Asian monsoon simulations by Community Climate Models CAM4 and CCSM4

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.     

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.     

Roles of Indian and Pacific Ocean air–sea coupling in tropical atmospheric variability

Sea surface temperature (SST) variations include negative feedbacks from the atmosphere, whereas SST anomalies are specified in stand-alone atmospheric general circulation simulations. Is the SST forced response the same as the coupled response? In this study, the importance of air–sea coupling in the Indian and Pacific Oceans for tropical atmospheric variability is investigated through numerical experiments with a coupled atmosphere-ocean general circulation model. The local and remote impacts of the Indian and Pacific Ocean coupling are obtained by comparing a coupled simulation with an experiment in which the SST forcing from the coupled simulation is specified in either the Indian or the Pacific Ocean. It is found that the Indian Ocean coupling is critical for atmospheric variability over the Pacific Ocean. Without the Indian Ocean coupling, the rainfall and SST variations are completely different throughout most of the Pacific Ocean basin. Without the Pacific Ocean coupling, part of the rainfall and SST variations in the Indian Ocean are reproduced in the forced run. In regions of large mean rainfall where the atmospheric negative feedback is strong, such as the North Indian Ocean and the western North Pacific in boreal summer, the atmospheric variability is significantly enhanced when air–sea coupling is replaced by specified SST forcing. This enhancement is due to the lack of the negative feedback in the forced SST simulation. In these regions, erroneous atmospheric anomalies could be induced by specified SST anomalies derived from the coupled model. The ENSO variability is reduced by about 20% when the Indian Ocean air–sea coupling is replaced by specified SST forcing. This change is attributed to the interfering roles of the Indian Ocean SST and Indian monsoon in western and central equatorial Pacific surface wind variations.     

FGOALS-g3模拟的南亚夏季风:气候态和年际变率

南亚夏季风的变化决定着印度半岛的旱涝状况,气候系统模式则是研究南亚夏季风变化规律的重要工具。本文基于观测和JRA55再分析资料,系统评估了FGOALS-g3模式模拟的南亚夏季风气候态和年际变率,并重点关注FGOALS-g3与FGOALS-g2以及是否考虑海气相互作用的模拟差异。结果表明,由于局地海温模拟的变化,相比于FGOALS-g2,FGOALS-g3模拟的南亚夏季风在气候态热带印度洋信风和El Ni?o期间沃克环流下沉支上有明显改进。同时,由于对流层系统性冷偏差持续存在并且中心位于副热带300 hPa附近,造成气候态上经向温度梯度减弱,使季风环流减弱,导致FGOALS-g3中陆地季风槽的水汽辐散偏差和降水干偏差仍然存在;在年际变率上,FGOALS-g3模拟的El Ni?o期间赤道西太平洋海温冷异常偏弱,印度洋偶极子偏强,导致印度半岛下沉运动减弱,FGOALS-g3中ENSO—印度降水负相关关系也依然偏弱。研究表明,耦合过程导致的气候态海温偏差通过改变环流和水汽输送,有效补偿了大气模式中印度半岛中部和中南半岛的降水湿偏差;在年际变率上,耦合模式由于考虑了海温—降水—云短波辐射的负反馈过程,能够减小大气模式模拟偏差的强度,但印太暖池区海温模拟偏差导致沃克环流下沉支偏西,使得印度半岛的降水响应出现更大的湿偏差。     

Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases

The Arabian Sea is an important moisture source for Indian monsoon rainfall. The skill of climate models in simulating the monsoon and its variability varies widely, while Arabian Sea cold sea surface temperature (SST) biases are common in coupled models and may therefore influence the monsoon and its sensitivity to climate change. We examine the relationship between monsoon rainfall, moisture fluxes and Arabian Sea SST in observations and climate model simulations. Observational analysis shows strong monsoons depend on moisture fluxes across the Arabian Sea, however detecting consistent signals with contemporaneous summer SST anomalies is complicated in the observed system by air/sea coupling and large-scale induced variability such as the El Ni?o-Southern Oscillation feeding back onto the monsoon through development of the Somali Jet. Comparison of HadGEM3 coupled and atmosphere-only configurations suggests coupled model cold SST biases significantly reduce monsoon rainfall. Idealised atmosphere-only experiments show that the weakened monsoon can be mainly attributed to systematic Arabian Sea cold SST biases during summer and their impact on the monsoon-moisture relationship. The impact of large cold SST biases on atmospheric moisture content over the Arabian Sea, and also the subsequent reduced latent heat release over India, dominates over any enhancement in the land-sea temperature gradient and results in changes to the mean state. We hypothesize that a cold base state will result in underestimation of the impact of larger projected Arabian Sea SST changes in future climate, suggesting that Arabian Sea biases should be a clear target for model development.     

Indian Ocean and monsoon coupled interactions in a warming environment

Several studies have drawn attention to the steady warming of the equatorial and tropical Indian Ocean (IO) sea surface temperature (SST) observed during recent decades. An intriguing aspect of the IO SST warming trend is that it is has been accompanied by a pronounced weakening of the large-scale boreal summer monsoon circulation. Based on a detailed diagnostic analysis of observed datasets, reanalysis products and IPCC AR4 coupled model output, this study examines how the observed changes in the summer monsoon circulation could have contributed to this SST warming trend. The present results reveal that the weakening trend of the summer monsoon cross-equatorial flow has favored a reorientation of surface westerlies towards the equatorial IO during recent decades, relative to summer monsoons of earlier decades, which were dominated by stronger cross-equatorial flow. Our analysis suggests that the weakening of the summer monsoon cross-equatorial flow has in turn significantly accelerated the SST warming in the central equatorial IO. While the trend in the equatorial westerlies has promoted downwelling and thermocline deepening in the eastern equatorial IO, the central equatorial IO warming is attributed to reduced upwelling in response to a weakening trend of the wind-stress curl. The observed trends in Indian monsoon rainfall and the near-equatorial SST warming are shown to be closely related to variations in the meridional gradient of the monsoon zonal winds. An examination of the twentieth century simulations from 22 IPCC AR4 models, suggests that some models capture the recent equatorial IO warming associated with the weakened summer monsoon circulation reasonably well. The individual member models, however, exhibit significant inter-model variations in representing the observed response of the IO and monsoon coupled system.     

The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius–Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that such effects are small compared to other sources of uncertainty, although models with large Arabian Sea cold SST biases may suppress the range of potential outcomes for changes to future early monsoon rainfall.     

How are seasonal prediction skills related to models’ performance on mean state and annual cycle?

Given observed initial conditions, how well do coupled atmosphere–ocean models predict precipitation climatology with 1-month lead forecast? And how do the models’ biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981–2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models’ ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian–Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated.     

A multi-model analysis of the role of the ocean on the African and Indian monsoon during the mid-Holocene

We investigate the role of the ocean feedback on the climate in response to insolation forcing during the mid-Holocene (6,000 year BP) using results from seven coupled ocean–atmosphere general circulation models. We examine how the dipole in late summer sea-surface temperature (SST) anomalies in the tropical Atlantic increases the length of the African monsoon, how this dipole structure is created and maintained, and how the late summer SST warming in the northwest Indian Ocean affects the monsoon retreat in this sector. Similar mechanisms are found in all of the models, including a strong wind evaporation feedback and changes in the mixed layer depth that enhance the insolation forcing, as well as increased Ekman transport in the Atlantic that sharpens the Atlantic dipole pattern. We also consider changes in interannual variability over West Africa and the Indian Ocean. The teleconnection between variations in SST and Sahelian precipitation favor a larger impact of the Atlantic dipole mode in this region. In the Indian Ocean, the strengthening of the Indian dipole structure in autumn has a damping effect on the Indian dipole mode at the interannual time scale.     

Predictability of the western North Pacific summer climate demonstrated by the coupled models of ENSEMBLES

The Asian monsoon system, including the western North Pacific (WNP), East Asian, and Indian monsoons, dominates the climate of the Asia-Indian Ocean-Pacific region, and plays a significant role in the global hydrological and energy cycles. The prediction of monsoons and associated climate features is a major challenge in seasonal time scale climate forecast. In this study, a comprehensive assessment of the interannual predictability of the WNP summer climate has been performed using the 1-month lead retrospective forecasts (hindcasts) of five state-of-the-art coupled models from ENSEMBLES for the period of 1960–2005. Spatial distribution of the temporal correlation coefficients shows that the interannual variation of precipitation is well predicted around the Maritime Continent and east of the Philippines. The high skills for the lower-tropospheric circulation and sea surface temperature (SST) spread over almost the whole WNP. These results indicate that the models in general successfully predict the interannual variation of the WNP summer climate. Two typical indices, the WNP summer precipitation index and the WNP lower-tropospheric circulation index (WNPMI), have been used to quantify the forecast skill. The correlation coefficient between five models’ multi-model ensemble (MME) mean prediction and observations for the WNP summer precipitation index reaches 0.66 during 1979–2005 while it is 0.68 for the WNPMI during 1960–2005. The WNPMI-regressed anomalies of lower-tropospheric winds, SSTs and precipitation are similar between observations and MME. Further analysis suggests that prediction reliability of the WNP summer climate mainly arises from the atmosphere–ocean interaction over the tropical Indian and the tropical Pacific Ocean, implying that continuing improvement in the representation of the air–sea interaction over these regions in CGCMs is a key for long-lead seasonal forecast over the WNP and East Asia. On the other hand, the prediction of the WNP summer climate anomalies exhibits a remarkable spread resulted from uncertainty in initial conditions. The summer anomalies related to the prediction spread, including the lower-tropospheric circulation, SST and precipitation anomalies, show a Pacific-Japan or East Asia-Pacific pattern in the meridional direction over the WNP. Our further investigations suggest that the WNPMI prediction spread arises mainly from the internal dynamics in air–sea interaction over the WNP and Indian Ocean, since the local relationships among the anomalous SST, circulation, and precipitation associated with the spread are similar to those associated with the interannual variation of the WNPMI in both observations and MME. However, the magnitudes of these anomalies related to the spread are weaker, ranging from one third to a half of those anomalies associated with the interannual variation of the WNPMI in MME over the tropical Indian Ocean and subtropical WNP. These results further support that the improvement in the representation of the air–sea interaction over the tropical Indian Ocean and subtropical WNP in CGCMs is a key for reducing the prediction spread and for improving the long-lead seasonal forecast over the WNP and East Asia.     

春季热带南大西洋海表温度异常与夏季亚澳季风区降水异常的联系

利用1979—2019年Hadley中心的海表温度资料、GPCP的降水资料以及NCEP-DOE的再分析资料等,分析了北半球春季热带南大西洋海表温度异常与北半球夏季亚澳季风区降水异常的联系。研究表明,北半球春季热带南大西洋海表温度异常与随后夏季热带西太平洋到南海（澳大利亚东侧海域到热带东印度洋）地区的降水异常为显著负相关（正相关）关系。北半球春季热带南大西洋的海表温度正异常可以引起热带大西洋和热带太平洋间的异常垂直环流,其中异常上升支（下沉支）位于热带大西洋（热带中太平洋）。热带中太平洋的异常下沉气流和低层辐散气流引起热带中西太平洋低层的异常东风,后者有利于热带中东太平洋海表温度出现负异常。通过Bjerknes正反馈机制,热带中东太平洋海表温度异常从北半球春季到夏季得到发展。热带中东太平洋海表温度负异常激发的Rossby波使得北半球夏季热带西太平洋低层出现一对异常反气旋。此时,850 hPa上热带西太平洋到海洋性大陆地区为显著的异常东风,有利于热带西太平洋到南海（澳大利亚东侧海域到热带东印度洋）地区出现异常的水汽辐散（辐合）,导致该地区降水减少（增加）。     

Role of thermocline–SST coupling in the evolution of IOD events and their regional impacts

The evolution of sea surface temperature (SST) and thermocline (represented by 20 °C isotherm depth, D20) in the east equatorial Indian Ocean (EIO) associated with the Indian Ocean Dipole (IOD) years is studied for the period of 50 years from 1958 to 2007. A new IOD index based on combined anomalies of surface winds, D20 and SST over the equatorial Indian Ocean is defined to identify strong and weak IOD events. It is found that the evolution of strong IOD events is driven by ocean dynamics in the form of thermocline–SST coupling and is strongly interactive with the atmosphere, whereas the weak IOD events are mere response to surface winds without such dynamical coupling. The easterly wind anomalies extend up to the western equatorial Indian Ocean (WIO) during strong IOD years and support enhanced EIO air–sea interactions. On the other hand, the evolution of zonal wind anomalies is weak during the weak IOD years. Thermocline–SST coupling is robust in both EIO and WIO during strong IOD years, which is primarily responsible for the enhanced SST gradient, strong enough to establish anomalous Walker circulation within the Indian Ocean. The strong convection over the WIO associated with the Indian Ocean Walker cell triggers a secondary cell with subsidence over the African landmass. This double cell structure over the equatorial Indian Ocean is not reported before. Such double cell structure is not evident in weak IOD years and instead the convection over WIO extends up to African landmass. These are well supported by the spatial pattern of anomalous precipitable water during strong and weak IOD years. Strengthening of monsoon flow and local Hadley cell associated with strong IOD events enhances precipitation over the Indian subcontinent, whereas weak IOD years have less impact on the Indian summer monsoon circulation and rainfall. Analysis reveals that the EIO thermocline index and combined index could be potential predictors for the central Indian rainfall during summer.     

The seasonal predictability of the Asian summer monsoon in a two-tiered forecast system

An extensive set of boreal summer seasonal hindcasts from a two tier system is compared with corresponding seasonal hindcasts from two other coupled ocean–atmosphere models for their seasonal prediction skill (for precipitation and surface temperature) of the Asian summer monsoon. The unique aspect of the two-tier system is that it is at relatively high resolution and the SST forcing is uniquely bias corrected from the multi-model averaged forecasted SST from the two coupled ocean–atmosphere models. Our analysis reveals: (a) The two-tier forecast system has seasonal prediction skill for precipitation that is comparable (over the Southeast Asian monsoon) or even higher (over the South Asian monsoon) than the coupled ocean–atmosphere. For seasonal anomalies of the surface temperature the results are more comparable across models, with all of them showing higher skill than that for precipitation. (b) Despite the improvement from the uncoupled AGCM all models in this study display a deterministic skill for seasonal precipitation anomalies over the Asian summer monsoon region to be weak. But there is useful probabilistic skill for tercile anomalies of precipitation and surface temperature that could be harvested from both the coupled and the uncoupled climate models. (c) Seasonal predictability of the South Asian summer monsoon (rainfall and temperature) does seem to stem from the remote ENSO forcing especially over the Indian monsoon region and the relatively weaker seasonal predictability in the Southeast Asian summer monsoon could be related to the comparatively weaker teleconnection with ENSO. The uncoupled AGCM with the bias corrected SST is able to leverage this teleconnection for improved seasonal prediction skill of the South Asian monsoon relative to the coupled models which display large systematic errors of the tropical SST’s.     

Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias

We have evaluated the simulation of Indian summer monsoon and its intraseasonal oscillations in the National Centers for Environmental Prediction climate forecast system model version 2 (CFSv2). The dry bias over the Indian landmass in the mean monsoon rainfall is one of the major concerns. In spite of this dry bias, CFSv2 shows a reasonable northward propagation of convection at intraseasonal (30–60 day) time scale. In order to document and understand this dry bias over the Indian landmass in CFSv2 simulations, a two pronged investigation is carried out on the two major facets of Indian summer monsoon: one, the air–sea interactions and two, the large scale vertical heating structure in the model. Our analysis shows a possible bias in the co-evolution of convection and sea surface temperature in CFSv2 over the equatorial Indian Ocean. It is also found that the simulated large scale vertical heat source (Q1) and moisture sink (Q2) over the Indian region are biased relative to observational estimates. Finally, this study provides a possible explanation for the dry precipitation bias over the Indian landmass in the simulated mean monsoon on the basis of the biases associated with the simulated ocean–atmospheric processes and the vertical heating structure. This study also throws some light on the puzzle of CFSv2 exhibiting a reasonable northward propagation at the intraseasonal time scale (30–60 day) despite a drier monsoon over the Indian land mass.     

Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models

Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean–atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959–1979) are closer to the ‘perfect model’ (attainable) score but, large differences are observed between ‘actual’ skill and ‘perfect model’ skill in the recent period (1980–2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.     

A Regional Air--Sea Coupled Model and Its Application over East Asia in the Summer of 2000

A regional air-sea coupled model,comprising the Regional Integrated Environment Model System (RIEMS)and the Princeton Ocean Model(POM)was developed to simulate summer climate features over East Asia in 2000.The sensitivity of the model's behavior to the coupling time interval(CTI),the causes of the sea surface temperature(SST)biases,and the role of air-sea interaction in the simulation of precipitation over China are investigated.Results show that the coupled model can basically produce the spatial pattern of SST,precipitation,and surface air temperature(SAT)with five different CTIs respectively.Also,using a CTI of 3,6 or 12 hours tended to produce more successful simulations than if using 1 and 24 hours.Further analysis indicates that both a higher and lower coupling frequency result in larger model biases in air-sea heat flux exchanges,which might be responsible for the sensitivity of the coupled model's behavior to the CTI. Sensitivity experiments indicate that SST biases between the coupled and uncoupled POM occurring over the China coastal waters were due to the mismatch of the surface heat fluxes produced by the RIEMS with those required by the POM.In the coupled run,the air-sea feedbacks reduced the biases in surface heat fluxes,compared with the uncoupled RIEMS,consequently resulted in changes in thermal contrast over land and sea and led to a precipitation increase over South China and a decrease over North China.These results agree well observations in the summer of 2000.     

Boreal summer continental monsoon rainfall and hydroclimate anomalies associated with the Asian-Pacific Oscillation

With the twentieth century analysis data (1901–2002) for atmospheric circulation, precipitation, Palmer drought severity index, and sea surface temperature (SST), we show that the Asian-Pacific Oscillation (APO) during boreal summer is a major mode of the earth climate variation linking to global atmospheric circulation and hydroclimate anomalies, especially the Northern Hemisphere (NH) summer land monsoon. Associated with a positive APO phase are the warm troposphere over the Eurasian land and the relatively cool troposphere over the North Pacific, the North Atlantic, and the Indian Ocean. Such an amplified land–ocean thermal contrast between the Eurasian land and its adjacent oceans signifies a stronger than normal NH summer monsoon, with the strengthened southerly or southwesterly monsoon prevailing over tropical Africa, South Asia, and East Asia. A positive APO implies an enhanced summer monsoon rainfall over all major NH land monsoon regions: West Africa, South Asia, East Asia, and Mexico. Thus, APO is a sensible measure of the NH land monsoon rainfall intensity. Meanwhile, reduced precipitation appears over the arid and semiarid regions of northern Africa, the Middle East, and West Asia, manifesting the monsoon-desert coupling. On the other hand, surrounded by the cool troposphere over the North Pacific and North Atlantic, the extratropical North America has weakened low-level continental low and upper-level ridge, hence a deficient summer rainfall. Corresponding to a high APO index, the African and South Asian monsoon regions are wet and cool, the East Asian monsoon region is wet and hot, and the extratropical North America is dry and hot. Wet and dry climates correspond to wet and dry soil conditions, respectively. The APO is also associated with significant variations of SST in the entire Pacific and the extratropical North Atlantic during boreal summer, which resembles the Interdecadal Pacific Oscillation in SST. Of note is that the Pacific SST anomalies are not present throughout the year, rather, mainly occur in late spring, peak at late summer, and are nearly absent during boreal winter. The season-dependent APO–SST relationship and the origin of the APO remain elusive.     

气候系统模式FGOALS模拟的南亚夏季风：偏差和原因分析

本文通过与观测和再分析资料的对比,评估了LASG/IAP发展的气候系统模式FGOALS的两个版本FGOALS-g2和FGOALS-s2对南亚夏季风的气候态和年际变率的模拟能力,并使用水汽收支方程诊断,研究了造成降水模拟偏差的原因。结果表明,两个模式夏季气候态降水均在陆地季风槽内偏少,印度半岛附近海域偏多,在降水年循环中表现为夏季北侧辐合带北推范围不足。FGOALS-g2中赤道印度洋"东西型"海温偏差导致模拟的东赤道印度洋海上辐合带偏弱,而FGOALS-s2中印度洋"南北型"海温偏差导致模拟的海上辐合带偏向西南。水汽收支分析表明,两个模式中气候态夏季风降水的模拟偏差主要来自于整层积分的水汽通量,尤其是垂直动力平流项的模拟偏差。一方面,夏季阿拉伯海和孟加拉湾的海温偏冷而赤道西印度洋海温偏暖,造成向印度半岛的水汽输送偏少;另一方面,对流层温度偏冷,冷中心位于印度半岛北部对流层上层,同时季风槽内总云量偏少,云长波辐射效应偏弱,对流层经向温度梯度偏弱以及大气湿静力稳定度偏强引起的下沉异常造成陆地季风槽内降水偏少。在年际变率上,观测中南亚夏季风环流和降水指数与Ni?o3.4指数存在负相关关系,但FGOALS两个版本模式均存在较大偏差。两个模式中与ENSO暖事件相关的沃克环流异常下沉支和对应的负降水异常西移至赤道以南的热带中西印度洋,沿赤道非对称的加热异常令两个模式中越赤道环流季风增强,导致印度半岛南部产生正降水异常。ENSO相关的沃克环流异常下沉支及其对应的负降水异常偏西与两个模式对热带南印度洋气候态降水的模拟偏差有关。研究结果表明,若要提高FGOALS两个版本模式对南亚夏季风气候态模拟技巧,需减小耦合模式对印度洋海温、对流层温度及云的模拟偏差;若要提高南亚夏季风和ENSO相关性模拟技巧需要提高模式对热带印度洋气候态降水以及与ENSO相关的环流异常的模拟能力。     

Sea surface temperature associations with the late Indian summer monsoon

Recent gridded and historical data are used in order to assess the relationships between interannual variability of the Indian summer monsoon (ISM) and sea surface temperature (SST) anomaly patterns over the Indian and Pacific oceans. Interannual variability of ISM rainfall and dynamical indices for the traditional summer monsoon season (June–September) are strongly influenced by rainfall and circulation anomalies observed during August and September, or the late Indian summer monsoon (LISM). Anomalous monsoons are linked to well-defined LISM rainfall and large-scale circulation anomalies. The east-west Walker and local Hadley circulations fluctuate during the LISM of anomalous ISM years. LISM circulation is weakened and shifted eastward during weak ISM years. Therefore, we focus on the predictability of the LISM. Strong (weak) (L)ISMs are preceded by significant positive (negative) SST anomalies in the southeastern subtropical Indian Ocean, off Australia, during boreal winter. These SST anomalies are mainly linked to south Indian Ocean dipole events, studied by Besera and Yamagata (2001) and to the El Niño-Southern Oscillation (ENSO) phenomenon. These SST anomalies are highly persistent and affect the northwestward translation of the Mascarene High from austral to boreal summer. The southeastward (northwestward) shift of this subtropical high associated with cold (warm) SST anomalies off Australia causes a weakening (strengthening) of the whole monsoon circulation through a modulation of the local Hadley cell during the LISM. Furthermore, it is suggested that the Mascarene High interacts with the underlying SST anomalies through a positive dynamical feedback mechanism, maintaining its anomalous position during the LISM. Our results also explain why a strong ISM is preceded by a transition in boreal spring from an El Niño to a La Niña state in the Pacific and vice versa. An El Niño event and the associated warm SST anomalies over the southeastern Indian Ocean during boreal winter may play a key role in the development of a strong ISM by strengthening the local Hadley circulation during the LISM. On the other hand, a developing La Niña event in boreal spring and summer may also enhance the east–west Walker circulation and the monsoon as demonstrated in many previous studies.     

年代际气候预测系统IAP DecPreS的海洋同化试验在西北太平洋的海温偏差及其对亚洲夏季风的影响

本文分析了中国科学院大气物理研究所年代际气候预测系统IAP DecPreS的海洋同化试验（简称EnOI-IAU试验）在西北太平洋地区的海表面温度（SST）年循环的模拟技巧,并通过对比IAP DecPreS系统自由耦合历史气候模拟试验结果,在包含海气耦合过程的框架下讨论了耦合模式中西北太平洋夏季SST模拟差异,及其对亚洲季风区夏季季风降水模拟的影响。结果表明,EnOI-IAU试验较好地模拟出了西北太平洋各个季节的SST空间分布,并显著减小了原存在于历史气候模拟试验中持续全年的SST冷偏差。混合层热收支诊断分析表明,包含同化过程在内的海洋过程的模拟差异对西北太平洋海温的模拟提升有重要贡献。夏季,EnOI-IAU试验模拟的印度季风伴随的低层西风较观测偏东、偏强,且高估了赤道西太平洋区域的降水量值、低估了印度洋区域的降水量值。水汽收支分析显示,气旋式环流异常造成的水汽辐合异常是造成亚洲季风区降水模拟差异的主要原因。研究表明,较之历史模拟试验,EnOI-IAU试验中夏季西北太平洋地区SST增暖造成局地对流增强,进而使得局地产生异常上升运动,水汽辐合增强,造成西北太平洋地区降水模拟偏多,激发出低层西风异常及赤道外气旋式环流异常。该低层西风异常导致了北印度洋地区低层辐散异常,减小了原存在于历史试验中印度洋地区的正降水偏差。西北太平洋气旋式环流异常一方面增强了印度夏季风伴随的低层西风,使得更多的水汽从阿拉伯海输送到西太平洋暖池区域,增强了该区域的降水量;另一方面,该气旋式环流异常减小了历史模拟试验中中国南部区域偏强的低层风速,进而提升了模式对东亚低层西南风的模拟能力。