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1.
在动力相似预报中引入多个参考态的更新   总被引:7,自引:2,他引:7  
任宏利  丑纪范 《气象学报》2006,64(3):315-324
针对如何更有效地利用历史资料中的相似信息提高预报水平的问题,在已有相似-动力模式研究基础上,进一步探讨了相似误差订正方法(ACE)的若干理论和技术问题,分析表明,ACE是对以相似离差方程和相似误差订正方程为理论依据的方法的再发展。在此基础上,提出了相似的更新问题和多个参考态的引入,并进而发展出一种考虑多参考态更新的动力相似预报新方法(MRSU)。这一方法通过引入相似更新周期的新概念,在预报进行到相似更新周期时重新选取多个参考态,并采用超平面近似法将相似-动力模式产生的多个预报估计成最佳预报向量,这样的“选取-估计”过程循环往复,从而完成整个时段的预报。Lorenz模式试验显示,相比于以往的相似-动力模式预报,MRSU能更有效减小预报误差,提高预报技巧,并且,ACE的理论优势应用前景也被初步证实。综合诸多研究结果,给出了MRSU的概念流程,这里针对复杂数值模式采用了ACE,能够等价实现相似-动力模式预报过程,无需重建模式,更易于推广。  相似文献   

2.
Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors (ACE) of model is developed in this paper. The ACE can combine effectively statistical and dynamical methods, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasonably absorb the information of a great many analogues in historical data in order to reduce model errors and improve forecast skill. Furthermore, the ACE may identify specific historical data for the solution of the inverse problem in terms of the particularity of current forecast. The qualitative analyses show that the ACE is theoretically equivalent to the principle of the previous analogue-dynamical model, but need not rebuild the complicated analogue-deviation model, so has better feasibility and operational foreground. Moreover, under the ideal situations, when numerical models or historical analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.  相似文献   

3.
统计-动力相结合的相似误差订正法   总被引:22,自引:6,他引:22  
任宏利  丑纪范 《气象学报》2005,63(6):988-993
根据大气相似性原理,提出了利用历史资料的相似信息估计模式误差的反问题,并发展了一种相似误差订正(ACE)方法。该方法将统计和动力两种方法有机结合,在不改变现有数值预报模式的前提下,既充分利用了动力学发展的成就,又能够有效提取大量历史资料中的相似信息,达到减小模式误差、改进当前预报的目的。而且,ACE方法能够针对当前预报的特殊性来区分所利用过去资料的特殊性,提取历史相似信息间接求解反问题。定性分析表明,ACE方法与以往相似-动力模式原理是等价的,但无需重新建立复杂的相似离差预报模式,更具可行性和业务应用前景。在理想化的极限情形下,当数值模式或历史相似完全准确时,ACE方法的预报结果将分别蜕变为动力或统计学方法的预报结果。  相似文献   

4.
With the Zebiak-Cane (ZC) model, the initial error that has the largest effect on ENSO prediction is explored by conditional nonlinear optimal perturbation (CNOP). The results demonstrate that CNOP-type errors cause the largest prediction error of ENSO in the ZC model. By analyzing the behavior of CNOPtype errors, we find that for the normal states and the relatively weak E1 Nifio events in the ZC model, the predictions tend to yield false alarms due to the uncertainties caused by CNOP. For the relatively strong E1 Nino events, the ZC model largely underestimates their intensities. Also, our results suggest that the error growth of E1 Nifio in the ZC model depends on the phases of both the annual cycle and ENSO. The condition during northern spring and summer is most favorable for the error growth. The ENSO prediction bestriding these two seasons may be the most difficult. A linear singular vector (LSV) approach is also used to estimate the error growth of ENSO, but it underestimates the prediction uncertainties of ENSO in the ZC model. This result indicates that the different initial errors cause different amplitudes of prediction errors though they have same magnitudes. CNOP yields the severest prediction uncertainty. That is to say, the prediction skill of ENSO is closely related to the types of initial error. This finding illustrates a theoretical basis of data assimilation. It is expected that a data assimilation method can filter the initial errors related to CNOP and improve the ENSO forecast skill.  相似文献   

5.
With the Zebiak-Cane (ZC) model, the initial error that has the largest effect on ENSO prediction is explored by conditional nonlinear optimal perturbation (CNOP). The results demonstrate that CNOP-type errors cause the largest prediction error of ENSO in the ZC model. By analyzing the behavior of CNOP- type errors, we find that for the normal states and the relatively weak EI Nino events in the ZC model, the predictions tend to yield false alarms due to the uncertainties caused by CNOP. For the relatively strong EI Nino events, the ZC model largely underestimates their intensities. Also, our results suggest that the error growth of EI Nino in the ZC model depends on the phases of both the annual cycle and ENSO. The condition during northern spring and summer is most favorable for the error growth. The ENSO prediction bestriding these two seasons may be the most difficult. A linear singular vector (LSV) approach is also used to estimate the error growth of ENSO, but it underestimates the prediction uncertainties of ENSO in the ZC model. This result indicates that the different initial errors cause different amplitudes of prediction errors though they have same magnitudes. CNOP yields the severest prediction uncertainty. That is to say, the prediction skill of ENSO is closely related to the types of initial error. This finding illustrates a theoretical basis of data assimilation. It is expected that a data assimilation method can filter the initial errors related to CNOP and improve the ENSO forecast skill.  相似文献   

6.
胡帅  吴波  周天军 《大气科学》2019,43(4):831-845
印度洋偶极子(IOD)是热带印度洋年际变率主导模态之一,对于区域乃至全球气候有重要影响。准确预报IOD对于短期气候预测具有重要意义。中国科学院大气物理研究所最近建立了近期气候预测系统IAP-DecPreS,其初始化方案采用“集合最优插值—分析增量更新”(EnOI-IAU)方案,能够同化观测的海洋次表层温度廓线资料。本文分析了IAP-DecPreS季节回报试验对IOD的回报技巧,重点比较了全场同化和异常场同化两种初始化策略下预测系统对IOD的回报技巧。分析表明,8月起报秋季IOD,无论从确定性预报还是概率性预报的角度,基于全场同化的回报试验技巧均高于异常场同化的回报试验。对于5月起报的秋季IOD,基于两种初始化策略的回报试验技巧相当。研究发现,全场同化策略相对于异常场的优势主要源于它提高了对伴随ENSO发生的IOD的预报技巧。ENSO遥强迫触发的热带东印度洋“风—蒸发—SST”正反馈过程是IOD发展和维持的关键。采用全场同化策略的回报结果能够更好地模拟出IOD发展过程中ENSO遥强迫产生的异常降水场和异常风场的空间分布特征;而采用异常场同化策略,模拟的异常降水场和风场偏差较大。导致两种初始化策略预测结果技巧差异的主要原因是,全场同化能够减小模式对热带印度洋气候平均态降水固有的模拟偏差,从而提升了热带印度洋对ENSO遥强迫响应的模拟能力。而异常场同化由于在同化过程中保持了模式固有的气候平均态,因此模拟的热带印度洋对ENSO遥强迫的响应存在与模式自由积分类似的模拟偏差。  相似文献   

7.
一个ENSO动力-相似误差订正模式及其后报初检验   总被引:4,自引:1,他引:4  
为有效利用历史资料中的相似信息,减小模式误差对ENSO这类跨季节-年际尺度预测问题的影响提高动力模式的预测水平.作者利用一种基于统计相似的模式误差订正方法,以国家气候中心简化海气耦合模式为平台建立了相应的动力-相似误差订正(DAEC)模式,并着重探讨了系统相似程度(全相似或部分相似)、误差重估周期以及相似样本个数等因素对预报效果的影响.结果表明,利用该方法可以有效地改善原有模式的预报性能,其中 "全相似" 比 "部分相似" 更能反映海气耦合系统的相似程度,从而对模式误差做出更为准确的估计,使预报误差明显减小.海洋和大气的误差重估周期对结果也有较大影响,在不同相似程度下分别存在着某种最优配置使得预报效果达到最佳.另外,在对相似样本存在状况及影响的研究中则发现在当前资料长度内整体上只存在着有限个相似样本,在此范围内随着样本取样数目的增加DAEC模式的预报性能逐渐提高.  相似文献   

8.
Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas (so-called "sensitive areas"). And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Niño prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Niño prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year, increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.  相似文献   

9.
针对未来1~10 a气候状态的近期气候预测(年代际预测)是当前国际气候领域的研究热点。本文综述了中国科学院大气物理研究所发展的基于耦合气候系统模式的年代际气候预测系统IAP-DecPreS相关的研究进展。IAP-DecPreS系统的核心部分是耦合模式海洋分量初始化方案,“集合最优插值-分析增量更新”(EnOI-IAU)方案,该方案将集合最优插值(EnOI)和增量分析更新(IAU)结合起来,能够同化原始的海洋次表层温度廓线观测资料,对耦合模式进行初始化。系统的年代际回报试验表明,IAP-DecPreS对太平洋年代际振荡和大西洋多年代际变率的预测技巧与耦合模式比较计划第五阶段(CMIP5)技巧较高的模式相当。IAP-DecPreS系统被广泛应用于气候预测相关研究,包括火山气溶胶对年代际预测技巧的影响,全场同化和异常场同化两种不同的初始化方法对ENSO、印度洋偶极子模态和印度洋洋盆模态等的预测技巧的影响。最后,结合国际发展态势,对未来IAP-DecPreS的发展进行了讨论。  相似文献   

10.
The impact of the warm SST bias in the Southeast Pacific (SEP) on the quality of seasonal and interannual variability and ENSO prediction in a coupled GCM is investigated. The reduction of this bias is achieved by means of empirical heat flux correction that is constant in time. It leads to a wide range of changes in the tropical Pacific climate including enhanced southeast trades, well-defined dry zone in the SEP, better simulation of the South Pacific Convergence Zone and stronger cross-equatorial asymmetry of the mean state in the eastern Pacific. As a result of the mean climate correction, significant improvements in the simulation of the seasonal cycle of the oceanic and atmospheric states are also observed both at the equator and basin-wide. Due to more realistic simulation of the seasonal evolution of the cold tongue, tropical convection and surface winds in the corrected version of the model, phase-lock of ENSO to the annual cycle looses its strong semi-annual component and becomes quite similar to the observed, although the amplitude of ENSO is reduced. Zonal wind stress response to the SST anomalies in the central-eastern Pacific also becomes more realistic. ENSO retrospective forecast experiments conducted with the directly coupled and the flux-corrected versions of the model demonstrate that deficiencies in the seasonal evolution of the cold tongue/Inter-Tropical Convergence Zone complex (that were largely due to the SEP bias in this model) and the related errors in the ENSO phase-lock to the annual cycle can seriously degrade ENSO prediction. By reducing these errors, ENSO predictive skill in the coupled model was substantially enhanced.  相似文献   

11.
孙丞虎  李维京 《气象学报》2009,67(6):1113-1123
为了改善模式初始场质量,减少初值与模式不协调对ENSO预测的影响,针对国家气候中心NCCo海-气耦合模式原初始化方案动力小协调的问题,从利用模式长期耦合模拟资料中的模式气候吸引子信息的角度出发,发展了一种获取观测资料中与模式相协调分量的信息重构方法,提出了一种模式气候吸引子信息约束下的动力协调初始化方案.对该方案回报检验的结果表明:通过反演NCCo海-气耦合模式模拟资料中的模式气候吸引子信息,有助于获取观测资料中与模式相协调的信息分量特征,实现了初始化过程中动力模式与所同化观测资料间的协调.这种基于信息重构方法的动力协调初始化方案,既可以延续原初始化方案利用观测信息较多的优势,又克服了原方案中观测资料和动力模式不协调的缺陷.这种新的初始化方案,消除了观测资料和模式不协调在初始场中产生的小尺度高频噪声,突出了与NCCo模式动力特征相适应的ENSO尺度信息.进而抑制了初始场中高频噪声所引起的快变预报误差的增长,提高了模式的预测技巧.  相似文献   

12.
数值天气预报———另类途径的必要性和可行性   总被引:5,自引:6,他引:5       下载免费PDF全文
通过讨论省 (甚至地、市) 气象部门要不要开展数值天气预报工作的问题, 认为不是所有的地方都要开展, 只是那些希望搞科研型业务、迫切要求提高当地高影响天气的预报准确率的地方要开展。对于如何开展的问题, 提出不是去重复类似于主流途径的做法, 而是开辟另类途径, 并阐述了另类途径的内容、方法和意义。强调开展另类途径无需构建模式 (这是非常困难的工作), 只需运转现成的模式, 借助所关心的现象的历史数据来改造现成模式, 使之本地化, 是完全可行的。  相似文献   

13.
南京信息工程大学气候预测系统1.0版(NUIST CFS1.0)是基于日本海洋科学技术开发机构(JAMSTEC)的SINTEX-F模式发展而来,可以实现对全球气候异常的季节-年际预测。对过去近40 a的集合历史回报预测试验结果的评估发现,该预测系统对热带太平洋和印度洋海温异常具有良好的预测技巧,并且该系统能提前1.5~2 a对ENSO(Nino3.4指数)做出有技巧的预测(即相关系数达0.5),同时也可以提前1~2个季节对印度洋偶极子(IOD)做出有较高技巧的预测,展现了对主要热带气候信号的良好预测技巧。但是与国内外所有动力模式预测系统类似,该系统对东亚地区的气候异常预测还存在较大的不足。考虑到ENSO对东亚地区气候异常的强烈影响,本文尝试去除与ENSO预测相关的系统偏差来初步订正东亚地区夏季温度异常和降水距平百分率的预测结果。对比订正前后的结果表明,这一简单的订正方法有助于提高我国气候异常的预测准确率。同时选取2019年夏季气温异常和降水距平百分率的实时预测结果作为个例进行分析,发现订正能够提供一定的技巧改善,但与观测结果相比仍存在较大偏差,需要在今后的工作中不断改进完善。此外,本文也初步评估了NUIST CFS1.0对我国冬春季的气候预测技巧,并提供了经简单订正后的2019/2020年冬季和2020年春季的实时预测结果。  相似文献   

14.
数值预报误差订正技术中相似-动力方法的发展   总被引:3,自引:0,他引:3       下载免费PDF全文
Due to the increasing requirement for high-level weather and climate forecasting accuracy, it is necessary to exploit a strategy for model error correction while developing numerical modeling and data assimilation techniques. This study classifies the correction strategies according to the types of forecast errors, and reviews recent studies on these correction strategies. Among others, the analogue-dynamical method has been developed in China, which combines statistical methods with the dynamical model, corrects model errors based on analogue information, and effectively utilizes historical data in dynamical forecasts. In this study, the fundamental principles and technical solutions of the analogue-dynamical method and associated development history for forecasts on different timescales are introduced. It is shown that this method can effectively improve medium- and extended-range forecasts, monthly-average circulation forecast, and short-term climate prediction. As an innovative technique independently developed in China, the analogue- dynamical method plays an important role in both weather forecast and climate prediction, and has potential applications in wider fields.  相似文献   

15.
基于国家气候中心气候系统模式1.1版本(BCC_CSM1.1m)的历史回报数据,利用时间相关系数和均方根误差等确定性技巧评分,对西伯利亚高压、阿留申低压、东亚冬季风3种东亚地区冬季典型环流系统的预报技巧进行检验评估,并通过时间序列分析和空间相关系数等方法,分析东亚地区冬季典型环流系统的可预报性来源。结果表明:由于模式对热带海洋和北太平洋海平面气压的预测偏差小、对欧亚大陆的预测偏差大,模式对阿留申低压、东亚冬季风的预测技巧高于西伯利亚高压。进一步分析表明:厄尔尼诺和南方涛动(ENSO)是阿留申低压和东亚冬季风的重要可预报性来源,而土壤温度是西伯利亚高压的重要可预报性来源,并受ENSO调制。此外,东亚冬季风的预报技巧也受到西伯利亚高压预报技巧的制约。  相似文献   

16.
鉴于当前短期气候预测中,纯粹使用动力学方法尚不能完全满足气候预测业务的需要,因此有必要在策略上采取动力和统计相结合的办法.在具体实现手段上,简要介绍了从历史资料中提炼预测信息,发展了一种基于历史相似误差订正的相似—动力短期气候预测新方法.分别在月、季节以及ENSO等短期气候预测领域相继开展了试验和应用,取得了—些令人鼓舞的初步结果,为下一步深入开展有关短期气候预测科学的研究提供了些许借鉴.  相似文献   

17.
不完整气象资料下基于作物模型的产量预报方法   总被引:6,自引:5,他引:1       下载免费PDF全文
针对基于作物模型开展产量实时预报后期气象资料的获取问题,提出通过相似类比,从历史气象资料库中获取替代资料的方案,基于CERES-Rice模型系统评估了平均值处理方案和历史相似类比方案的可预报性和误差分布特征。结果表明:水稻产量对成熟前2个月内的气象条件较为敏感,基于气象资料和作物模型开展产量预测,在5%误差范围内可获得60%以上的预测概率;以多年气候平均值替代起报日后期气象资料,在成熟前2个月起报预测概率约为60%,成熟前1个月约为70%,但预报误差系统性偏高;采用气候相似类比方法,从历史气象资料中获取起报日后期替代资料,可有效降低预报误差的系统偏差,若引入后期气候趋势信息,成熟前2个月起报预测概率可达80%以上,较采用历史平均值有显著提高。研究结果为基于作物模型和气象观测及气候预测信息开展产量预报提供了技术方案。  相似文献   

18.
The El Niño–Southern Oscillation (ENSO) reflects anomalous variations in the sea surface temperature (SST) and atmospheric circulation over the tropical central–eastern Pacific. It remarkably impacts on weather and climate worldwide, so monitoring and prediction of ENSO draw intensive research. However, there is not yet a unique standard internationally for identifying the timing, intensity, and type of ENSO events. The National Climate Center of China Meteorological Administration (NCC/CMA) has led the effort to establish a national identification standard of ENSO events, which was officially endorsed by the National Standardization Administration of China and implemented operationally in NCC/CMA in 2017. In this paper, two key aspects of this standard are introduced. First, the Niño3.4 SST anomaly index, which is well-recognized in the international ENSO research community and used operationally in the US, has replaced the previous Niño Z index and been used to identify the start, end, and peak times, and intensity of ENSO events. Second, two new indices—the eastern Pacific ENSO (EP) index and the central Pacific ENSO (CP) index, based on the SST conditions in Niño3 and Niño4 region respectively, are calculated to first determine the ENSO type before monitoring and assessing the impacts of ENSO on China’s climate. With this standard, all historical ENSO events since 1950 are consistently re-identified; their distinct properties are diagnosed and presented; and the impacts of ENSO events under different types on China’s climate are re-assessed. This standard is also employed to validate the intensity, grade, and type of the ENSO events predicted by the NCC/CMA operational ENSO prediction system. The new standard and the thus derived unified set of re-analyzed historical ENSO events and associated information provide a good reference for better monitoring and prediction of future ENSO events.  相似文献   

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Based on the viewpoint that the North Atlantic Oscillation(NAO) has an intrinsic timescale of approximate two weeks and can be treated as an initial value problem, targeted observations for improving the prediction of the onset of NAO events are investigated by using the conditional nonlinear optimal perturbation(CNOP) method with a quasigeostrophic model. The results show that flow-dependent sensitive areas for the prediction of NAO onset are mainly located over North Atlantic and its upstream regions. Targeted observations over the main sensitive areas could improve NAO onset prediction in most cases(approximately 75%) due to reduced errors in anomalous eddy vorticity forcing(EVF) projection in the typical NAO mode. Moreover, a flow-independent sensitive area is determined based on the winter climatological flow, which is located over North America and its adjacent ocean. The NAO onset prediction can also be improved by targeted observations over the flow-independent sensitive area, but the skill improvement is somewhat lower than that derived from observations over the flow-dependent sensitive area. The above results indicate that targeted observations over sensitive areas identified by the CNOP method can help to improve the onset prediction of NAO events.  相似文献   

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