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1.
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
2.
The initial errors constitute one of the main limiting factors in the ability to predict the El Nio–Southern Oscillation(ENSO) in ocean–atmosphere coupled models. The conditional nonlinear optimal perturbation(CNOP) approach was employed to study the largest initial error growth in the El Nio predictions of an intermediate coupled model(ICM). The optimal initial errors(as represented by CNOPs) in sea surface temperature anomalies(SSTAs) and sea level anomalies(SLAs) were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of El Nio, the El Nio event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier(SPB) phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly,weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events. 相似文献
3.
Qian Weihong 《Acta Meteorologica Sinica》1997,11(1):105-118
In recent years,the dynamic coupled models of ocean-atmosphere and statistical models have been used in routine operation for issuing long-lead forecasts.The dynamic coupled models consist of models with varying degrees of complexity,ranging from simplified coupled models of the shallow water to coupled general circulation models.During the period of 1980-1992,some models performed considerably better than the persistence forecast on predicting typical indices of ENSO for lead time of 6 to 12 months.It seems that ENSO is predictable at least one year in advance.However.nearly all the models have lost their skill of forecasting sea surface temperature(SST)changes in the eastern equatorial Pacific since 1992.It is a challenge not only to the dynamic models but also to the understanding of the ENSO cycle mechanism.This paper examines multiple time-space scales of the ocean-atmosphere interactions and potential prediction ability of ENSO event by using data analysis and model study. 相似文献
4.
The annual cycle and the predictability of the tropical coupled ocean-atmosphere system 总被引：5，自引：0，他引：5
P. J. Webster 《Meteorology and Atmospheric Physics》1995,56(1-2):33-55
Summary Using large-scale circulation statistics from the Pacific Ocean basin, predictability of the coupled ocean-atmosphere system on interannual time scales is found both to be limited in extent and to possess a strong annual cycle. Irrespective of when lagged correlations are commenced, correlations decrease rapidly through the boreal spring, indicating an inherent predictability limitation for large scale coupled oceanicatmospheric processes such as El Niño. Long term prediction experiments using numerical coupled-models show that the models are excellent facsimiles of the real system. They, too, encounter the predictability barrier and exhibit a substantial decrease in observation-prediction correlation across the boreal spring. Thus, a predictive system based solely on the interactive physics of the Pacific Basin appears limited to a maximum of less than one year and a minimum of only one or two months.Two hypotheses are made to explain the existence of the predictability barrier. First, it is argued that the tropical coupled system is at its frailest state during the boreal spring and that the signal-to-noise ratio is weakest. In such a system, maximum random error growth may occur as the atmosphere and the ocean become temporally detached and wander onto different climate trajectories. A series of 144 preliminary Monte Carlo experiments were conducted with a coupled ocean-atmosphere model to test the hypothesis. Irrespective of when the experiments were commenced, error growth was maximized at the same time of the year. The second hypothesis suggests that the near-equatorial circulation is perturbed at the time of its weakest state by external influences such as the monsoon and that the climate wanderings are nudged deterministically. There is observational and theoretical evidence to support the hypothesis. Observations suggest that anomalous monsoons impart basin-wide coherent alterations of the wind stress field in the Pacific Ocean. Experiments with a coupled ocean-atmosphere model show that the period of an ENSO event is altered substantially by an anomalous monsoon. Given that there appear to be precursors to anomalous monsoons, it is suggested that there may be ways to avoid the predictability barrier and thus extend prediction of the entire system.Finally, noting that the two hypotheses are not mutually exclusive, they are combined to form a unified theory. As the asymmetric monsoonal and the symmetric near-equatorial heating are in approximate quadrature, it is argued that the monsoons influence the Walker circulation during the boreal spring. However, during the boreal fall and early winter the near-equatorial heating variability dominates the winter monsoon.With 18 Figures 相似文献
5.
The equatorial Atlantic oscillation and its response to ENSO 总被引：6，自引：3，他引：3
An internal equatorial Atlantic oscillation has been identified by analyzing sea surface temperature (SST) observations. The equatorial Atlantic oscillation can be viewed as the Atlantic analogue of the El Niño/Southern Oscillation (ENSO) phenomenon in the equatorial Pacific, but it is much less vigorous. The equatorial Atlantic oscillation is strongly influenced by the Pacific ENSO with the equatorial Atlantic sea surface temperature lagging by about six months. This lag can be explained by the dynamical adjustment time of the equatorial Atlantic to low-frequency wind stress variations and the seasonally varying background state, which favours strongest growth of perturbations in summer. Results of an extended-range simulation with a coupled ocean-atmosphere GCM support this picture. 相似文献
6.
Efforts have been made to appreciate the extent to which we can predict the dominant modes of December–January–February (DJF) 2 m air temperature (TS) variability over the Asian winter monsoon region with dynamical models and a physically based statistical model. Dynamical prediction was made on the basis of multi-model ensemble (MME) of 13 coupled models with the November 1 initial condition for 21 boreal winters of 1981/1982–2001/2002. Statistical prediction was performed for 21 winters of 1981/1982–2001/2002 in a cross-validated way and for 11 winters of 1999/2000–2009/2010 in an independent verification. The first four observed modes of empirical orthogonal function analysis of DJF TS variability explain 69 % of the total variability and are statistically separated from other higher modes. We identify these as predictable modes, because they have clear physical meaning and the MME reproduces them with acceptable criteria. The MME skill basically originates from the models’ ability to capture the predictable modes. The MME shows better skill for the first mode, represented by a basin-wide warming trend, and for second mode related to the Arctic Oscillation. However, the statistical model better captures the third and fourth modes, which are strongly related to El Niño and Southern Oscillation (ENSO) variability on interannual and interdecadal timescales, respectively. Independent statistical forecasting for the recent 11-year period further reveals that the first and fourth modes are highly predictable. The second and third modes are less predictable due to lower persistence of boundary forcing and reduced potential predictability during the recent years. In particular, the notable decadal change in the monsoon–ENSO relationship makes the statistical forecast difficult. 相似文献
7.
Prediction of primary climate variability modes at the Beijing Climate Center 总被引：3，自引：2，他引：1 
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下载免费PDF全文 Hong-Li Ren Fei-Fei Jin Lianchun Song Bo Lu Ben Tian Jinqing Zuo Ying Liu Jie Wu Chongbo Zhao Yu Nie Peiqun Zhang Jin Ba Yujie Wu Jianghua Wan Yuping Yan Fang Zhou 《Acta Meteorologica Sinica》2017,31(1):204-223
Climate variability modes, usually known as primary climate phenomena, are well recognized as the most important predictability sources in subseasonal–interannual climate prediction. This paper begins by reviewing the research and development carried out, and the recent progress made, at the Beijing Climate Center (BCC) in predicting some primary climate variability modes. These include the El Niño–Southern Oscillation (ENSO), Madden–Julian Oscillation (MJO), and Arctic Oscillation (AO), on global scales, as well as the sea surface temperature (SST) modes in the Indian Ocean and North Atlantic, western Pacific subtropical high (WPSH), and the East Asian winter and summer monsoons (EAWM and EASM, respectively), on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system (CPPS) and completed a hindcast experiment for the period 1991–2014. The performance of the CPPS in predicting such climate variability modes is systematically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole (IOD) and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improvements in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC’s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper. 相似文献
8.
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
9.
M. Latif K. Sperber J. Arblaster P. Braconnot D. Chen A. Colman U. Cubasch C. Cooper P. Delecluse D. Dewitt L. Fairhead G. Flato T. Hogan M. Ji M. Kimoto A. Kitoh T. Knutson H. Le Treut T. Li S. Manabe O. Marti C. Mechoso G. Meehl S. Power E. Roeckner J. Sirven L. Terray A. Vintzileos R. Voß B. Wang W. Washington I. Yoshikawa J. Yu S. Zebiak 《Climate Dynamics》2001,18(3-4):255-276
An ensemble of twenty four coupled ocean-atmosphere models has been compared with respect to their performance in the tropical Pacific. The coupled models span a large portion of the parameter space and differ in many respects. The intercomparison includes TOGA (Tropical Ocean Global Atmosphere)-type models consisting of high-resolution tropical ocean models and coarse-resolution global atmosphere models, coarse-resolution global coupled models, and a few global coupled models with high resolution in the equatorial region in their ocean components. The performance of the annual mean state, the seasonal cycle and the interannual variability are investigated. The primary quantity analysed is sea surface temperature (SST). Additionally, the evolution of interannual heat content variations in the tropical Pacific and the relationship between the interannual SST variations in the equatorial Pacific to fluctuations in the strength of the Indian summer monsoon are investigated. The results can be summarised as follows: almost all models (even those employing flux corrections) still have problems in simulating the SST climatology, although some improvements are found relative to earlier intercomparison studies. Only a few of the coupled models simulate the El Niño/Southern Oscillation (ENSO) in terms of gross equatorial SST anomalies realistically. In particular, many models overestimate the variability in the western equatorial Pacific and underestimate the SST variability in the east. The evolution of interannual heat content variations is similar to that observed in almost all models. Finally, the majority of the models show a strong connection between ENSO and the strength of the Indian summer monsoon. 相似文献
10.
In this paper we seek to identify inter-annual sea surface temperature anomalies (SSTA) patterns outside the tropical Pacific that may influence El Niño/Southern Oscillation (ENSO) through atmospheric teleconnections. We assume that a linear ENSO hindcast based on tropical Pacific warm water volume and Niño3.4 SSTA indices captures tropical Pacific intrinsic predictability inherent to recharge oscillator dynamics. This simple hindcast model displays statistically significant skill at the 95 % confidence level at leads of up to seven seasons ahead of the ENSO peak. Our results reveal that ENSO-independent equatorial wind stress anomalies only significantly improve the skill of that linear hindcast at the 95 % level in boreal spring and summer before the ENSO peak and in boreal fall, five seasons ahead of the ENSO peak. At those seasons, the robust large-scale SST patterns that provide a statistically significant enhancement of ENSO predictability are related to the Atlantic meridional mode and south Pacific subtropical dipole mode in spring, the Indian Ocean Dipole and the south Atlantic subtropical dipole mode in fall. While the first two regions display significant simultaneous correlations with western equatorial Pacific wind stress in three reanalyses (ERA-I, NCEP and NCEP2), the Indian Ocean Dipole and south Atlantic subtropical dipole mode correlation with Pacific winds is less robust amongst re-analyses. We discuss our results in view of other studies that suggest a remote influence of various regions on ENSO. Although modest, the sensitivity of our results to the dataset and to details of the analysis method illustrates that finding regions that influence ENSO from the statistical analysis of observations is a difficult task. 相似文献
11.
Incorporating a semi-stochastic model of ocean-modulated westerly wind bursts into an ENSO prediction model 总被引：1，自引：0，他引：1
Prediction models of the El Niño-Southern Oscillation (ENSO) phenomenon often represent westerly wind bursts (WWBs), a significant player in ENSO dynamics, as stochastic forcing. A recent paper developed an observationally motivated semi-stochastic statistical model that quantifies the dependence of WWBs on large-scale sea-surface temperature. This WWB model is added here to a hybrid coupled model, thus activating a two-way SST-WWB feedback. The WWB model represents both the deterministic and stochastic elements of WWBs and thus is especially appropriate for ensemble ENSO prediction experiments. An ensemble of retrospective forecasts is performed for the years 1979–2002. Overall statistical measures of predictability are neither degraded nor improved relative to the hybrid, coupled general circulation model, perhaps because of the limitations of the hybrid coupled model and the initialization procedure used. While the present work is meant as a proof-of-concept, it is found that the addition of the WWB model does improve the prediction of the onset and the development of the large 1997 warm event, pointing to the potential for ENSO prediction skill improvement using this approach. 相似文献
12.
A comparison of rainfall variability in the semi-arid Brazilian Nordeste in observations and in two sets of model simulations leads to the conclusion that the evolving interaction between Tropical Atlantic Variability (TAV) and the El Niño-Southern Oscillation (ENSO) phenomenon can explain two puzzling features of ENSOs impact on the Nordeste: (1) the event-to-event unpredictability of ENSOs impact; (2) the greater impact of cold rather than warm ENSO events during the past 50 years. The explanation is in the preconditioning role of Tropical Atlantic Variability. When, in seasons prior to the mature phase of ENSO, the tropical Atlantic happens to be evolving consistently with the development expected of the ENSO teleconnection, ENSO and TAV add up to force large anomalies in Nordeste rainfall. When it happens to be evolving in opposition to the canonical development of ENSO, then the net outcome is less obvious, but also less anomalous. The more frequent occurrence of tropical Atlantic conditions consistent with those that develop during a cold ENSO event, i.e. of a negative meridional sea surface temperature gradient, explains the weaker warm ENSO and stronger cold ENSO anomalies in Nordeste rainfall of the latter part of the twentieth century. Close monitoring of the evolution of the tropical Atlantic in seasons prior to the mature phase of ENSO should lead to an enhanced forecast potential. 相似文献
13.
Summary Two lines of research into climate change and El Niño/Southern Oscillation (ENSO) converge on the conclusion that changes in ENSO statistics occur as a response to global climate (temperature) fluctuations. One approach focuses on the statistics of temperature fluctuations interpreted within the framework of random walks. The second is based on the discovery of correlation between the recurrence frequency of El Niño and temperature change, while developing physical arguments to explain several phenomena associated with changes in El Niño frequency. Consideration of both perspectives leads to greater confidence in, and guidance for, the physical interpretation of the relationship between ENSO and global climate change. Topics considered include global dynamics of ENSO, ENSO triggers, and climate prediction and predictability.Revised November 14, 2002; accepted November 28, 2002
Published online: June 12, 2003 相似文献
14.
15.
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). 相似文献
16.
季风与ENSO的选择性相互作用:年循环和春季预报障碍的影响 总被引：1，自引：1，他引：0
本文主要基于对Webster and Yang（1992）一文的回顾,讨论了年循环在季风和ENSO相互作用中的作用、春季预报障碍（SPB）、Webster-Yang指数（WYI）、以及亚洲夏季风的前期讯号等内容。亚洲季风和ENSO作为全球天气和气候变率的主要来源,它们之间的相互作用存在明显的年变化和季节“锁相”特征:在北半球秋冬季,亚洲季风对流活动最弱,此时ENSO的信号最强;但是到了北半球春季,亚洲季风对流快速爆发,而此时的ENSO信号却迅速衰减。亚洲季风和ENSO位相的错位变化使得热带海—气系统的不稳定性在北半球春季达到最大,此时任意一个微小的扰动都容易快速增长,最终导致基于ENSO的预报技巧减小。亚洲夏季风环流本质上可以看成是大气对副热带地区潜热加热的低频罗斯贝波响应,它具有很强的垂直风切变,这是WYI定义的物理基础。WYI数值越大,代表垂直东风切变越大,即亚洲季风环流增强,反之亦然。利用WYI与前期大气环流场、欧亚雪盖、土壤湿度等物理量进行回归分析,结果表明:当亚洲夏季风增强时,前期冬季和春季,在北印度洋和亚洲副热带地区上空出现东风异常,同时在更高纬度地区伴随出现西风的异常;此外,副热带地区如印度次大陆、中南半岛和东亚的土壤湿度增大;中纬度地区尤其是青藏高原中西部的积雪密度明显减小。这些前期讯号的发现有助于我们构建动力统计模型,进而提高对亚洲夏季风的季节预报水平。 相似文献
17.
Based on experiments using a coupled general circulation model which resolves tropical ocean–atmosphere coupled phenomena such as El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole, forcing mechanisms of the Indian Ocean subtropical dipole (IOSD) are investigated. In the control experiment, as in the observation, several types of the IOSD are generated by the variations in the Mascarene High during austral summer and characterized by a dipole pattern of sea surface temperature (SST) anomalies in the northeastern and southwestern parts of the southern Indian Ocean. In another experiment, where the SST outside the southern Indian Ocean is nudged toward the monthly climatology of the simulated SST, one type of the IOSD occurs, but it is less frequent and associated with the zonal wavenumber four pattern of equivalently barotropic geopotential height anomalies in high latitudes, suggesting an interesting link with the Antarctic Circumpolar Wave. This indicates that, even without the atmospheric teleconnection from tropical coupled climate modes, the IOSD may develop in association with the atmospheric variability in high latitudes of the Southern Hemisphere. In the other experiment, where only the southern Indian Ocean and the tropical Pacific are freely interactive with the atmosphere, two types of both positive and negative IOSD occur. Since the occurrence frequency of the IOSD significantly increases as compared to the second experiment, this result confirms that the atmospheric teleconnection from ocean-atmosphere coupled modes in the tropical Pacific such as ENSO may also induce the variations in the Mascarene High that generate the IOSD. The present research, even within the realm of model studies, shows clearly that the predictability of the IOSD in mid-latitudes is related to both low and high-latitudes climate variations. 相似文献
18.
How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability? 总被引：1，自引：0，他引：1
Bin Wang June-Yi Lee I.-S. Kang J. Shukla J.-S. Kug A. Kumar J. Schemm J.-J. Luo T. Yamagata C.-K. Park 《Climate Dynamics》2008,30(6):605-619
Accurate prediction of the Asian-Australian monsoon (A-AM) seasonal variation is one of the most important and challenging tasks in climate prediction. In order to understand the causes of the low accuracy in the current prediction of the A-AM precipitation, this study strives to determine to what extent the ten state-of-the-art coupled atmosphere-ocean-land climate models and their multi-model ensemble (MME) can capture the two observed major modes of A-AM rainfall variability–which account for 43% of the total interannual variances during the retrospective prediction period of 1981–2001. The first mode is associated with the turnabout of warming to cooling in the El Niño-Southern Oscillation (ENSO), whereas the second mode leads the warming/cooling by about 1 year, signaling precursory conditions for ENSO. The first mode has a strong biennial tendency and reflects the Tropical Biennial Oscillation (Meehl in J Clim 6:31–41, 1993). We show that the MME 1-month lead prediction of the seasonal precipitation anomalies captures the first two leading modes of variability with high fidelity in terms of seasonally evolving spatial patterns and year-to-year temporal variations, as well as their relationships with ENSO. The MME shows a potential to capture the precursors of ENSO in the second mode about five seasons prior to the maturation of a strong El Niño. However, the MME underestimates the total variances of the two modes and the biennial tendency of the first mode. The models have difficulties in capturing precipitation over the maritime continent and the Walker-type teleconnection in the decaying phase of ENSO, which may contribute in part to a monsoon “spring prediction barrier” (SPB). The NCEP/CFS model hindcast results show that, as the lead time increases, the fractional variance of the first mode increases, suggesting that the long-lead predictability of A-AM rainfall comes primarily from ENSO predictability. In the CFS model, the correlation skill for the first principal component remains about 0.9 up to 6 months before it drops rapidly, but for the spatial pattern it exhibits a drop across the boreal spring. This study uncovered two surprising findings. First, the coupled models’ MME predictions capture the first two leading modes of precipitation variability better than those captured by the ERA-40 and NCEP-2 reanalysis datasets, suggesting that treating the atmosphere as a slave may be inherently unable to simulate summer monsoon rainfall variations in the heavily precipitating regions (Wang et al. in J Clim 17:803–818, 2004). It is recommended that future reanalysis should be carried out with coupled atmosphere and ocean models. Second, While the MME in general better than any individual models, the CFS ensemble hindcast outperforms the MME in terms of the biennial tendency and the amplitude of the anomalies, suggesting that the improved skill of MME prediction is at the expense of overestimating the fractional variance of the leading mode. Other outstanding issues are also discussed. 相似文献
19.
The North Atlantic Oscillation (NAO) is a major winter climate mode, describing one-third of the inter-annual variability of the upper-level flow in the Atlantic European mid-latitudes. It provides a statistically well-defined pattern to study the predictability of the European winter climate. In this paper, the predictability of the NAO and the associated surface temperature variations are considered using a dynamical prediction approach. Two state-of-the-art coupled atmosphere–ocean ensemble forecast systems are used, namely the seasonal forecast system 2 from the European Centre for Medium Range Weather Forecast (ECMWF) and the multi-model system developed within the joint European project DEMETER (Development of a European Multi-Model Ensemble Prediction System for Seasonal to Inter-annual Prediction). The predictability is defined in probabilistic space using the debiased ranked probability skill score with adapted discretization (RPSSD). The potential predictability of the NAO and its impact are also investigated in a perfect model approach, where each ensemble member is used once as observation. This approach assumes that the climate system is fully represented by the model physics. Using the perfect model approach for the period 1959–2001, it is shown that the mean winter NAO index is potentially predictable with a lead time of 1 month (i.e. from 1st of November). The prediction benefit is rather small (6% skill relative to a reference climatology) but statistically significant. A similar conclusion holds for the near surface temperature variability related to the NAO. Again, the potential benefit is small (5%) but statistically significant. Using the forecast approach, the NAO skill is not statistically significant for the period 1959–2001, while for the period 1987–2001 the skill is surprisingly large (15% relative to a climate prediction). Furthermore, a weak relation is found between the strength of the NAO amplitude and the skill of the NAO. This contrasts with El Niño/Southern Oscillation (ENSO) variability, where the forecast skill is strongly amplitude dependent. In general, robust results are only achieved if the sensitivity with respect to the sample size (both the ensemble size and length of the period) is correctly taken into account.
This revised version was published online in May 2005. Some black and white figures were replaced by coloured figures. 相似文献
This revised version was published online in May 2005. Some black and white figures were replaced by coloured figures. 相似文献
20.
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