The intraseasonal oscillation in ECHAM4 Part I: coupled to a comprehensive ocean model

This study discusses the representation of the intraseasonal oscillation (ISO) in three simulations with the ECHAM4 atmosphere general circulation model (GCM). First, the model is forced by AMIP sea surface temperatures (SST), then coupled to the OPYC3 global ocean GCM and third forced by OPYC3 SSTs to clarify possible air-sea interactions and connections of the ISO and the ENSO cycle. The simulations are compared to ECMWF reanalysis data and NOAA outgoing longwave radiation (OLR) observations. Although previous studies have shown that the ECHAM4 GCM simulates an ISO-like oscillation, the main deficits are an overly fast eastward propagation and an eastward displacement of the main ISO activity, which is shown with a composite analysis of daily data between 1984 to 1988 for the reanalysis and the AMIP simulation, 25 years of the coupled integration, and a five year subset of the coupled SST output used for the OPYC3 forced atmosphere GCM experiment. These deficits are common to many atmospheric GCMs. The composites are obtained by principal oscillation pattern (POP). The POPs are also used to investigate the propagation speed and the interannual variability of the main ISO activity. The present coupled model version reveals no clear improvements in the ISO simulation compared to the uncoupled version forced with OPYC3 SSTs, although it is shown that the modeled ISO influences the simulated high-frequency SST variability in the coupled GCM. Within the current analysis, ECHAM4 forced by AMIP SSTs provides the most reasonable ISO simulation. However, it is shown that the maximum amplitudes of the annual cycle of the ISO variability in all analyzed model versions are reached too late in the year (spring and summer) compared to the observations (winter and spring). Additionally, the ENSO cycle influences the interannual variability of the ISO, which is revealed by 20 years of daily reanalysis data and 100 years of the coupled integration. The ENSO cycle is simulated by the coupled model, although there is a roughly 1 K cold bias in the East Pacific in the coupled model. This leads to a diminished influence of the ENSO cycle on the spatial variability of the modeled ISO activity compared to observations. This points out the strong sensitivity of the SST on the ISO activity. Small biases in the SST appear to cause large deterioration in the modeled ISO.     

Discrepancies in Simulated Ocean Net Surface Heat Fluxes over the North Atlantic

The change in ocean net surface heat flux plays an important role in the climate system. It is closely related to the ocean heat content change and ocean heat transport, particularly over the North Atlantic, where the ocean loses heat to the atmosphere, affecting the AMOC (Atlantic Meridional Overturning Circulation) variability and hence the global climate. However, the difference between simulated surface heat fluxes is still large due to poorly represented dynamical processes involving multiscale interactions in model simulations. In order to explain the discrepancy of the surface heat flux over the North Atlantic, datasets from nineteen AMIP6 and eight highresSST-present climate model simulations are analyzed and compared with the DEEPC (Diagnosing Earth's Energy Pathways in the Climate system) product. As an indirect check of the ocean surface heat flux, the oceanic heat transport inferred from the combination of the ocean surface heat flux, sea ice, and ocean heat content tendency is compared with the RAPID (Rapid Climate Change-Meridional Overturning Circulation and Heat flux array) observations at 26°N in the Atlantic. The AMIP6 simulations show lower inferred heat transport due to less heat loss to the atmosphere. The heat loss from the AMIP6 ensemble mean north of 26°N in the Atlantic is about 10 W m^–2 less than DEEPC, and the heat transport is about 0.30 PW (1 PW = 10¹⁵ W) lower than RAPID and DEEPC. The model horizontal resolution effect on the discrepancy is also investigated. Results show that by increasing the resolution, both surface heat flux north of 26°N and heat transport at 26°N in the Atlantic can be improved.     

Intermodel Diversity of Simulated Long-term Changes in the Austral Winter Southern Annular Mode: Role of the Southern Ocean Dipole

The Southern Annular Mode(SAM)plays an important role in regulating Southern Hemisphere extratropical circulation.State-of-the-art models exhibit intermodel spread in simulating long-term changes in the SAM.Results from Atmospheric Model Intercomparison Project(AMIP)experiments from 28 models archived in CMIP5 show that the intermodel spread in the linear trend in the austral winter(June?July?August)SAM is significant,with an intermodel standard deviation of 0.28(10 yr)?1,larger than the multimodel ensemble mean of 0.18(10 yr)?1.This study explores potential factors underlying the model difference from the aspect of extratropical sea surface temperature(SST).Extratropical SST anomalies related to the SAM exhibit a dipole-like structure between middle and high latitudes,referred to as the Southern Ocean Dipole(SOD).The role of SOD-like SST anomalies in influencing the SAM is found in the AMIP simulations.Model performance in simulating the SAM trend is linked with model skill in reflecting the SOD?SAM relationship.Models with stronger linkage between the SOD and the SAM tend to simulate a stronger SAM trend.The explained variance is about 40%in the AMIP runs.These results suggest improved simulation of the SOD?SAM relationship may help reproduce long-term changes in the SAM.     

Evaluation of the interannual variability in the East Asian summer monsoon in AMIP and historical experiments of CAS FGOALS-f3-L

The evaluation of East Asian summer monsoon (EASM) simulations could improve our understanding of Asian monsoon dynamics and climate simulations. In this study, by using Phase 6 of the Coupled Model Intercomparison Project (CMIP6) experiments of the Atmospheric Model Intercomparison Project (AMIP) and historical runs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean–Atmosphere–Land System (FGOALS-f3-L) model, the model simulation skill for the interannual variability in the EASM was determined. According to multivariate empirical orthogonal function (MV-EOF) analysis, the major mode of the EASM mainly emerged as a Pacific-Japan pattern in the western Pacific accompanied by a local anticyclonic anomaly with a total variance of 24.6%. The historical experiment could suitably reproduce this spatial pattern and attained a closer total variance than that attained by the AMIP experiment. The historical experiment could also better simulate the time frequency of the EASM variability than the AMIP experiment. However, the phase of principal component 1 (PC1) was not suitably reproduced in the historical experiment since no initialization procedure was applied at the beginning of the integration in the historical simulation process, whereas the sea surface temperature (SST) was preset in the AMIP experiment. Further analysis revealed that air–sea interactions in the Indian Ocean and tropical western Pacific were important for the model to provide satisfactory EASM simulations, while El Niño–Southern Oscillation (ENSO) simulation was possibly related to the climate variability in the EASM simulations, which should be further analyzed.摘要对东亚夏季季风(EASM)模拟的评估可以提高我们对亚洲季风动力和气候模拟的理解. 在这项研究中, 通过使用中国科学院(CAS)全球海洋-大气-陆地系统(FGOALS-f3-L)模式参加的第六次耦合模式相互比较计划(CMIP6)中的大气模式相互比较计划(AMIP)和历史(historical)试验, 明确了EASM的年际变率的模拟能力. 通过多变量经验正交函数(MV-EOF)分析发现, 观测的EASM的主导模态为西太平洋上的太平洋-日本模态, 并伴有局部反气旋异常. 主导模态的方差贡献率为24.6%. 历史(historical)试验可以基本再现这种空间模态, 其方差贡献率较AMIP试验更接近于观测. 与AMIP试验相比, 历史(historical)试验还能更好地模拟EASM变率的时间频率. 然而, 由于历史(historical)模拟没有在积分开始时应用初始化过程, 而AMIP试验受到海表面温度(SST)的约束, 因此主成分(PC1)的位相在历史(historical)试验中没有得到较好地再现. 进一步分析发现, 印度洋和西太平洋热带地区的海气相互作用对EASM的模拟非常重要, 而EASM气候变率的模拟可能与厄尔尼诺-南方涛动(ENSO)的模拟能力有关, 这值得进一步分析.     

Madden–Julian Oscillation simulated in BCC climate models

This study evaluates the ability of four versions BCC (Beijing Climate Center or National Climate Center) models (BCC_AGCM2.1, BCC_AGCM2.2, BCC_CSM1.1 and BCC_CSM1.1m) in simulating the MJO phenomenon using the outputs of the AMIP (Atmospheric Model Intercomparison Project) and historical runs. In general, the models can simulate some major characteristics of the MJO, such as the intensity, the periodicity, the propagation, and the temporal/spatial evolution of the MJO signals in the tropics. There are still some biases between the models and the observation/reanalysis data, such as the overestimated total intraseasonal variability, but underestimated MJO intensity, shorter significant periodicity, and excessive westward propagation. The differences in the ability of simulating the MJO between AMIP and historical experiments are also significant. Compared to the AMIP runs, the total intraseasonal variability is reduced and more realistic, however the ratio between the MJO and its westward counterpart decreases in the historical runs. This unrealistic simulation of the zonal propagation might have been associated with the greater mean precipitation over the Pacific and corresponded to the exaggeration of the South Pacific Convergence Zone structure in precipitation mean state. In contrast to the T42 versions, the improvement of model resolution demonstrate more elaborate topography, but the enhanced westward propagation signals over the Arabia Sea followed. The underestimated (overestimated) MJO variability over eastern Indian Ocean (Pacific) was assumed to be associated with the mean state. Three sets of sensitive experiments using BCC_CSM1.1m turn out to support this argument.     

The two interannual variability modes of the Western North Pacific Subtropical High simulated by 28 CMIP5–AMIP models

Using the output of the Atmospheric Model Intercomparison Project (AMIP) experiments of 28 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), the models’ performances in the simulation of the two dominant interannual variability modes of the Western North Pacific Subtropical High (WNPSH) are investigated. In the observation, the positive phases of these two modes feature an anomalous anticyclone over the western North Pacific (WNP), but the first mode (M1) is closely connected with the sea surface temperature (SST) anomalies over the tropical Indian Ocean (TIO), the maritime continent (MC) and the equatorial central Pacific (CP), while the second mode (M2) is closely connected with the SST anomalies over the WNP. The M1 is well captured by the CMIP5–AMIP models forced by the historical SST, suggesting the M1 is an SST-forced mode. The CMIP5–AMIP models capture the close relationship of the M1 with the SST anomalies over the TIO, the MC and the CP. The forcing mechanisms of M1 in the CMIP5–AMIP models are consistent with the observation, including a Kelvin wave emanating from the TIO and a local Hadley circulation originating from the MC. Different from the high reproducibility of the M1, the M2 is only moderately reproduced by the multi-model ensemble (MME) mean of the CMIP5–AMIP models. The simulated anomalous WNPSH of the M2 is weaker and shifts southwestward in the MME and many individual models compared to the observation. Among the five anomalous WNPSH years associated with the M2, the MME captures the anomalous WNPSH only in 1993 and 1994 but not in 1980, 1981 and 1987. The partial reproducibility of the M2 by the CMIP5–AMIP models suggests the M2 is neither a pure atmospheric internal mode nor a pure SST-forced mode. The observed close relationship between the anomalous WNPSH and the WNP SST anomalies is underestimated by the CMIP5–AMIP models, suggesting the local SST–WNPSH relationship may depend on the air–sea interaction over the WNP.     

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）.     

Simulations of Eurasian Winter Temperature Trends in Coupled and Uncoupled CFSv2

Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled(atmosphere-only) and coupled(ocean–atmosphere) simulations by the Climate Forecast System, version 2(CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project(AMIP) runs forced with mean seasonal cycles of sea surface temperature(SST)and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually,and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time.The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.     

FGOALS海洋同化试验对西北太平洋夏季SST—降水关系的模拟评估

评估了耦合气候系统模式FGOALS海洋同化试验对西北太平洋夏季降水和SST相关关系的模拟技巧,并对比了相应的观测海温强迫试验（AMIP）和历史气候模拟试验结果。结果显示,FGOALS海洋同化试验对亚洲季风区大部分海域夏季SST年际变化有较高的模拟技巧,但其对菲律宾以东海域模拟技巧较低。在西北太平洋夏季降水-SST相关关系方面,同化试验部分地再现了南海和菲律宾以东海域降水超前SST变化1个月和同时二者的负相关关系,优于AMIP试验但逊于自由耦合模拟试验。同化试验对SST倾向-降水相关关系的模拟技巧亦介于AMIP试验和自由耦合试验之间。观测中,西北太平洋夏季降水与环流异常受日界线附近和赤道东印度洋海洋大陆地区海温异常的遥强迫,并通过改变到达海表的净短波辐射通量影响局地SST异常,导致局地海温-降水和局地海温倾向-降水的负相关关系。在AMIP试验中,遥强迫导致的西北太平洋地区环流异常较之观测偏弱,由于缺少局地海气耦合过程,在西北太平洋多数地区表现为海温对大气的强迫作用,即SST-降水正相关关系。FGOALS同化试验和自由耦合试验考虑了局地海气耦合过程,虽然低估了遥强迫对西北太平洋地区夏季环流异常的影响,依然部分模拟出局地降水-SST负相关关系但较之观测偏弱。同时,自由耦合试验高估了西北太平洋20°N以南地区海温异常对大气环流异常的强迫,使得其对中国南海和日本岛以南海域SST-降水负相关关系的模拟稍优于同化试验。     

North Pacific SST Forcing on the Central United States “Warming Hole” as Simulated in CMIP5 Coupled Historical and Uncoupled AMIP Experiments

The central United States experienced a cooling trend during the twentieth century, called the “warming hole,” most notably in the last quarter of the century when global warming accelerated. The coupled simulations of the models that participated in the Coupled Model Intercomparison Project, Phases 3 and 5 (CMIP3/5), have been unable to reproduce this abnormal cooling phenomenon satisfactorily. An unrealistic representation of the observed phasing of the Pacific Decadal Oscillation (PDO)—one of the proposed forcing mechanisms for the warming hole—in the models is considered to be one of the main causes of this effect. The CMIP5’s uncoupled Atmospheric Model Intercomparison Project (AMIP) experiment, whose duration approximately coincides with the peak warming hole cooling period, provides an opportunity, when compared with the coupled historical experiment, to examine the role of the variation in Pacific Ocean sea surface temperature (SST) in the warming hole’s formation and also to assess the skill of the models in simulating the teleconnection between Pacific SST and the continental climate in North America. Accordingly, this study compared AMIP and historical runs in the CMIP5 suite thereby isolating the role of SST forcing in the formation of the warming hole and its maintenance mechanisms. It was found that, even when SST forcing in the AMIP run was “perfectly” prescribed in the models, the skill of the models in simulating the warming hole cooling in the central United States showed little improvement over the historical run, in which SST is calculated interactively, even though the AMIP run overestimated the anti-correlation between temperature in the central United States and the PDO index. The fact that better simulation of the PDO phasing in the AMIP run did not translate into an improved summer cooling trend in the central United States suggests that the inability of the coupled CMIP5 models to reproduce the warming hole under the historical run is not mainly a result of the mismatch between simulated and observed PDO phasing, as believed.     

Iap general circulation models: a first step towards developing a local area model for weather prediction in nigeria

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A Coupling Experiment of an Atmosphere and an Ocean Model with a Monthly Anomaly Exchange Scheme

A nine-layer spectral atmospheric general circulation model is coupled to a twenty-layer global oceanic general circulation model with the “prediction-correction” monthly anomaly exchange scheme which has been proposed at the Institute of Atmospheric Physics (IAP). A forty-year integration of the coupled model shows that the CGCM is fairly successful in keeping a reasonable pattern of the modelled SST although most of the Pacific become warmer than those given by the uncoupled ocean model. The model tends to reach a more realistic state than the uncoupled one in terms of downward surface heat flux into ocean particularly in the equatorial Pacific region. Also, the model is capable to simulate interannual variability of sea surface temperature in tropical region.     

The intraseasonal oscillation in ECHAM4 Part II: sensitivity studies

The focus is on sensitivity studies to identify factors that increase the skill of the ECHAM4 atmosphere general circulation model (GCM) in representing the intraseasonal oscillation (ISO). The ISO mode is dominated by an eastward propagating oscillation during boreal winter, also known as the Madden-Julian oscillation. A previous study compared observations and reanalysis data to uncoupled and coupled versions of the ECHAM4 GCM. The sensitivity experiments in the present study use those results to assess the importance of the following mechanisms for the simulation of the ISO. First, the vertical resolution is increased to indicate the effect of improved representation of the tropospheric stratification. Second, the horizontal resolution is increased to investigate the importance of the ratio of vertical and horizontal resolution. Third, the effects of the land-sea distribution are studied in an experiment with land points associated with the maritime continent replaced by sea points. Fourth, the ECHAM4 GCM is forced by a T42 version of the observed optimum interpolated SST (OISST) dataset as used in the ECMWF reanalysis to study the influence of the SST as a boundary condition. In addition to integrations with monthly mean SSTs, also an experiment with weekly mean SSTs is examined. The increased vertical resolution slightly slows down the propagation speed of the simulated ISO. Increasing the horizontal resolution from T42 to T106 results in a very noisy and therefore poorer simulation of the ISO. It is suggested that this is due to an inappropriate ratio of vertical and horizontal resolution. Replacing the land points associated with the maritime continent with sea points leads to a more realistic representation of convection over the maritime continent than in the standard model. A consequence is a reduction of the erroneous eastward shift of the simulated ISO activity, although the phase speed of the ISO is simultaneously increased. ECHAM4 forced by an OISST dataset interpolated to the models T42 grid leads to the strongest improvements, since the annual mean AMIP SST averaged over the maritime continent region is 0.14 K warmer than the OISST, and individual grid points can be more than 0.5 K warmer. The reason is that the AMIP SST uses only measurements over water for grid points that are partly covered by land, whereas the OISST also blends these measurements with measurements over the land portions. ECHAM4 forced by the interpolated OISST, which is in the mean only 0.04 K colder over the maritime continent than the OISST, produces a reasonable ISO with a mean period of 40 days for a forcing with monthly mean SSTs and 48 days for a forcing with weekly mean SSTs. These results illustrate the strong influence of the details of the prescribed SST on the simulation of the ISO.     

The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST

The impact of realistic atmospheric initialisation on the seasonal prediction of tropical Pacific sea surface temperatures is explored with the Predictive Ocean–Atmosphere Model for Australia (POAMA) dynamical seasonal forecast system. Previous versions of POAMA used data from an Atmospheric Model Intercomparison Project (AMIP)-style simulation to initialise the atmosphere for the hindcast simulations. The initial conditions for the hindcasts did not, therefore, capture the true intra-seasonal atmospheric state. The most recent version of POAMA has a new Atmosphere and Land Initialisation scheme (ALI), which captures the observed intra-seasonal atmospheric state. We present the ALI scheme and then compare the forecast skill of two hindcast datasets, one with AMIP-type initialisation and one with realistic initial conditions from ALI, focussing on the prediction of El Niño. For eastern Pacific (Niño3) sea surface temperature anomalies (SSTAs), both experiments beat persistence and have useful SSTA prediction skill (anomaly correlations above 0.6) at all lead times (forecasts are 9 months duration). However, the experiment with realistic atmospheric initial conditions from ALI is an improvement over the AMIP-type initialisation experiment out to about 6 months lead time. The improvements in skill are related to improved initial atmospheric anomalies rather than an improved initial mean state (the forecast drift is worse in the ALI hindcast dataset). Since we are dealing with a coupled system, initial atmospheric errors (or differences between experiments) are amplified though coupled processes which can then lead to long lasting errors (or differences).     

Northern Hemisphere atmospheric blocking as simulated by 15 atmospheric general circulation models in the period 1979–1988

 As a part of the Atmospheric Model Intercomparison Project (AMIP), the behaviour of 15 general circulation models has been analysed in order to diagnose and compare the ability of the different models in simulating Northern Hemisphere midlatitude atmospheric blocking. In accordance with the established AMIP procedure, the 10-year model integrations were performed using prescribed, time-evolving monthly mean observed SSTs spanning the period January 1979–December 1988. Atmospheric observational data (ECMWF analyses) over the same period have been also used to verify the models results. The models involved in this comparison represent a wide spectrum of model complexity, with different horizontal and vertical resolution, numerical techniques and physical parametrizations, and exhibit large differences in blocking behaviour. Nevertheless, a few common features can be found, such as the general tendency to underestimate both blocking frequency and the average duration of blocks. The problem of the possible relationship between model blocking and model systematic errors has also been assessed, although without resorting to ad-hoc numerical experimentation it is impossible to relate with certainty particular model deficiencies in representing blocking to precise parts of the model formulation. Received: 16 July 1997/Accepted: 20 October 1997     

An analysis of seasonal predictability in coupled model forecasts

In the recent decade, operational seasonal prediction systems based on initialized coupled models have been developed. An analysis of how the predictability of seasonal means in the initialized coupled predictions evolves with lead-time is presented. Because of the short lead-time, such an analysis for the temporal behavior of seasonal predictability involves a mix of both the predictability of the first and the second kind. The analysis focuses on the lead-time dependence of ensemble mean variance, and the forecast spread. Further, the analysis is for a fixed target season of December?CJanuary?CFebruary, and is for sea surface temperature, rainfall, and 200-mb height. The analysis is based on a large set of hindcasts from an initialized coupled seasonal prediction system. Various aspects of predictability of the first and the second kind are highlighted for variables with long (for example, SST), and fast (for example, atmospheric) adjustment time scale. An additional focus of the analysis is how the predictability in the initialized coupled seasonal predictions compares with estimates based on the AMIP simulations. The results indicate that differences in the set up of AMIP simulations and coupled predictions, for example, representation of air?Csea interactions, and evolution of forecast spread from initial conditions do not change fundamental conclusion about the seasonal predictability. A discussion of the analysis presented herein, and its implications for the use of AMIP simulations for climate attribution, and for time-slice experiments to provide regional information, is also included.     

Sources of systematic errors in the climatology of a regional climate model over Europe

 Two ten-year simulations made with a European regional climate model (RCM) are compared. They are driven by the same observed sea surface temperatures but use different lateral boundary forcing. For one simulation, RCM AMIP, this forcing is obtained from a standard integration of a global general circulation model (GCM AMIP), whereas for the other simulation, RCM ASSIM, it is derived from a time series of operational analyses. The archive of analysis fields (surface pressure plus winds and temperatures on various pressure levels) is not sufficiently comprehensive to provide directly the full set of driving fields required for the RCM (in particular, no moisture fields are present), so these are obtained via a GCM integration, GCM ASSIM, in which the model is continuously relaxed towards the analysis fields using a data assimilation technique. Errors in RCM AMIP can arise either from the internal RCM physics or from errors in the lateral boundary forcing inherited from GCM AMIP. Errors in RCM ASSIM can arise from the internal RCM physics or the boundary moisture forcing but not from the driving circulation. Although previous studies have considered RCM integrations driven either by output from standard GCM integrations or operational analyses, our study is the first to compare parallel integrations of each type. This allows the total systematic error in an RCM integration driven by standard GCM output to be partitioned into components arising from the driving circulation and the internal RCM physics. These components indicate the scope for reducing regional simulation biases by improving either the driving GCM or the RCM itself. The results relate mainly to elements of surface climate likely to be influenced by both the driving circulation and regional physical processes operating in the RCM. For cloud cover, errors are found to arise largely from the internal RCM physics. Values are too low despite a positive relative humidity bias, indicating shortcomings in the parametrisation scheme used to calculate cloud cover. In summer, surface temperature and precipitation errors are also explained principally by regional processes. For example excessive solar heating leads to anomalously high surface temperatures over southern Europe and excessive drying of the soil reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing also exerts some influence, mainly via a tropospheric cold bias which partially offsets the warming over southern Europe and also increases precipitation. In other seasons the lateral boundary forcing and the regional physics both contribute significantly to the errors in surface temperature and precipitation. In winter the boundary forcing (apart from moisture) is responsible for about 60% of the total error variance for temperature and about 40% for precipitation, due to the cold bias and circulation errors such as a southward shift in the storm track. The remaining errors arise from the regional physics, although for precipitation an excessive supply of moisture from the lateral boundaries also contributes. The skill of the mesoscale component of the surface temperature and precipitation distributions exceeds previous estimates, due to more realistic observed climatology. The mesoscale patterns are very similar in the two RCM simulations indicating that errors in the simulation of fine scale detail arise mainly from inadequate representations of local forcings rather than errors in the large-scale circulation. Circulation errors in RCM AMIP (e.g. cold bias, southward shift of storm track) are also present in GCM AMIP, but are largely absent in RCM ASSIM except in summer. This confirms evidence from previous work that the key to reducing most circulation errors in the RCM lies in improving the driving GCM. Regional processes only make a major contribution to circulation errors in summer, when reduced advection from the boundaries allows errors in surface temperature to be transmitted more effectively into the troposphere. Finally, we find evidence of error balances in the GCM which act to minimise biases in important climatological variables. This reflects tuning of the model physics at GCM resolution. In order to achieve simultaneous optimisation of the RCM and GCM at widely differing resolutions it may be necessary to introduce explicit scale dependences into some aspects of the physics. Received: 17 September 1997/Accepted: 10 March 1998     

FGOALS耦合模式对赤道太平洋海温和降水年循环的模拟评估

本文评估了中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室（LASG/IAP）研发的全球气候系统模式（FGOALS）的4个版本（FGOALS-g2、s2、g3、f3-L）对赤道太平洋地区的海温、降水气候态和季节循环的模拟能力。本文从海气耦合机制和热量收支的角度对耦合模式结果和相应的大气模式比较计划试验（AMIP）进行了对比分析,探讨了造成这一地区海温和降水模拟偏差的原因。结果显示,上一代模式g2和s2的海表温度均方根误差大于2°C,新一代模式g3和f3-L模拟的均方根误差降低50%,为1°C左右。因为新版本中赤道太平洋地区的净短波辐射平均态误差的减小,海洋上层热量动力输送过程的改善和净短波辐射与海温回归关系改进,赤道太平洋地区海温的平均态,南北温度和降水的不对称性都更加接近观测。f3-L比g3在上述方面改进更多,海温也更加合理。但是新一代版本模拟的降水均没有显著改进,赤道北侧ITCZ的降水偏大4 mm d?1。对流降水带来的凝结潜热释放加强了南北非绝热加热梯度,越赤道南风偏差抵消了一部分因为短波辐射偏大带来的海温偏暖,这说明海温平均态的改善是模拟误差相互抵消的结果。在季节循环的模拟方面也存在类似的现象,f3-L和g3中的海温年循环有所改进但较观测振幅仍旧偏弱。这是因为f3-L和g3模拟的经向风和潜热的年循环振幅比前版本要偏强,误差加大的同时也更大地抵消短波辐射的年循环偏差。g2和s2模拟的海温在赤道东太平洋则存在一个虚假半年循环分量,这主要是由潜热通量半年循环偏差所引起的。     

Climate mean,variability and dominant patterns of the Northern Hemisphere wintertime mean atmospheric circulation in the NCEP CFSv2

In this study, the climate mean, variability, and dominant patterns of the Northern Hemisphere wintertime mean 200 hPa geopotential height (Z200) in a CMIP and a set of AMIP simulations from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) are analyzed and compared with the NCEP/NCAR reanalysis. For the climate mean, it is found that a component of the bias in stationary waves characterized with wave trains emanating from the tropics into both the hemispheres can be attributed to the precipitation deficit over the Maritime continent. The lack of latent heating associated with the precipitation deficit may have served as the forcing of the wave trains. For the variability of the seasonal mean, both the CMIP and AMIP successfully simulated the geographical locations of the major centers of action, but the simulated intensity was generally weaker than that in the reanalysis, particularly for the center over the Davis Strait-southern Greenland area. It is also noted that the simulated action center over Aleutian Islands was southeastward shifted to some extent. The shift was likely caused by the eastward extension of the Pacific jet. Differences also existed between the CMIP and the AMIP simulations, with the center of actions over the Aleutian Islands stronger in the AMIP and the center over the Davis Strait-southern Greenland area stronger in the CMIP simulation. In the mode analysis, the El Nino-Southern Oscillation (ENSO) teleconnection pattern in each dataset was first removed from the data, and a rotated empirical orthogonal function (REOF) analysis was then applied to the residual. The purpose of this separation was to avoid possible mixing between the ENSO mode and those generated by the atmospheric internal dynamics. It was found that the simulated ENSO teleconnection patterns from both model runs well resembled that from the reanalysis, except for a small eastward shift. Based on the REOF modes of the residual data, six dominant modes of the reanalysis data had counterparts in each model simulation, though with different rankings in explained variance and some distortions in spatial structure. By evaluating the temporal coherency of the REOF modes between the reanalysis and the AMIP, it was found that the time series associated with the equatorially displaced North Atlantic Oscillation in the two datasets were significantly correlated, suggesting a potential predictability for this mode.     

A note on horizontal resolution dependence for monsoon rainfall simulations

Summary The motivation for this study came from recent results of an Atmospheric Model Inter-comparison Project (AMIP) coordinated by the Lawrence Livermore Laboratory at Livermore, California. That project included a review of seasonal monsoon simulations from 13 different atmospheric models over the world. Most of the models used a horizontal resolution of roughly 300 km. The seasonal monsoon simulations from these models varied significantly. The poor performance by these models stems in part from the use of the coarse resolution. The purpose of this note is to show that by using the same model physics and lower boundary conditions, such as snow/ice cover and sea surface temperatures, the use of the higher horizontal resolution does have a stronger positive impact on the skill of monthly rainfall when compared to a lower horizontal resolution. In this note we present the results of such a comparison between the horizontal resolutions of T42 and T170. These studies are carried out for the prescribed lower boundary specification of sea surface temperatures and snow/ice cover with the help of an Atmospheric General Circulation Model. Received August 16, 1999 Revised October 14, 1999