E1 Nifio-Southem Oscillation （ENSO） events significantly affect the year-by-year variations of the East Asian winter monsoon （EAWM）. However, the effect of La Nifia events on the EAWM is not a mirror image of that of E1 Nifio events. Although the EAWM becomes generally weaker during El Nifio events and stronger during La Nifia winters, the enhanced precipitation over the southeastern China and warmer surface air temperature along the East Asian coastline during E1 Nifio years are more significant. These asymmetric effects are caused by the asymmetric longitudinal positions of the western North Pacific （WNP） anticyclone during El Nifio events and the WNP cyclone during La Nifia events; specifically, the center of the WNP cyclone during La Nifia events is westward-shifted relat- ive to its El Nifio counterpart. This central-position shift results from the longitudinal shift of remote E1 Nifio and La Nifia anomalous heating, and asymmetry in the amplitude of local sea surface temperature anomalies over the WNP. However, such asymmetric effects of ENSO on the EAWM are barely reproduced by the atmospheric models of Phase 5 of the Coupled Model Intercomparison Project （CMIP5）, although the spatial patterns of anomalous circula- tions are reasonably reproduced. The major limitation of the CMIP5 models is an overestimation of the anomalous WNP anticyclone/cyclone, which leads to stronger EAWM rainfall responses. The overestimated latent heat flux an- omalies near the South China Sea and the northern WNP might be a key factor behind the overestimated anomalous circulations.
Based on satellite data and the estimated inversion strength(EIS) derived by Wood et al.(2006), a feasible and uncomplicated stratocumulus scheme is proposed, referred to as EIS scheme. It improves simulation of cloud radiative forcing(CRF) in the Grid-point Atmospheric Model of IAP/LASG version 2(GAMIL2.0) model. When compared with the original lower troposphere stability(LTS) scheme, the EIS scheme reproduces more reasonable climatology distributions of clouds and CRF. The parameterization partly corrects CRF underestimation at mid and high latitudes and overestimation in the convective region. Such improvements are achieved by neglecting the effect of free-tropospheric stratification changes that follow a cooler moist adiabat at middle and high latitude, thereby improving simulated cloudiness. The EIS scheme also improves simulation of the CRF interannual variability. The positive net CRF and negative stratiform anomaly in the East Asian and western North Pacific monsoon regions(EAWNPMR) are well simulated. The EIS scheme is more sensitive to sea surface temperature anomalies(SSTA) than the LTS. Therefore, under the effect of a warmer SSTA in the EAWNPMR, the EIS generates a stronger negative stratiform response, which reduces radiative heating in the low and mid troposphere, in turn producing strong subsidence and negative anomalies of both moisture and cloudiness. Consequent decreases in cloud reflection and shading effects ultimately improve simulation of incoming surface shortwave radiative fluxes and CRF. Because of the stronger subsidence, a stronger anomalous anticyclone over the Philippines Sea is simulated by the EIS run, which leads to a better positive precipitation anomaly in eastern China during ENSO winter.
In order to assess the performance of two versions of the IAP/LASG Flexible Global Ocean-Atmosphere- Land System （FGOALS） model, simulated changes in surface air temperature （SAT）, from natural and an- thropogenie forcings, were compared to observations for the period 1850-2005 at global, hemispheric, conti- nental and regional scales. The global and hemispheric averages of SAT and their land and ocean components during 1850-2005 were well reproduced by FGOALS-g2, as evidenced by significant correlation coefficients and small RMSEs. The significant positive correlations were firstly determined by the warming trends, and secondly by interdecadal fluctuations. The abilities of the models to reproduce interdecadal SAT variations were demonstrated by both wavelet analysis and significant positive correlations for detrended data. The observed land-sea thermal contrast change was poorly simulated. The major weakness of FGOALS-s2 was an exaggerated warming response to anthropogenic forcing, with the simulation showing results that were far removed from observations prior to the 1950s. The observations featured warming trends （1906-2005） of 0.71, 0.68 and 0.79℃ （100 yr）-1 for global, Northern and Southern Hemispheric averages, which were overestimated by FGOALS-s2 [1.42, 1.52 and 1.13~C （100 yr）-1] but underestimated by FGOALS-g2 [0.69, 0.68 and 0.73~C （100 yr）-l]. The polar amplification of the warming trend was exaggerated in FGOALS- s2 but weakly reproduced in FGOALS-g2. The stronger response of FGOALS-s2 to anthropogenic forcing was caused by strong sea-ice albedo feedback and water vapor feedback. Examination of model results in 15 selected subcontinental-scale regions showed reasonable performance for FGOALS-g2 over most regions. However, the observed warming trends were overestimated by FGOALS-s2 in most regions. Over East Asia, the meridional gradient of the warming trend simulated by FGOALS-s2 （FGOALS-g2） was stronger （weaker） than observed.
An overview of Chinese contribution to Coupled Model Intercomparison Project-Phase 5 （CMIP5） is presented. The performances of five Chinese Climate/Earth System Models that participated in the CMIP5 pro ject are assessed in the context of climate mean states, seasonal cycle, intraseasonal oscillation, interan-nual variability, interdecadal variability, global monsoon, Asian-Australian monsoon, 20th-century historical climate simulation, climate change pro jection, and climate sensitivity. Both the strengths and weaknesses of the models are evaluated. The models generally show reasonable performances in simulating sea surface tem-perature （SST） mean state, seasonal cycle, spatial patterns of Madden-Julian oscillation （MJO） amplitude and tropical cyclone Genesis Potential Index （GPI）, global monsoon precipitation pattern, El Ni-no-Southern Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO） related SST anomalies. However, the perfor-mances of the models in simulating the time periods, amplitude, and phase locking of ENSO, PDO time periods, GPI magnitude, MJO propagation, magnitude of SST seasonal cycle, northwestern Pacific mon-soon and North American monsoon domains, as well as the skill of large-scale Asian monsoon precipitation need to be improved. The model performances in simulating the time evolution and spatial pattern of the 20th-century global warming and the future change under representative concentration pathways pro jection are compared to the multimodel ensemble of CMIP5 models. The model discrepancies in terms of climate sensitivity are also discussed.
In this study, two modes of the Silk Road pattern were investigated using NCEP2 reanalysis data and the simulation produced by Spectral Atmospheric Circulation Model of IAP LASG, Version 2 （SAMIL2.0） that was forced by SST observation data. The horizontal distribution of both modes were reasonably reproduced by the simulation, with a pattern correlation coefficient of 0.63 for the first mode and 0.62 for the second mode. The wave train was maintained by barotropic energy conversion （denoted as CK） and baroclinic energy conversion （denoted as CP） from the mean flow. The distribution of CK was dominated by its meridional component （CKy） in both modes. When integrated spatially, CKx was more efficient than its zonal component （CKx） in the first mode but less in the second mode. The distribution and efficiency of CK were not captured well by SAMIL2.0. However, the model performed reasonably well at reproducing the distribution and efficiency of CP in both modes. Because CP is more efficient than CK, the spatial patterns of the Silk Road pattern were well reproduced. Interestingly, the temporal phase of the second mode was well captured by a single-member simulation. However, further analysis of other ensemble runs demonstrated that the successful reproduction of the temporal phase was a result of internal variability rather than a signal of SST forcing. The analysis shows that the observed temporal variations of both CP and CK were poorly reproduced, leading to the low accuracy of the temporal phase of the Silk Road pattern in the simulation.
The performances of four Chinese AGCMs participating in the Coupled Model Intercomparison Project Phase 5 （CMIP5） in the simulation of the boreal summer intraseasonal oscillation （BSISO） are assessed. The authors focus on the major characteristics of BSISO： the intensity, significant period, and propagation. The results show that the four AGCMs can reproduce boreal summer intraseasonal signals of precipitation; however their limitations are also evident. Compared with the Climate Prediction Center Merged Analysis of Precipitation （CMAP） data, the models underestimate the strength of the intraseasonal oscillation （ISO） over the eastern equatorial Indian Ocean （IO） during the boreal summer （May to October）, but overestimate the intraseasonal variability over the western Pacific （WP）. In the model results, the westward propagation dominates, whereas the eastward propagation dominates in the CMAP data. The northward propagation in these models is tilted southwest-northeast, which is also different from the CMAP result. Thus, there is not a northeast-southwest tilted rain belt revolution off the equator during the BSISO＇s eastward journey in the models. The biases of the BSISO are consistent with the summer mean state, especially the vertical shear. Analysis also shows that there is a positive feedback between the intraseasonal precipitation and the summer mean precipitation. The positive feedback processes may amplify the models＇ biases in the BSISO simulation.
The development of coupled earth/climate system models in China over the past 20 years is reviewed, including a comparison with other international models that participated in the Coupled Model Intercom- parison Project （CMIP） from phase 1 （CMIP1） to phase 4 （CMIP4）. The Chinese contribution to CMIP is summarized, and the major achievements from CMIP1 to CMIP3 are listed as a reference for assessing the strengths and weaknesses of Chinese models. After a description of CMIP5 experiments, the five Chinese models that participated in CMIP5 are then introduced. Furthermore, following a review of the current status of international model development, both the challenges and opportunities for the Chinese climate modeling community are discussed. The development of high-resolution climate models, earth system mod- els, and improvements in atmospheric and oceanic general circulation models, which are core components of earth/climate system models, are highlighted. To guarantee the sustainable development of climate system models in China, the need for national-level coordination is discussed, along with a list of the main compo- nents and supporting elements identified by the US National Strategy for Advancing Climate Modeling.
Using the reanalysis data and 20th century simulation of coupled model FGOALS_gl developed by LASG/IAP, we identified two distinct interannual modes of Northwestern Pacific Subtropical Anticyclone （NWPAC） by performing Empirical Orthogonal Function （EOF） analysis on 850 hPa wind field over the northwestern Pacific in summer. Based on the associated anoma- lous equatorial zonal wind, these two modes are termed as ＂Equatorial Easterly related Mode＂ （EEM） and ＂Equatorial Westerly related Mode＂ （EWM）, respectively. The formation mechanisms of these two modes are similar, whereas the maintenance mechanisms, dominant periods, and the relationships with ENSO are different. The EEM is associated with E1 Nifio decaying phase, with the anomalous anticyclone established in the preceding winter and persisted into summer through local positive air-sea feedback. By enhancing equatorial upwelling of subsurface cold water, EEM favors the transition of ENSO from E1 Nifio to La Nifia. The EWM is accompanied by the E1 Nifio events with long persistence, with the anomalous anticyclone formed in spring and strengthened in summer due to the warm Sea Surface Temperature anomalies （SSTA） forcing from the equatorial central-eastern Pacific. The model well reproduces the spatial patterns of these two modes, but fails to simulate the percentage variance accounted for by the two modes. In the NCEP reanalysis （model result）, EEM （EWM） appears as the first mode, which accounts for 35.6% （68.2%） of the total variance.
