IAP AGCM 4.1对淮河流域夏季降水的预报技巧评估

基于中国科学院大气物理研究所新一代大气环流模式IAP AGCM 4.1共30 a(1981—2010年)的集合回报试验结果,评估了模式对淮河流域夏季降水的预报技巧。分析结果表明,模式总体上可以较好地再现出淮河流域夏季平均降水南多北少的空间分布特征,其中模式模拟的6月降水量与观测值的空间相关可达0.93。但降水强度与观测相比具有系统性的偏差,且模式模拟的降水年际变率显著偏弱。基于降水距平相关系数的确定性预报技巧分析表明,模式对流域西南部夏季降水的预测技巧较高,达到0.2以上,且模式对6月降水异常的预测能力相对最好,7月次之。针对淮河不同子流域的预报技巧分析表明,IAP AGCM 4. 1对蚌埠、鲁台子、王家坝水文控制站以上集水面积的夏季面雨量异常具有一定的预报技巧,30 a集合回报的时间相关系数分别为0. 11、0. 13、0. 16。基于降水等级的概率预报技巧评估表明,模式对7月淮河流域南部少雨事件具有很好的预报能力,同时对6月流域中部多雨事件的预报技巧也较高。     

MJO potential predictability and predictive skill in IAP AGCM 4.1

MJO模拟及预报是现阶段大气科学研究的前沿问题。本文利用中科院大气物理所大气环流模式(IAP AGCM4.1)的集合回报结果,分析了MJO潜在可预报性及预报技巧。研究表明IAP AGCM4.1对MJO有着较好的潜在可预报性,且集合预报的潜在可预报性要明显优于单样本预报;就MJO的预报技巧而言,集合预报同样优于单样本预报;模式对MJO的预报技巧还显著依赖于预报初始时刻的MJO状态,初始MJO信号越强,模式对MJO的预报技巧也越高,且更接近可预报性的上限。     

基于K-均值聚类方法的大气环流模式IAP AGCM4.1对西北太平洋热带气旋的模拟评估

IAP AGCM4.1（Institute of Atmospheric Physics Atmospheric General Circulation Model, version 4.1）是中国科学院大气物理研究所自主研发的大气环流模式,也是中科院地球系统模式CAS-ESM1（Chinese Academy of Sciences Earth System Model, version 1）的大气分量模式。本文利用极端气候分析软件TECA（Toolkit for Extreme Climate Analysis）,对IAP AGCM4.1模拟的1979～2012年西北太平洋热带气旋（TC）进行了识别与评估。结果表明IAP AGCM4.1模拟的TC空间分布、路径走向与生成源地与观测基本一致,但模拟的TC个数有所低估,仅为观测的36%。基于K-均值聚类方法的分类评估显示,这种低估主要体现在模式对于西北行转向类和西行类TC没有模拟能力。对于近海西—西北行类、西转向类和东转向类TC,模式模拟的个数可分别达到观测的39%,48%和85%,模拟的季节变化与观测的相关系数在0.89～0.91之间,周期误差在1～2天。就TC路径而言,模式对于近海西—西北行类和东转向类TC模拟效果较好,质心经度误差、质心纬度误差和经纬向标准差的模拟误差分别为1%～5%、4%～16%和5～15%。此外,环流合成分析表明模式很好地再现了东转向类TC发生、发展期间环境流场的演变以及副热带高压的变化情况,模拟的副热带高压强度和面积指数与观测的相关系数可达0.89。模式对西北行转向类和西行类TC模拟能力较差的原因可能与模式对副热带高压的模拟偏差有关。     

应用IAP9L-AGCM对2002年中国夏季气候的预测及效果检验

利用中科院大气所9层大气环流格点模式(IAP9L—AGCM)和IAP—ENSO预测系统对2002年中国夏季气候进行实时集合预测及其检验。结果显示，IAP9L—AGCM较好地预测出了2002年夏季我国大范围旱涝的分布形势，如华南、我国西部多雨，黄河和长江流域之间大范围干旱等；850hPa减弱的夏季风、青藏高原辐散中心以及北太平洋上空的异常气旋性环流中心亦被较好地预报出来；不足的是，模式对降水异常细致分布的预测能力有限。预测结果还表明，该模式对夏季(6—8月)平均降水的预报技巧要高于月平均状况，且月平均预报的准确度从6—8月依次递减。     

基于旋转经验正交分解的流域降水气候预测误差订正方法

流域尺度的降水短期气候预测水平对流域的防灾减灾具有重要价值。为了进一步提高中国科学院大气物理研究所新一代大气环流模式IAP AGCM 4.1在淮河和长江流域夏季降水预测效果,利用旋转经验正交分解（Rotated Empirical Orthogonal Function, REOF）方法对两个流域夏季降水区域特征进行分析的基础上,建立了一个适用于流域的分区经验正交分解（Empirical Orthogonal Function, EOF）订正方案,并利用IAP AGCM 4.1气候预测系统在两个流域的夏季降水共30年（1981～2010年）的集合回报试验结果进行了订正试验。结果表明分区订正方法明显改进了模式对淮河流域的夏季降水预测水平,淮河流域的流域平均相关系数从0.03提高到了0.22。对长江流域的季度降水预报也有显著的改进效果,平均相关系数从-0.05提高到0.24。分区订正结果明显优于流域整体订正方案,证明了基于REOF分析确定降水具有强局地性特征的订正区域,能够很好地提高EOF订正方法的效果稳定性,这对其他流域降水预测的订正研究具有很好的借鉴意义。     

IAP PSSCA 两组预测试验的评估及比较 I.降水部分

利用中国科学院大气物理研究所研制的短期气候距平数值预测系统（IAP PSSCA）,　　种版本的大气环流模式：AGCM 1.1和AGCM 1.2,分别以2月11～19日的9天大气观测值为初始场,以给定海温为边界场,对1980～1994年的15年的降水异常进行了两组集合后报试验。对试验结果进行定量评估表明：IAP PSSCA对降水异常具有一定的预测能力,特别是在中国东部受东亚季风及海温异常影响的地区,IAP PSSCA具有较高的预报技巧,其中以东南区域（包括江淮流域和华南地区）最高,尤其是对有洪涝灾害的降水异常年,距平相关系数在0.50左右,接近可供业务使用的要求,说明模式能够抓住在东亚季风区存在的某种物理机制,从而提高了这一地区的预报技巧;另外,两个大气环流模式相比,改进了地表反照率的AGCM 1.2的15年集合平均预测技巧略高于AGCM 1.1,特别是在华北地区,预测效果有明显提高,这表明改进地表反照率从而改进了模式的气候平均态的模拟,能提高气候模式的预测能力,说明较好的陆面过程引入模式对短期气候预测是有益的。     

中国业务动力季节预报的进展

利用动力模式开展季节到年际的短期气候预测 ,是目前国际上气候预测的发展方向。自 1996年以来 ,经过 8a多的研制和发展 ,国家气候中心已建立起第 1代动力气候模式预测业务系统 ,其中包括 1个全球大气 海洋耦合模式 (CGCM )、1个高分辨率东亚区域气候模式 (RegCM_NCC)和 5个简化的ENSO预测模式 (SAOMS) ,可用于季节—年际时间尺度的全球气候预测 ;全球海气耦合模式与区域气候模式嵌套 ,可以提供高分辨率的东亚区域气候模式制做季节预测。CGCM对 1982～ 2 0 0 0年夏季的历史回报试验表明 ,该模式对热带太平洋海表面温度和东亚区域的季节预测具有较好的预测能力。RegCM NCC的 5a模拟基本上能再现东亚地区主要雨带的季节进展。利用嵌套的区域气候模式RegCM NCC对 1991～ 2 0 0 0年的夏季回报表明 ,在预报主要季节雨带方面有一定技巧。 2 0 0 1～ 2 0 0 3年 ,CGCM和RegCM NCC的实时季节预报与观测相比基本合理。特别是 ,模式成功地预报了 2 0 0 3年梅雨季节长江和黄河之间比常年偏多的降水。SAOMS模式系统的回报试验表明 ,该系统对热带太平洋海表面温度距平有一定的预报能力 ,模式超前 6～ 12个月的回报与观测的相关系数明显高于持续预报。 1997～ 2 0 0 3年 ,SAOMS多模式集合实时预报与观测的相关系数达到     

IAP AGCM模式对地面气温长期趋势的预报分析

分析了1979～2004年共26年中国台站地面气温的观测资料以及中国科学院大气物理研究所的大气环流模式IAP AGCM在夏季和冬季的季节集合预报结果对地面气温长期变化趋势的预报.分析结果表明,在所研究的26年中,中国大部分地区是一个增温的趋势,其中冬季增温比夏季增温显著.IAP AGCM集合预报不能很好地预报出观测资料...     

华北汛期降水多因子相似订正方案与预报试验

本文基于动力—相似预报的基本原理, 在已初步建立的华北汛期降水模式的动态最优多因子组合相似订正方案工作基础上, 研究前期关键因子之间的相互配置对夏季降水的影响, 挑选关键的大气环流预报因子。根据预报年前期气候因子的异常状况, 通过EOF压缩自由度进行相似年选取, 进一步构建了基于前期异常信号的汛期降水相似订正预报方案。研究发现, 预报年前期大气环流中异常因子个数的偏多或偏少与该年华北降水的多寡呈现较好的对应关系, 并以异常因子的个数状况作为判断该年是否为异常年的标准, 将异常多因子方案与动态最优多因子方案相结合, 建立模式误差相似订正的多因子综合预报方案。通过诊断分析发现, 该方案对降水异常年有着较好的针对性。2003～2009年7年的独立样本回报结果表明: 该方法进一步提高了模式对华北汛期降水的预报能力, 将华北汛期降水预报的距平相关系数 (ACC) 平均分从系统订正结果的0.38提高至0.61, 具有良好的业务应用前景。     

IAP AGCM4.0模式对热带大气季节内振荡的模拟评估

基于中国科学院大气物理所大气环流模式IAP AGCM4.0总共30年(1979~2008年)的模拟结果,评估了IAP AGCM4.0模式对热带大气季节内振荡的模拟能力。分析结果表明IAP AGCM4.0模式可以在一定程度上模拟出热带大气季节内振荡的主要时空谱结构特征,在周期30~80天处存在明显的谱能量中心;模式模拟的季节内振荡东传的主要特征与观测基本一致,东移波的能量远大于西移波。基于RMM指数(All-season Real-time Multivariate MJO Index)的分析表明,模式模拟的850 h Pa和200 h Pa季节内尺度风场和对流活动在赤道地区的空间分布与观测基本一致。但与观测相比,模式模拟的热带大气季节内振荡的周期较短,东传速度快于观测,虚假的西传特征过强,对流活跃区域范围较小、强度较弱。就非绝热加热而言,模式模拟结果与再分析资料比较接近,但最大加热在印度洋和西太平洋地区出现的位相较晚。进一步分析表明,模式中影响对流触发的相对湿度阈值(RHc)的不同取值(RHc分别取为85%、90%、95%和100%),可以显著影响热带大气非绝热加热垂直廓线,从而影响模式对热带大气季节内振荡的模拟;当对流触发相对湿度阈值取为90%时,IAP AGCM4.0模式对热带大气季节内振荡模拟的能力相对最好,非绝热加热垂直廓线在不同位相的分布特征也与再分析资料最为接近。这说明模式对流参数化方案中不同参数的合适选取,可以改进模式对热带大气季节内振荡的模拟能力。     

我国近年来短期气候预测研究的若干进展

回顾了近年来我国短期气候预测研究的若干进展,主要是在中国科学院大气物理研究所完成的以气候模式为基础的短期气候预测方面工作.第一个基于气候数值模式开展短期气候预测试验的是曾庆存等人,他们所采用的是IAP AGCM耦合一个热带太平洋环流模式(OGCM);1997年,基于耦合气候模式基础上的ENSO预测系统建立起来;同时开展了东亚区气候可预测性研究;利用气候变动的准两年信号提出了对模式预测结果进行有效修正的方案;为了考虑初始土壤湿度异常对夏季气候的影响,建立了气象变量和土壤湿度的经验关系;还系统地研究了1998年海面温度异常和大气春季异常对夏季气候(特别是发生于中国的大水)预测的影响.     

Simulation of East Asian Summer Monsoon with IAP CGCM

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Rainfall anomaly prediction using statistical downscaling in a multimodel superensemble over tropical South America

This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical downscaling along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric–ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of downscaling and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well.     

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.     

CONVECTIVE ANOMALIES IN TROPICAL OCEAN AREAS AND LONG-LEAD FORECAST OF SUMMER RAINFALL IN SHANDONG

This study focuses on deep convection anomalies in tropical regions in winter-spring period and their possible influence on the following summer rainfall in Shandong province. On the basis of monthly precipitation wet and dry summers in Shandong are defined according to a precipitation index. Then monthly OLR data, observed by NOAA satellites, are used to diagnose the features of deep convection for both wet and dry summers. It is found that negative anomalies seem dominant prior to wet summers, while large areas of positive anomalies appear prior to dry summers in tropical oceans. The differences are remarkable especially in the western, middle and eastern tropical Pacific as well as in the tropical Indian Ocean. Correlative analysis confirms the relations between OLR and precipitation. Subtropical High, which plays an essential role in summer rainfall, is also connected with the deep conviction. Altogether eight EOF-CCA forecast models are established on the basis of the above study. The assessment of the models relies on the gauge observing precipitation in 1997 and 1998. The results show that models using spring OLR data appear to be more practicable than those using winter OLR data, and the models established with OLR in western Pacific and the Indian Ocean perform better than the others.     

A statistical downscaling scheme to improve global precipitation forecasting

Based on hindcasts obtained from the “Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction” (DEMETER) project, this study proposes a statistical downscaling (SD) scheme suitable for global precipitation forecasting. The key idea of this SD scheme is to select the optimal predictors that are best forecast by coupled general circulation models (CGCMs) and that have the most stable relationships with observed precipitation. Developing the prediction model and further making predictions using these predictors can extract useful information from the CGCMs. Cross-validation and independent sample tests indicate that this SD scheme can significantly improve the prediction capability of CGCMs during the boreal summer (June–August), even over polar regions. The predicted and observed precipitations are significantly correlated, and the root-mean-square-error of the SD scheme-predicted precipitation is largely decreased compared with the raw CGCM predictions. An inter-model comparison shows that the multi-model ensemble provides the best prediction performance. This study suggests that combining a multi-model ensemble with the SD scheme can improve the prediction skill for precipitation globally, which is valuable for current operational precipitation prediction.     

Changes in El Niño and La Niña teleconnections over North Pacific–America in the global warming simulations

The change in the teleconnections of both El Niño and La Niña over the North Pacific and American regions due to a future greenhouse warming has been analyzed herein by means of diagnostics of the Intergovernmental Panel on Climate Change-Fourth Assessment Report (IPCC-AR4) coupled general circulation models (CGCMs). Among the IPCC-AR4 CGCM simulations, the composites of the eight-member multimodel ensemble are analyzed. In most CGCMs, the tropical Pacific warming due to the increase of CO₂ concentration in the atmosphere promotes the main convection centers in the equatorial Pacific associated with both El Niño and La Niña to the east. The eastward shift of the convection center causes a systematic eastward shift of not only El Niño but also La Niña teleconnection patterns over the North Pacific and America, which is demonstrated in the composite maps of 500 hPa circulation, surface temperature, and the precipitation against El Niño and La Niña, as observed in a comparison between the pre-industrial and CO₂ doubling experiments. Thus, a systematic eastward migration of convection centers in the tropical Pacific associated with both El Niño and La Niña due to a future global warming commonly causes the eastward shift of the atmospheric teleconnection patterns over the Northern Hemisphere.     

The change in the East Asian summer monsoon simulated by the MIROC3.2 high-resolution coupled model under global warming scenarios

In order to investigate changes in the East Asian summer monsoon (EASM) under the global warming, the MIROC3.2 (hires) coupled general circulation model (CGCM) developed by the Center for Climate System Research is utilized. The outputs of MIROC3.2 (hires) model have been analyzed using two scenarios; the 20th Century Climate in Coupled Models (20C3M) scenario and the Special Reports for Emissions Scenarios A1B (SRES A1B). Eight Intergovernmental Panel on Climate Change (IPCC) models are also analyzed to compare model performances. It is shown that the simulation skill of MIROC3.2 (hires) for the EASM is relatively superior to these IPCC CGCMs. It has been found that the intensified rain band and the extended duration of the EASM are anticipated with MIROC3.2 (hires) under the global warming in well accordance with previous studies. Especially, the precipitation due to the cumulus convection is predicted to increase more significantly than the precipitation by the large-scale condensation. Due to the increased land-sea thermal contrast in summer under the global warming, water vapor fluxes in the lower troposphere are enhanced. Consequently, the convective instability may be strengthened and thus it leads to the increase of precipitation by cumulus convection. Moreover, the upper tropospheric circulations associated with the EU pattern would lead to the larger interannual variability of precipitation over the EASM region in the future warm climate. In addition, it is found that the relationship between the sea surface temperature over the tropical Pacific Ocean in the wintertime and the summer rainfall over the East Asia may be weakened, suggesting that the predictability of the EASM might become more difficult under the global warming.     

El-Nino Southern Oscillation simulated and predicted in SNU coupled GCMs

The characteristics of the El-Nino Southern Oscillation (ENSO) simulated in free integrations using two versions of the Seoul National University (SNU) ocean–atmosphere coupled global climate model (CGCM) are examined. A revised version of the SNU CGCM is developed by incorporating a reduced air–sea coupling interval (from 1?day to 2?h), a parameterization for cumulus momentum transport, a minimum entrainment rate threshold for convective plumes, and a shortened auto-conversion time scale of cloud water to raindrops. With the revised physical processes, lower tropospheric zonal wind anomalies associated with the ENSO-related sea surface temperature anomalies (SSTA) are represented with more realism than those in the original version. From too weak, the standard deviation of SST over the eastern Pacific becomes too strong in the revised version due to the enhanced air–sea coupling strength and intraseasonal variability associated with ENSO. From the oceanic side, the stronger stratification and the shallower-than-observed thermocline over the eastern Pacific also contribute to the excessive ENSO. The impacts of the revised physical processes on the seasonal predictability are investigated in two sets of the hindcast experiment performed using the two versions of CGCMs. The prediction skill measured by anomaly correlation coefficients of monthly-mean SSTA shows that the new version has a higher skill over the tropical Pacific regions compared to the old version. The better atmospheric responses to the ENSO-related SSTA in the revised version lead to the basin-wide SSTA maintained and developed in a manner that is closer to observations. The symptom of an excessively strong ENSO of the new version in the free integration is not prominent in the hindcast experiment because the thermocline depth over the eastern Pacific is maintained as initialized over the arc of time of the hindcast (7?months).