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1.
Westerly wind bursts or events (WWBs or WWEs) are commonly viewed as stochastic processes, independent of any oceanic forcing. Some recent work and observations have suggested that these events can be viewed as state-dependent noise in that they are modulated by the SST variability. This potentially affects the predictability of the El Niño Southern Oscillation (ENSO). In this study, we examine the impact of parameterized WWBs on ENSO variability in the Community Climate System Model version 3.0 and 4.0 (CCSM3 and CCSM4). The WWBs parameterization is derived based on 50 years of atmospheric reanalysis data and observed estimates of tropical Pacific SST. To study the impact of WWBs three experiments are performed. In the first experiment, the model is integrated for several hundred years with no prescribed WWBs events (i.e. the control). In the second case, state-independent WWBs events are introduced. In other words, the occurrence, location, duration, and scale of the WWBs are determined (within bounds) randomly. These wind events are always positive (eastward) without a westward counterpart and are totally independent of the anomalies in the state variables, and can be thought of as additive noise. For the third case, the WWBs are introduced but as multiplicative noise or state-dependent forcing, modulated by SST anomalies.The statistical moments for the Niño 3.4 index shows that the state-dependent case produced larger El Niño Southern Oscillation (ENSO) events and the bias toward stronger cold events is reduced as compared to the control and the state-independent runs. There is very little difference between the control and the state-independent WWB simulations suggesting that the deterministic component of the burst is responsible for reshaping the ENSO events. Lag-lead correlation of ocean variables with Niño 3.4 index suggests larger temporal coherence of the ENSO events. This, along with SSTA composites, also suggest a shift toward a more self sustained mechanism as the experiments progress from the control to the state dependent WWBs. Overall, the parameterized WWBs have the capability to modify the ENSO regime in the CGCM, demonstrating the importance of sub-seasonal variability on interannual time scales. The fast varying (stochastic) component of WWB is of little importance, whereas the slow (SST dependent) component has a significant impact overall. The results are consistent between CCSM3 and CCSM4. 相似文献
2.
To understand the diversity of the El Niño-Southern Oscillation (ENSO) under the background of Pacific decadal oscillation (PDO) during recent decades, characteristics of westerly wind bursts (WWBs) during positive and negative phases of the PDO were analyzed. It is shown that, during the ENSO developing period, the El Niño evolution may be affected by stronger or more frequent WWBs in the positive PDO phase than in the negative PDO phase. The sustained effects of atmospheric dynamics on the equatorial ocean can be indicated by the accumulated WWB strength, which contains most WWB characteristics, including the accumulated days, occurrence frequency, strength, and spatial range of WWBs. The synoptic/climate systems that are directly related to WWBs show a wider spatial distribution in the positive PDO phase than in the negative PDO phase. 相似文献
3.
西风爆发(WWB)对赤道西太平洋暖池SST的影响是WWB与ENSO相互作用的一个重要环节。作者运用TOGA(TropicalOcean-GlobalAtmosphere)-COARE(CoupledOcean-AtmosphereResponseExperiment)期间暖池海区8个浮标的观测资料，根 据Stenven和Niiler的热量平衡诊断方法，从能量平衡角度分析了赤道156°E附近SST对1992年9月到1993年1月期间两次WWB事件的响应。两次WWB期间，SST都是在 WWB之前和其后升温，而在WWB期间降温，升温和降温的幅度均为1℃左右。热量平衡分析结果表明，季节内时间尺度上海表热通量是导致赤道西太平洋暖池混合层温度变化的主要因素。在海表热通量中，短波辐射和潜热是变化量最大的两项，决定着净通量的正负，其他项的变化则相对较小。水平平流项有时可以超过海表热通量的作用，其作用不可忽略。两次WWB的过程中，季节变化造成的混合层的温盐结构和流场结构的差异是导致两次WWB事件时上层海洋热量平衡差别的主要因素。另外，混合层的厚度也有明显的变化，而混合层厚度变化的差异则是与流场的结构以及WWB的向东传播特征密切相关。 相似文献
4.
The retrospective prediction of ENSO from 1881 to 2000 by a hybrid coupled model: (II) Interdecadal and decadal variations in predictability 总被引：1，自引：0，他引：1
In this study, the retrospective predictions of ENSO (El Niño and Southern Oscillation) were performed for the period from 1881 to 2000 using a hybrid coupled model, which is an ocean general circulation model coupled to a linear statistical atmospheric model, and using a newly developed initialization scheme of SST assimilation by Ensemble Kalman Filter. With the retrospective predictions of the past 120 years, some important issues of ENSO predictability (measured by correlation and RMSE skills of NINO3 sea surface temperature anomaly index) were studied including decadal/interdecadal variations in ENSO predictability and the mechanisms responsible for these variations. Emphasis was placed on investigating the relationship between ENSO predictability and various characteristics of ENSO system such as the signal strength, the irregularity of periodicity, the noise and the nonlinearity. It is found that there are significant decadal/interdecadal variations in the prediction skills of ENSO during the past 120 years. The ENSO events were more predictable during the late nineteenth and the late twentieth centuries. The decadal/interdecadal variations of prediction skills are strongly related to the strength of sea-surface temperature anomaly (SSTA) signals, especially to the strength of SSTA signals at the frequencies of 2–4 year periods. The SSTA persistence, dominated by SSTA signals at frequencies over 4-year periods, also has a positive relationship to prediction skills. The high-frequency noise, on the other hand, has a strong inverse relationship to prediction skills, suggesting that it also probably plays an important role in ENSO predictability. 相似文献
5.
We analyse the differences in the properties of the El Niño Southern Oscillation (ENSO) in a set of 17 coupled integrations with the flux-adjusted, 19-level HadCM3 model with perturbed atmospheric parameters. Within this ensemble, the standard deviation of the NINO3.4 deseasonalised SSTs ranges from 0.6 to 1.3 K. The systematic changes in the properties of the ENSO with increasing amplitude confirm that ENSO in HadCM3 is prevalently a surface (or SST) mode. The tropical-Pacific SST variability in the ensemble of coupled integrations correlates positively with the SST variability in the corresponding ensemble of atmosphere models coupled with a static mixed-layer ocean (“slab” models) perturbed with the same changes in atmospheric parameters. Comparison with the respective coupled ENSO-neutral climatologies and with the slab-model climatologies indicates low-cloud cover to be an important controlling factor of the strength of the ENSO within the ensemble. Our analysis suggests that, in the HadCM3 model, increased SST variability localised in the south-east tropical Pacific, not originating from ENSO and associated with increased amounts of tropical stratocumulus cloud, causes increased ENSO variability via an atmospheric bridge mechanism. The relationship with cloud cover also results in a negative correlation between the ENSO activity and the model’s climate sensitivity to doubling CO2. 相似文献
6.
Rong-Hua Zhang 《大气科学进展》2015,32(3):301-318
A hybrid coupled model(HCM) is constructed for El Nino–Southern Oscillation(ENSO)-related modeling studies over almost the entire Pacific basin. An ocean general circulation model is coupled to a statistical atmospheric model for interannual wind stress anomalies to represent their dominant coupling with sea surface temperatures. In addition, various relevant forcing and feedback processes exist in the region and can affect ENSO in a significant way; their effects are simply represented using historical data and are incorporated into the HCM, including stochastic forcing of atmospheric winds, and feedbacks associated with freshwater flux, ocean biology-induced heating(OBH), and tropical instability waves(TIWs). In addition to its computational efficiency, the advantages of making use of such an HCM enable these related forcing and feedback processes to be represented individually or collectively, allowing their modulating effects on ENSO to be examined in a clean and clear way. In this paper, examples are given to illustrate the ability of the HCM to depict the mean ocean state, the circulation pathways connecting the subtropics and tropics in the western Pacific, and interannual variability associated with ENSO. As satellite data are taken to parameterize processes that are not explicitly represented in the HCM, this work also demonstrates an innovative method of using remotely sensed data for climate modeling. Further model applications related with ENSO modulations by extratropical influences and by various forcings and feedbacks will be presented in Part II of this study. 相似文献
7.
In this paper we explore the impact of atmospheric nonlinearities on the optimal growth of initial condition error of El Niño and the Southern Oscillation (ENSO) prediction using singular vector (SV) analysis. This is performed by comparing and analyzing SVs of two hybrid coupled models (HCMs), one composed of an intermediate complexity dynamical ocean model coupled with a linear statistical atmospheric model, and the other one with the same ocean model coupled with a nonlinear statistical atmosphere. Tangent linear and adjoint models for both HCMs are developed. SVs are computed under the initial conditions of seasonal background and actual ENSO cycle simulated by the ocean model forced with the real wind data of 1980–1999. The optimization periods of 3, 6 and 9 months are individually considered. The results show that the first SVs in both HCMs are very similar to each other, characterized by a central east-west dipole pattern spanning over the entire tropical Pacific. The spatial patterns of the leading SV in both HCMs are not sensitive to optimization periods and initial time. However, the first singular value, indicating the optimal growth rate of prediction error, displays considerable differences between the two HCMs, indicating a significant impact of atmospheric nonlinearities on the optimal growth of ENSO prediction error. These differences are greater with increasing optimization time, suggesting that the impact of atmospheric nonlinearities on the optimal growth of prediction error becomes larger for a longer period of prediction. 相似文献
8.
Climate Dynamics - This study focuses on improving prediction of the two types of ENSO by combining multi-model ensemble (MME) with a statistical error correction method that is based on a stepwise... 相似文献
9.
A hybrid coupled model (HCM) for the tropical Pacific ocean-atmosphere system is employed for ENSO prediction. The HCM consists
of the Geophysical Fluid Dynamics Laboratory ocean general circulation model and an empirical atmospheric model. In hindcast
experiments, a correlation skill competitive to other prediction models is obtained, so we use this system to examine the
effects of several initialization schemes on ENSO prediction. Initialization with wind stress data and initialization with
wind stress reconstructed from SST using the atmospheric model give comparable skill levels. In re-estimating the atmospheric
model in order to prevent hindcast-period wind information from entering through empirical atmospheric model, we note some
sensitivity to the estimation data set, but this is considered to have limited impact for ENSO prediction purposes. Examination
of subsurface heat content anomalies in these cases and a case forced only by the difference between observed and reconstructed
winds suggests that at the current level of prediction skill, the crucial wind components for initialization are those associated
with the slow ENSO mode, rather than with atmospheric internal variability. A “piggyback” suboptimal data assimilation is
tested in which the Climate Prediction Center data assimilation product from a related ocean model is used to correct the
ocean initial thermal field. This yields improved skill, suggesting that not all ENSO prediction systems need to invest in
costly data assimilation efforts, provided the prediction and assimilation models are sufficiently close.
Received: 17 April 1998 / Accepted: 22 July 1999 相似文献
10.
A hybrid coupled model (HCM) for the tropical Pacific ocean-atmosphere system is used to test the effects of physical parametrizations
on ENSO simulation. The HCM consists of the Geophysical Fluid Dynamics Laboratory ocean general circulation model coupled
to an empirical atmospheric model based on the covariance matrix of observed SST and wind stress anomaly fields. In this two-part
work, part I describes the effects of ocean vertical mixing schemes and atmospheric spin-up time on ENSO period. Part II addresses
ENSO prediction using the HCM and examines the impact of initialization schemes. The standard version of the HCM exhibits
spatial and temporal evolution that compare well to observations, with irregular cycles that tend to exhibit 3- and 4-year
frequency-locking behavior. Effects in the vertical mixing parametrization that produce stronger mixing in the surface layer
give a longer inherent ENSO period, suggesting model treatment of vertical mixing is crucial to the ENSO problem. Although
the atmospheric spin-up time scale is short compared to ENSO time scales, it also has a significant effect in lengthening
the ENSO period. This suggests that atmospheric time scales may not be truly negligible in quantitative ENSO theory. Overall,
the form and evolution mechanism of the ENSO cycle is robust, even though the period is affected by these physical parametrizations.
Received: 17 April 1998 / Accepted: 22 July 1999 相似文献
11.
一个改进的混合型海气耦合模式：ENSO模拟 总被引：1，自引：0，他引：1
通过在中国科学院大气物理研究所热带太平洋环流模式与一个统计大气模式所建立的混合型海气耦合模式中引入次表层上卷海温非局地参数化方案, 对比分析了次表层上卷海温对耦合模式模拟结果的影响, 表明在引入次表层上卷海温非局地参数化方案前耦合模式模拟的SSTA最大变率中心位于日界线附近赤道南北狭窄范围内, 而在赤道东太平洋及南美沿岸一带变率过低, 周期呈准2年振荡。改进后, 耦合模式模拟结果的分布不论在东西方向亦或南北方向与观测更为相近, 振荡周期为4年左右, 而且还能模拟出观测中ENSO振荡的季节依赖性特征。进一步分析改进的耦合模式中海气耦合特征, 表明 “延迟振子” 理论、 “西太平洋振子” 理论、 “充电-放电振子” 理论及 “平流-反射” 理论所揭示的一些规律在该模式中都能被不同程度地描述出来, 这说明在实际的ENSO循环过程中, 可能有多种机制在同时起作用。 相似文献
12.
ENSO机理及其预测研究 总被引：19，自引：0，他引：19
资料分析研究表明ENSO(El Ni?o和La Ni?a)实际上是热带太平洋次表层海温距平的循环,而次表层海温距平的循环是赤道西太平洋异常纬向风所驱动的,赤道西太平洋的异常纬向风又主要由异常东亚冬季风所激发。因此可以将ENSO的机理视为主要是由东亚季风异常造成的赤道西太平洋异常纬向风所驱动的热带太平洋次表层海温距平的循环。同时分析还表明,热带西太平洋大气季节内振荡(ISO)的明显年际变化,作为一种外部强迫,对ENSO循环起着十分重要的作用;El Ni?o的发生同大气ISO的明显系统性东传有关。资料分析也表明,El Ni?o持续时间的长短与大气环流异常有密切关系。 用非线性最优化方法研究El Ni?o－南方涛动(ENSO)事件的可预报性问题,揭示了最容易发展成ENSO事件的初始距平模态,即条件非线性最优扰动(CNOP)型初始距平;找出能够导致显著春季可预报性障碍(SPB),且对ENSO预报结果有最大影响的一类初始误差——CNOP型初始误差,进而探讨耦合过程的非线性在SPB研究中的重要作用,提出了关于ENSO事件发生SPB的一种可能机制;用CNOP方法揭示了ENSO强度的不对称现象,探讨ENSO不对称性的年代际变化问题,提出ENSO不对称性年代际变化的一种机制;建立了关于ENSO可预报性的最大可预报时间下界、最大预报误差上界和最大允许初始误差下界的三类可预报性问题,分别从三个方面揭示ENSO事件的春季可预报性障碍现象,比较有效地量化了模式ENSO事件的可预报性。 利用中国科学院大气物理研究所地球流体力学数值模拟国家重点实验室的ENSO预测系统,研究了海洋资料同化在ENSO预测中的应用,该系统可以同时对温、盐剖面资料和卫星高度计资料进行同化。并且在模式中采用次表层上卷海温的非局地参数化方法,可有效地改进ENSO模拟水平。采用集合卡曼滤波(Ensemble Kalman Filter,EnKF)同化方法以及在集合资料同化中“平衡的”多变量模式误差扰动方法为集合预报提供更加精确和协调的初始场,ENSO预报技巧得到提高。 相似文献
13.
14.
Ensemble hindcasts of ENSO events over the past 120 years using a large number of ensembles 总被引：1，自引：0，他引：1
Based on an intermediate coupled model (ICM), a probabilistic ensemble prediction system (EPS) has been developed. The ensemble Kalman filter (EnKF) data assimilation approach is used for generating the initial ensemble conditions, and a linear, first-order Markov-Chain SST anomaly error model is embedded into the EPS to provide model-error perturbations. In this study, we perform ENSO retrospective forecasts over the 120 year period 1886–2005 using the EPS with 100 ensemble members and with initial conditi... 相似文献
15.
介绍了西北太平洋热带气旋(TC)频次的延伸期预报方法,比较了新构建的动力-统计和统计预报模型的预测技巧,并探讨了预报误差来源及改进方向。动力-统计预报模型是基于动力模式预测的热带季节内振荡(ISO)信号及ISO-TC生成的同期统计关系来进行预报;统计预报模型则是基于TC生成的前兆ISO信号建模预报。预报评估结果显示,动力-统计混合预报模型的预报技巧高于统计预报模型,原因在于影响TC次季节变化的前兆信号并不稳定,且随着预报超前时间迅速消散,无法提供有效且稳定的可预报源;相反地,TC生成与同期的ISO背景场显著相关,动力模式对ISO(预报因子)有较好的预报能力,因此动力-统计相结合的预报方法为TC延伸期预报提供了有效途径。虽然目前动力-统计预报模型的预报技巧可达5～6周,但仍有进一步改进和提高的空间。通过对不同类型TC预报技巧检验和误差分析,研究认为年际和年代际背景场对ISO调控TC活动的影响不可忽略,且热带外ISO信号(如罗斯贝波破碎和西风急流强度等)对TC频次和轨迹也有显著影响,这些因子为TC延伸期预报提供了潜在可预报源。 相似文献
16.
S. Kravtsov 《Climate Dynamics》2012,39(9-10):2377-2391
This paper assesses potential predictability of decadal variations in the El Ni?o/Southern Oscillation (ENSO) characteristics by constructing and performing simulations using an empirical nonlinear stochastic model of an ENSO index. The model employs decomposition of global sea-surface temperature (SST) anomalies into the modes that maximize the ratio of interdecadal-to-subdecadal SST variance to define low-frequency predictors called the canonical variates (CVs). When the whole available SST time series is so processed, the leading canonical variate (CV-1) is found to be well correlated with the area-averaged SST time series which exhibits a non-uniform warming trend, while the next two (CV-2 and CV-3) describe secular variability arguably associated with a combination of Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) signals. The corresponding ENSO model that uses either all three (CVs 1–3) or only AMO/PDO-related (CVs 2 and 3) predictors captures well the observed autocorrelation function, probability density function, seasonal dependence of ENSO, and, most importantly, the observed interdecadal modulation of ENSO variance. The latter modulation, and its dependence on CVs, is shown to be inconsistent with the null hypothesis of random decadal ENSO variations simulated by multivariate linear inverse models. Cross-validated hindcasts of ENSO variance suggest a potential useful skill at decadal lead times. These findings thus argue that decadal modulations of ENSO variability may be predictable subject to our ability to forecast AMO/PDO-type climate modes; the latter forecasts may need to be based on simulations of dynamical models, rather than on a purely statistical scheme as in the present paper. 相似文献
17.
A four-dimensional variational (4D-Var) data assimilation method is implemented in an improved intermediate coupled model (ICM) of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The “observation” of the SST anomaly, which is sampled from a “truth” model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction. 相似文献
18.
用混合海气耦合模式长期积分的模拟结果, 分析了模式大气的年际变化性; 用1979~1994年间的“回报”个例, 探讨了该模式对ENSO引起的全球气候异常的预报。结果表明:模式能较好地再现与ENSO相关的全球大气环流的年际变化特征; 对预报而言, 模式较高的预报技巧主要分布在热带地区, 全球热带大气具有较稳定的1年左右的可预报时效; 基本上可预报中、高纬地区由ENSO引起的冬、夏季大气环流异常 (包括气温和降水), 超前时间可达9个月至1年。 相似文献
19.
Hui Ding Richard J. Greatbatch Wonsun Park Mojib Latif Vladimir A. Semenov Xuguang Sun 《Climate Dynamics》2014,42(1-2):367-379
The variability of the East Asian summer monsoon (EASM) is studied using a partially coupled climate model (PCCM) in which the ocean component is driven by observed monthly mean wind stress anomalies added to the monthly mean wind stress climatology from a fully coupled control run. The thermodynamic coupling between the atmospheric and oceanic components is the same as in the fully coupled model and, in particular, sea surface temperature (SST) is a fully prognostic variable. The results show that the PCCM simulates the observed SST variability remarkably well in the tropical and North Pacific and Indian Oceans. Analysis of the rainfall-SST and rainfall-SST tendency correlation shows that the PCCM exhibits local air-sea coupling as in the fully coupled model and closer to what is seen in observations than is found in an atmospheric model driven by observed SST. An ensemble of experiments using the PCCM is analysed using a multivariate EOF analysis to identify the two major modes of variability of the EASM. The PCCM simulates the spatial pattern of the first two modes seen in the ERA40 reanalysis as well as part of the variability of the first principal component (correlation up to 0.5 for the model ensemble mean). Different from previous studies, the link between the first principal component and ENSO in the previous winter is found to be robust for the ensemble mean throughout the whole period of 1958–2001. Individual ensemble members nevertheless show the breakdown in the relationship before the 1980’s as seen in the observations. 相似文献
20.
In this study, we assimilated sea surface temperature (SST) data of the past 120 years into an oceanic general circulation model (OGCM) for El Niño-southern oscillation (ENSO) retrospective predictions using ensemble Kalman filter (EnKF). It was found that the ensemble covariance matrix in EnKF can act as a time-variant transfer operator to project the SST corrections onto the subsurface temperatures effectively when initial perturbations of ensemble were constructed using vertically coherent random fields. As such the increments of subsurface temperatures can be obtained via the transfer operator during assimilation cycles. The results show that the SST assimilation improves the model simulation skills significantly, not only for the SST anomalies over the whole assimilated domain, but also for the subsurface temperature anomalies of the upper 100 m over the tropical Pacific off the equator. Along the equator, the improvement of the assimilation is confined within the mixing layer because strong upwelling motions there prevent the downward transfer of SST information. The retrospective prediction skills of ENSO over the past 120 years from 1881 to 2000 were significantly improved by the SST assimilation at all leads of 1–12 months, especially for the 3–6 months leads, compared with those initialized by the control run without assimilation. The skilful predictions by the assimilation allow us to further study ENSO predictability using this coupled model. 相似文献