cold bias over northern Africa and a weaker than observed meridional temperature gradient. The cold bias is caused by an eastward displacement of the simulated Azores surface high into Western Europe creating a stronger than observed meridional sea level pressure gradient over northern Africa. This bias systematically occurs in simulations using both climatological and observed SSTs. The biases in sea level pressure, temperature and zonal winds have the potential to produce poor regional climate model results for West Africa if the meteorological output from the CCM3 is used as lateral boundaries. Moreover, these biases introduce uncertainties to West African GCM sensitivity studies associated with interannual variability, land-use change and elevated anthropogenic greenhouse gases.  相似文献   

15.
全球植被年际尺度动态过程的数值模拟及其评估   总被引：1，自引：1，他引：0  
动态植被模型（Interactive Canopy Model,ICM）中考虑了生态系统碳氮循环过程,能够描述较短时间尺度上的植被与大气之间相互作用过程。利用21 a的GIMMS卫星观测LAI资料,与ICM模拟结果进行年际变率对比分析,评估模型对植被年际变化的模拟性能。结果表明,ICM能在一定程度上反映植被年际变率的空间分布特征,但模拟的热带部分地区植被的年际变率偏小,除此之外大部分地区模拟的年际变率偏大;模拟能够反映出全球植被年际变化的主要空间分布型,同时低纬度地区植被的时间演变特征要好于高纬度地区;ICM对寒带灌丛、北非稀树大草原、落叶针叶林的年际变化模拟较好,但对中国东部农作物的模拟表现出了明显的周期振荡现象,与实际情况差距较大。  相似文献   

16.
The Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM) is a newly developed global climate model that will participate in the Coupled Model Intercomparison Project phase 6. Based on historical simulations (1900?2013), we evaluate the model performance in simulating the observed characteristics of the Arctic climate system, which includes air temperature, precipitation, the Arctic Oscillation (AO), ocean temperature/salinity, the Atlantic meridional overturning circulation (AMOC), snow cover, and sea ice. The model?data comparisons indicate that the CAMS-CSM reproduces spatial patterns of climatological mean air temperature over the Arctic (60°?90°N) and a rapid warming trend from 1979 to 2013. However, the warming trend is overestimated south of the Arctic Circle, implying a subdued Arctic amplification. The distribution of climatological precipitation in the Arctic is broadly captured in the model, whereas it shows limited skills in depicting the overall increasing trend. The AO can be reproduced by the CAMS-CSM in terms of reasonable patterns and variability. Regarding the ocean simulation, the model underestimates the AMOC and zonally averaged ocean temperatures and salinity above a depth of 500 m, and it fails to reproduce the observed increasing trend in the upper ocean heat content in the Arctic. The large-scale distribution of the snow cover extent (SCE) in the Northern Hemisphere and the overall decreasing trend in the spring SCE are captured by the CAMS-CSM, while the biased magnitudes exist. Due to the underestimation of the AMOC and the poor quantification of air–sea interaction, the CAMS-CSM overestimates regional sea ice and underestimates the observed decreasing trend in Arctic sea–ice area in September. Overall, the CAMS-CSM reproduces a climatological distribution of the Arctic climate system and general trends from 1979 to 2013 compared with the observations, but it shows limited skills in modeling local trends and interannual variability.  相似文献   

17.
We compare the ability of coupled global climate models from the phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6, respectively) in simulating the temperature and precipitation climatology and interannual variability over China for the period 1961–2005 and the climatological East Asian monsoon for the period1979–2005. All 92 models are able to simulate the geographical distribution of the above variables reasonably well.Compared with earlier CMIP5 models, current CMIP6 models have nationally weaker cold biases, a similar nationwide overestimation of precipitation and a weaker underestimation of the southeast–northwest precipitation gradient, a comparable overestimation of the spatial variability of the interannual variability, and a similar underestimation of the strength of winter monsoon over northern Asia. Pairwise comparison indicates that models have improved from CMIP5 to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon. The ability of models relates to their horizontal resolutions in certain aspects. Both the multi-model arithmetic mean and median display similar skills and outperform most of the individual models in all considered aspects.  相似文献   

18.
The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941  相似文献   

19.
本文利用37个CMIP5模式和CESM（Community Earth System Model）包含40个成员的超级集合试验的表面气温预估数据，比较了工业革命前气候参照试验、多项式拟合法和方差分析方法这三种目前在国际上运用较多的方法所估算的表面气温内部变率的异同，分析了内部变率的估算对气候预估中信号萌芽时间（TOE）的影响。结果表明:若采用CMIP5多模式集合，则工业革命前气候参照试验和多项式拟合法都是估算内部变率的合理方法，而方差分析方法则由于包含模式性能自身的影响会夸大内部变率故不推荐使用。内部变率的全球分布呈现出极向强化的现象，中高纬度地区的内部变率幅度远大于热带、副热带地区。内部变率受不同排放情景的影响较小，且随时间无显著变化，但方差分析方法估算的内部变率在热带地区容易受到排放情景的影响。若基于类似CESM这样的单个气候模式的超级集合模拟试验来估算内部变率，三种方法估算的结果相似。不同方法估算的内部变率对TOE的影响主要位于北大西洋拉布拉多海、南大洋威德尔海和罗斯海等邻近海洋深对流区。对于中国区域平均来说，基于CESM超级集合模拟试验，三种方法估算的内部变率与强迫信号之比都小于15%；对CMIP5多模式集合，采用工业革命前气候参照试验和多项式拟合法得到的结果与此接近，但若采用方差分析方法则显著高估内部变率的作用。  相似文献   

20.
This study examines the ability of Community Atmosphere Model (CAM) and Community Climate System Model (CCSM) to simulate the Asian summer monsoon, focusing particularly on inter-model comparison and the role of air–sea interaction. Two different versions of CAM, namely CAM4 and CAM5, are used for uncoupled simulations whereas coupled simulations are performed with CCSM4 model. Ensemble uncoupled simulations are performed for a 30 year time period whereas the coupled model is integrated for 100 years. Emphasis is placed on the simulation of monsoon precipitation by analyzing the interannual variability of the atmosphere-only simulations and sea surface temperature bias in the coupled simulation. It is found that both CAM4 and CAM5 adequately simulated monsoon precipitation, and considerably reduced systematic errors that occurred in predecessors of CAM4, although both tend to overestimate monsoon precipitation when compared with observations. The onset and cessation of the precipitation annual cycle, along with the mean climatology, are reasonably well captured in their simulations. In terms of monsoon interannual variability and its teleconnection with SST over the Pacific and Indian Ocean, both CAM4 and CAM5 showed modest skill. CAM5, with revised model physics, has significantly improved the simulation of the monsoon mean climatology and showed better skill than CAM4. Using idealized experiments with CAM5, it is seen that the adoption of new boundary layer schemes in CAM5 contributes the most to reduce the monsoon overestimation bias in its simulation. In the CCSM4 coupled simulations, several aspects of the monsoon simulation are improved by the inclusion of air–sea interaction, including the cross-variability of simulated precipitation and SST. A significant improvement is seen in the spatial distribution of monsoon mean climatology where a too-heavy monsoon precipitation, which occurred in CAM4, is rectified. A detailed investigation of this significant precipitation reduction showed that the large systematic cold SST errors in the Northern Indian Ocean reduces monsoon precipitation and delays onset by weakening local evaporation. Sensitivity experiments with CAM4 further confirmed these results by simulating a weak monsoon in the presence of cold biases in the Northern Indian Ocean. It is found that although the air–sea coupling rectifies the major weaknesses of the monsoon simulation, the SST bias in coupled simulations induces significant differences in monsoon precipitation. The overall simulation characteristics demonstrate that although the new model versions CAM4, CAM5 and CCSM4, are significantly improved, they still have major weaknesses in simulating Asian monsoon precipitation.  相似文献   

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