利用ARGO资料改进ENSO和我国夏季降水气候预测

全球海洋ARGO资料的获取为气候预测的研究提供了前所未有的海洋资料。该文首先利用ARGO资料改进次表层参数化方案后的Zebiak-Cane海洋模式, 与统计大气模式耦合, 建立了热带动力海洋-统计大气耦合模式。通过比较应用和未应用ARGO资料改进的海洋模式, 进行了耦合模式的长期回报试验。结果表明:ARGO资料的应用极大地改善了耦合模式对热带太平洋海面温度异常的预测能力, 提前3个月和6个月的回报结果都有很大的改进, 基本上回报出了Ni?o3.4区海面温度异常的演变特征, 对厄尔尼诺和拉尼娜都能够给出较准确的回报, 回报结果与观测之间的相关性在整个热带太平洋区域明显提高。该文还利用国家气候中心 (NCC) 全球海气耦合模式, 对我国夏季降水进行了个例和多年季度回报模拟试验, 探讨了包含和不包含ARGO观测资料的同化资料作为初始场对我国夏季降水预测的影响, 表明采用带有ARGO观测资料的海洋同化初始场, 回报的我国夏季降水分布形式与观测更一致, 回报结果与观测之间的正相关区域变大, 对我国夏季降水的回报水平比采用没有ARGO观测资料的海洋同化初始场时有明显提高。     

Argo大洋观测资料的同化及其在短期气候预测和海洋分析中的应用

国际Argo(Array for Real-time Geostrophic Oceanography)计划的实施,提供了前所未有的全球深海大洋0～2000 m水深范围内的海水温度和盐度观测资料,在大气和海洋科研业务中应用这一全新的资料,是深入认识大气和海洋变异、提高我国气候预测、海洋监测分析和预报能力的一个关键所在.通过开发非线性温—盐协调同化方案和利用同化高度计资料来调整模式的温度和盐度场,建立了可同化包括Argo等多种海洋观测资料的全球海洋资料变分同化系统,提高了对全球海洋的监测分析能力.实现了海洋资料同化系统与全球海气耦合模式的耦合,显著提高了短期气候预测水平.利用Argo资料改进了海洋动力模式中的物理过程参数化方案,有效提高了海洋模式对真实大洋的模拟能力和对厄尔尼诺/拉尼娜的预测能力.开发了利用Argo浮标漂流轨迹推算全球海洋表层和中层流的方法,提高了推算的全球表层流、中层流资料质量,有效弥补了洋流观测的匮乏.     

An overview of decadal climate predictability in a multi-model ensemble by climate model MIROC

Decadal climate predictability is examined in hindcast experiments by a multi-model ensemble using three versions of the coupled atmosphere-ocean model MIROC. In these hindcast experiments, initial conditions are obtained from an anomaly assimilation procedure using the observed oceanic temperature and salinity with prescribed natural and anthropogenic forcings on the basis of the historical data and future emission scenarios in the Intergovernmental Panel of Climate Change. Results of the multi-model ensemble in our hindcast experiments show that predictability of surface air temperature (SAT) anomalies on decadal timescales mostly originates from externally forced variability. Although the predictable component of internally generated variability has considerably smaller SAT variance than that of externally forced variability, ocean subsurface temperature variability has predictive skills over almost a decade, particularly in the North Pacific and the North Atlantic where dominant signals associated with Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO) are observed. Initialization enhances the predictive skills of AMO and PDO indices and slightly improves those of global mean temperature anomalies. Improvement of these predictive skills in the multi-model ensemble is higher than that in a single-model ensemble.     

The Impact of “Bad” Argo Profiles on Ocean Data Assimilation

Recent studies have found cold biases in a fraction of Argo profiles (hereinafter referred to as bad Array for Real-time Geostrophic Oceanography (Argo) profiles) due to the pressure drifts during 2003 and 2006. These bad Argo profiles have had an important impact on in situ observation-based global ocean heat content estimates. This study investigated the impact of bad Argo profiles on ocean data assimilation results that were based on observations from diverse ocean observation systems, such as in situ profiles (e.g., Argo, expendable bathythermograph (XBT), and Tropical Atmosphere Ocean (TAO), remote-sensing sea surface temperature products and satellite altimetry between 2004 and 2006. Results from this work show that the upper ocean heat content analysis is vulnerable to bad Argo profiles and demonstrate a cooling trend in the studied period despite the multiple independent data types that were assimilated. When the bad Argo profiles were excluded from the assimilation, the decreased heat content disappeared and a warming occurred. Combination of satellite altimetry and mass variation data from gravity satellite demonstrated an increase, which agrees well with the increased heat content. Additionally, when an additional Argo profile quality control procedure was utilized that simply removed the profiles that presented static unstable water columns, the results were very similar to those obtained when the bad Argo profiles were excluded from the assimilation. This indicates that an ocean data assimilation that uses multiple data sources with improved quality control could be less vulnerable to a major observation system failure, such as a bad Argo event.     

一个海气耦合模式对东亚夏季气候预测潜力的评估

利用一个具有较高分辨率的海气耦合模式SINTEX-F(Scale Interaction Experiment-Frontier Research Center for Global Change coupled GCM)的多年回报结果,评估了该海气耦合模式对东亚区域,尤其是中国地区气候异常的预测潜力.与观测实况的比较结果表明:SINTEX-F模式对夏季降水、500 hPa高度场和地表气温都有一定的预测技巧,但是相比而言降水与高度场的回报技巧要高于地表气温;而且耦合模式对东亚地区气候异常的主要空间分布和年际变化特征也有较好的预测潜力,对500 hPa高度场效果较好;对降水异常的年际变化也有一定的预测潜力,尤其是我国中部地区效果较好,但是模式预测的降水异常的幅值较观测相对偏弱;此外对我国西部的极端气候也有一定的预测潜力.     

Global seasonal climate predictability in a two tiered forecast system: part I: boreal summer and fall seasons

This paper shows demonstrable improvement in the global seasonal climate predictability of boreal summer (at zero lead) and fall (at one season lead) seasonal mean precipitation and surface temperature from a two-tiered seasonal hindcast forced with forecasted SST relative to two other contemporary operational coupled ocean–atmosphere climate models. The results from an extensive set of seasonal hindcasts are analyzed to come to this conclusion. This improvement is attributed to: (1) The multi-model bias corrected SST used to force the atmospheric model. (2) The global atmospheric model which is run at a relatively high resolution of 50 km grid resolution compared to the two other coupled ocean–atmosphere models. (3) The physics of the atmospheric model, especially that related to the convective parameterization scheme. The results of the seasonal hindcast are analyzed for both deterministic and probabilistic skill. The probabilistic skill analysis shows that significant forecast skill can be harvested from these seasonal hindcasts relative to the deterministic skill analysis. The paper concludes that the coupled ocean–atmosphere seasonal hindcasts have reached a reasonable fidelity to exploit their SST anomaly forecasts to force such relatively higher resolution two tier prediction experiments to glean further boreal summer and fall seasonal prediction skill.     

Hindcast skill and predictability for precipitation and two-meter air temperature anomalies in global circulation models over the Southeast United States

This paper presents an assessment of the seasonal prediction skill of current global circulation models, with a focus on the two-meter air temperature and precipitation over the Southeast United States. The model seasonal hindcasts are analyzed using measures of potential predictability, anomaly correlation, Brier skill score, and Gerrity skill score. The systematic differences in prediction skill of coupled ocean–atmosphere models versus models using prescribed (either observed or predicted) sea surface temperatures (SSTs) are documented. It is found that the predictability and the hindcast skill of the models vary seasonally and spatially. The largest potential predictability (signal-to-noise ratio) of precipitation anywhere in the United States is found in the Southeast in the spring and winter seasons. The maxima in the potential predictability of two-meter air temperature, however, reside outside the Southeast in all seasons. The largest deterministic hindcast skill over the Southeast is found in wintertime precipitation. At the same time, the boreal winter two-meter air temperature hindcasts have the smallest skill. The large wintertime precipitation skill, the lack of corresponding two-meter air temperature hindcast skill, and a lack of precipitation skill in any other season are features common to all three types of models (atmospheric models forced with observed SSTs, atmospheric models forced with predicted SSTs, and coupled ocean–atmosphere models). Atmospheric models with observed SST forcing demonstrate a moderate skill in hindcasting spring-and summertime two-meter air temperature anomalies, whereas coupled models and atmospheric models forced with predicted SSTs lack similar skill. Probabilistic and categorical hindcasts mirror the deterministic findings, i.e., there is very high skill for winter precipitation and none for summer precipitation. When skillful, the models are conservative, such that low-probability hindcasts tend to be overestimates, whereas high-probability hindcasts tend to be underestimates.     

Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction

A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere.     

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.     

一个全球海气耦合模式跨季度汛期预测能力的初步检验和评估

文中利用一个全球大气 海洋耦合模式 ,对中国汛期气候异常进行了 1991～ 2 0 0 1年共 11a的跨季度回报试验和检验研究。采用一套多指标的评估方法 ,对该模式的预报性能进行系统的定量评估。结果表明 ,该模式对中国汛期降水和温度及夏季北半球大尺度环流场等都有一定的跨季度预报能力。模式对中国不同区域夏季降水的预测能力有所不同。总的来说 ,模式对中国东部和西部的降水趋势回报较好 ,模式预报好于气候预报和持续性预报。从相关系数指标来看 ,模式跨季度预测夏季温度的技巧在中国西部比中国东部高。     

全球海洋资料同化系统ZFL_GODAS的研制和初步评估试验

本研究发展了一个全球海洋资料同化系统ZFL_GODAS。该系统是一个短期气候数值预测业务系统的子系统,为短期气候预测海气耦合模式提供全球海洋初始场。系统能够同化的观测资料包括卫星高度计资料、卫星海表温度(SST)资料,以及Argo、XBT、TAO等各种不同来源的现场温盐廓线资料。系统使用的海洋模式为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开发的气候系统海洋模式LICOM1.0,同化方案为集合最优插值(EnOI)方案。系统使用一个由海洋模式自由积分得到的静态样本来估计背景场误差协方差。这样的基于集合样本的背景场误差协方差具有多变量协变、各向异性的特征,且能反映海洋物理过程固有的空间尺度特征。针对EnOI同化程序的特点,开发了一套特色鲜明、负载均衡、高效的并行化同化程序。本文通过与不同类型观测资料的比较,对同化系统的性能进行了评估。通过比较海表温度和海面高度的年际变率,海表温度异常随时间的变化,SST、海面高度异常(SLA)以及次表层温盐预报产品的均方根误差,5年平均温度偏差廓线、平均盐度廓线、平均纬向流速廓线等发现:系统工作正常、同化效果较好;经过同化以后,各变量都更加接近观测,误差更小,与观测场的相关性更好,可以为短期气候预测系统提供较好的海洋初始场,也可以为物理海洋学的研究提供有效的再分析资料。     

区域海气耦合模式对中国夏季降水的模拟

以区域气候模式RegCM3和普林斯顿海洋模式POM为基础,建立了一个区域海气耦合模式,对1963-2002年中国夏季气候进行模拟,重点分析该耦合模式对中国夏季降水的模拟性能以及降水模拟改进的可能原因.结果表明:耦合模式对中国夏季雨带分布的模拟明显优于控制试验(单独的大气模式),对长江流域以及华南降水的模拟性能改进尤为明显,同时耦合模式能够更为真实地刻画中国东部地区汛期雨带的移动.对降水的年际变化分析发现,耦合模式模拟的1963-2002年中国夏季降水年际变率与观测吻合,模拟的夏季长江流域降水与观测降水相关系数达到0.48,模拟的华南夏季降水与观测的相关系数达到0.61,而控制试验结果与观测降水的相关系数均较小.对中国东部长江流域夏季降水与近海海温的相关分析表明,用给定海温驱动的大气模式,并不能正确模拟出中国东部夏季降水与海温的关系,而耦合模式能够较好地模拟出长江流域与孟加拉湾、南海以及黑潮区海温的关系,与GISST(全球海冰和海表温度)和观测降水相关关系一致.对水汽输送通量的分析发现,控制试验模拟的水汽输送路径与NCEP/NCAR再分析资料相比差别较大,耦合模式模拟的来自海洋上的水汽输送强度和路径与NCEP/NCAR再分析资料一致,提高了耦合模式对水汽输送的模拟能力,从而改善了模式对华南以及长江流域降水的模拟.     

辐射参数化方案对气候模拟和回报的影响

研究两种不同辐射参数化方案(Morcrette 方案和Ritter方案)对一个大气环流模式及其与一个海洋环流模式的耦合模式的模拟和回报效果的影响. 大气模式的模拟结果表明,采用Morcrette方案模拟的降水较采用Ritter方案有明显改进.采用Morcrette辐射方案的大气模式对夏季500 hPa高度场的模拟比采用Ritter方案的大气模式有明显改进,但对冬季500 hPa高度场的模拟没有改进.大气-海洋耦合模式的20年夏季回报结果表明采用Morcrette方案回报的夏季降水在华北和江淮地区明显比采用Ritter辐射方案好;对于夏季温度,带有Morcrette方案的耦合模式的回报在江淮地区没有带有Ritter方案的耦合模式好,但在黄河以北和新疆等地区,前者明显好于后者.     

Global seasonal climate predictability in a two tiered forecast system. Part II: boreal winter and spring seasons

We examine the Florida Climate Institute–Florida State University Seasonal Hindcast (FISH50) skill at a relatively high (50 km grid) resolution two tiered Atmospheric General Circulation Model (AGCM) for boreal winter and spring seasons at zero and one season lead respectively. The AGCM in FISH50 is forced with bias corrected forecast sea surface temperature averaged from two dynamical coupled ocean–atmosphere models. The comparison of the hindcast skills of precipitation and surface temperature from FISH50 with the coupled ocean–atmosphere models reveals that the probabilistic skill is nearly comparable in the two types of forecast systems (with some improvements in FISH50 outside of the global tropics). Furthermore the drop in skill in going from zero lead (boreal winter) to one season lead (boreal spring) is also similar in FISH50 and the coupled ocean–atmosphere models. Both the forecast systems also show that surface temperature hindcasts have more skill than the precipitation hindcasts and that land based precipitation hindcasts have slightly lower skill than the corresponding hindcasts over the ocean.     

区域气候模式对中国夏季降水的10年回报试验及其评估分析

该文使用国家气候中心全球海气耦合模式嵌套区域气候模式(RegCM_NCC)对1991～2000年中国夏季降水进行了数值回报试验.从模式回报的降水10年平均状况来看,模式基本上能够反映这10年夏季的平均状况.用国家气候中心预报评分P、技巧评分SS、距平相关系数(ACC)和异常气候评分TS 4种评估参数对模式的回报试验进行了总体评估分析,结果表明该模式对我国汛期降水具有一定的跨季度预报能力,对部分地区(西部,东北,长江下游等)有较强的预报能力.从相关系数来看,预报准确率较高(即相关系数较高)的地区是中国东北地区的北部(内蒙古的北部和黑龙江的西北部),内蒙古-河套-长江中游地区,新疆的西北部,西藏的东部和四川的西部,江南部分地区,广西部分地区.这些地区的中心一般均超过0.90的信度检验.160个站中相关系数高于0.20的有54个,约占33.73%.     

Simulation of China Summer Precipitation Using a Regional Air-Sea Coupled Model

A regional air-sea coupled model based on the regional climate model(RegCM3)and the regional oceanic model POM(Princeton Ocean Model)is developed and a series of experiments are performed to verify the ability of the coupled model in simulating the summer precipitation over China from 1963 to 2002.The results show that the space correlation coefficients between the GISST(Global Ice and Sea Surface Temperature)data and the simulated SST by RegCM3-POM exceed 0.9.Compared with the uncoupled experiments,the coupled model RegCM3-POM has a better performance in simulating the mean summer(June to August)precipitation over China,and the distribution of the rainband in the coupled model is more accurate.The improvement of the rainfall simulation is significant over the Yangtze River Valley and in South China.The rainbelt intraseasoaal evolution over eastern China in summer indicates that the simulation ability of RegCM3-POM is improved in comparison with the uncoupled model.The interannual summer rainfall variation over eastern China simulated by RegCM3-POM is in accordance with observation,while the spatial pattern of the interannual summer rainfall variation in the uncoupled model is inaccurate.The simulated correlation coefficient between the summer rainfall in the uncoupled model RegCM3 and observation is0.30 over the Yangtze River Valley and 0.29 in South China.The coefficient between the rainfall in the coupled RegCM3-POM and observation is 0.48 over the Yangtze River Valley and 0.61 in South China.The RegCM3-POM has successfully simulated the correlation coefficients between summer rainfall in the Yangtze River Valley and SST anomalies of the Bay of Bengal,South China Sea,and the Kuroshio area,whereas the uncoupled model RegCM3 fails to reproduce this relationship.The study further shows that the monsoon circulation and the path of the moisture transport flux simulated by RegCM3-POM are in good agreement with the NCEP/NCAR data.     

区域气候模式RegCM_NCC对华北冬季气温和降水的预报评估

利用国家气候中心全球海气耦合模式CGCM_NCC的输出结果驱动区域气候模式RegCM_NCC对华北地区1991—2010年冬季气温和降水进行了数值回报试验,并采用国家气候中心的业务预报评分(P)等5个评估参数对模式的回报结果进行了评估分析。结果表明:RegCM_NCC回报的华北地区20年冬季气温的P评分多年平均值为70.4分,其中大部分年份平均气温的P评分在60分以上,80分以上的有11年,11年的预报相对于随机预报和气候预报有正技巧;20年冬季降水的P评分多年平均值为66.3分,13年冬季降水的P评分在60分以上,在80分以上的有5年,8年的预报相对于随机预报有正技巧,有11年的预报相对于气候预报有正技巧。冬季Nino3.4区海温距平为负和东大西洋-俄罗斯西部型遥相关指数为负,均有利于回报的华北冬季气温P评分提高。     

北半球夏季热带季节内振荡影响我国夏季降水的规律和预测方法

利用1979—2018年夏季逐日观测和再分析数据，对北半球夏季热带季节内振荡影响我国夏季降水的规律和预测方法开展了研究。首先，利用非传统滤波即异常相对倾向（Anomalous Relative Tendency，ART）方法获取了气象要素的次季节变化分量，并采用EOF分析方法提取了北半球夏季热带主要季节内振荡信号，结果表明向外长波辐射（Outgoing Longwave Radiation，OLR）异常相对倾向EOF前两个模态共同反映了北半球夏季起源于印度洋并向东和向北传播的、具有30~60 d周期的季节内振荡（Boreal Summer Intraseasonal Oscillation，BSISO）信号。回归分析表明，该季节内振荡信号能够导致当地及其北面地区低层风场和位势高度场异常，影响该地区及其北面地区的水汽辐合辐散，从而能引起我国尤其是我国南方地区季节内旱涝变化，并一定程度上反映了我国异常雨带的向北推进过程。而后，将提取的热带主要季节内振荡信号作为预测因子，将降水异常相对倾向作为先行预板对象，利用多元线性回归方法构建了我国夏季旬降水异常相对倾向的预报模型，将预报的旬降水异常相对倾向加上观测已知的降水近期背景距平，从而得到旬降水距平的预报结果。通过历史回报和交叉检验，评估了该模型对梅雨期我国江淮流域降水（包括2020年梅汛期异常降水）的次季节预测能力。     

NUMERICAL SIMULATION STUDIES ON SHORT-RANGE CLIMATIC VARIATION

Several global and regional climatic models(including atmosphere models, ocean models and coupledatmosphere-ocean models)are improved and developed to simulate the predictability of short-range(i.e.monthly,sea-sonal,interannual)climate variability,based on the understanding of global and regional climatic characteristics andprocesses,and according to the theorem of climatological dynamics.The results of numerical experiment show that someare very encouraging,some others reveal problems existed.However,the model and data are being more and more ad-vanced.     

Decadal climate predictions with a coupled OAGCM initialized with oceanic reanalyses

We investigate the effects of realistic oceanic initial conditions on a set of decadal climate predictions performed with a state-of-the-art coupled ocean-atmosphere general circulation model. The decadal predictions are performed in both retrospective (hindcast) and forecast modes. Specifically, the full set of prediction experiments consists of 3-member ensembles of 30-year simulations, starting at 5-year intervals from 1960 to 2005, using historical radiative forcing conditions for the 1960–2005 period, followed by RCP4.5 scenario settings for the 2006–2035 period. The ocean initial states are provided by ocean reanalyses differing by assimilation methods and assimilated data, but obtained with the same ocean model. The use of alternative ocean reanalyses yields the required perturbation of the full three-dimensional ocean state aimed at generating the ensemble members spread. A full-value initialization technique is adopted. The predictive skill of the system appears to be driven to large extent by trends in the radiative forcing. However, after detrending, a residual skill over specific regions of the ocean emerges in the near-term. Specifically, natural fluctuations in the North Atlantic sea-surface temperature (SST) associated with large-scale multi-decadal variability modes are predictable in the 2–5 year range. This is consistent with significant predictive skill found in the Atlantic meridional overturning circulation over a similar timescale. The dependency of forecast skill on ocean initialization is analysed, revealing a strong impact of details of ocean data assimilation products on the system predictive skill. This points to the need of reducing the large uncertainties that currently affect global ocean reanalyses, in the perspective of providing reliable near-term climate predictions.