共查询到20条相似文献，搜索用时 46 毫秒
1.
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
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.
Improved ENSO Forecasts by Assimilating Sea Surface Temperature Observations into an Intermediate Coupled Model 总被引：2，自引：0，他引：2
A simple method for initializing intermediate coupled models (ICMs) using only sea surface temperature (SST) anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984–2003 and the period 1997–2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system. 相似文献
4.
A new hybrid coupled model(HCM) is presented in this study, which consists of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model. The ocean component is the intermediate ocean model(IOM)of the intermediate coupled model(ICM) used at the Institute of Oceanology, Chinese Academy of Sciences(IOCAS). The atmospheric component is ECHAM5, the fifth version of the Max Planck Institute for Meteorology atmospheric general circulation model. The HCM integrates its atmospheric and oceanic components by using an anomaly coupling strategy. A100-year simulation has been made with the HCM and its simulation skills are evaluated, including the interannual variability of SST over the tropical Pacific and the ENSO-related responses of the global atmosphere. The model shows irregular occurrence of ENSO events with a spectral range between two and five years. The amplitude and lifetime of ENSO events and the annual phase-locking of SST anomalies are also reproduced realistically. Despite the slightly stronger variance of SST anomalies over the central Pacific than observed in the HCM, the patterns of atmospheric anomalies related to ENSO,such as sea level pressure, temperature and precipitation, are in broad agreement with observations. Therefore, this model can not only simulate the ENSO variability, but also reproduce the global atmospheric variability associated with ENSO, thereby providing a useful modeling tool for ENSO studies. Further model applications of ENSO modulations by ocean–atmosphere processes, and of ENSO-related climate prediction, are also discussed. 相似文献
5.
Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4 D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously,and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4 D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation,which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4 D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper. 相似文献
6.
Yoo-Geun Ham Jong-Seong Kug Daehyun Kim Young-Ho Kim Dong-Hoon Kim 《Climate Dynamics》2013,40(5-6):1551-1568
In this study, the phase-locking of El Nino Southern Oscillation (ENSO) in a coupled model with different physical parameter values is investigated. It is found that there is a dramatic change in ENSO phase-locking in response to a slight change in the Tokioka parameter, which is a minimum entrainment rate threshold in the cumulus parameterization. With a smaller Tokioka parameter, the model simulates ENSO peak in the boreal summer season rather than in the winter season as observed. It is revealed that the differences in climatological zonal sea surface temperature (SST) gradient and its associated mean state changes are crucial to determine the phase-locking of ENSO. In the simulations with smaller Tokioka parameter values, climatological zonal SST gradient during the boreal summer is excessively large, because the zonally-asymmetric SST change (i.e., SST increase is relatively smaller over the eastern Pacific) is maximum during the boreal summer when the eastern Pacific SST is the coolest of the year. The enhanced climatological zonal SST gradient in boreal summer reduces the convection over the eastern Pacific, which leads to a weakening of air–sea coupling strength. The minimum coupling strength during summer prevents SST anomalies from further development in the following season, which favors SST maximum during summer. In addition, enhanced zonal SST gradient and resultant thermocline shoaling over the eastern Pacific lead to excessive zonal advective feedback and thermocline feedback. Atmospheric damping is also weakened during boreal summer season. These changes due to feedback processes allow an excessive development of SST anomalies during the summer time, and lead to a summer peak of ENSO. The importance of basic state change for the ENSO phase-locking is also validated in a multi-model framework using the Coupled Model Intercomparison Project phase-3 archive. It is found that several of the climate models have the same problem in producing a summer peak of ENSO. Consistent with the simulations with different physical parameter values, these models have minimum air–sea coupling strength during the boreal summer season. Also, they have stronger climatological zonal SST gradient and shallower climatological thermocline depth over the eastern Pacific during the boreal summer season. 相似文献
7.
The predictability of El Ni?o?Southern Oscillation (ENSO) has been an important area of study for years. Searching for the optimal precursor (OPR) of ENSO occurrence is an effective way to understand its predictability. The CNOP (conditional nonlinear optimal perturbation), one of the most effective ways to depict the predictability of ENSO, is adopted to study the optimal sea surface temperature (SST) precursors (SST-OPRs) of ENSO in the IOCAS ICM (intermediate coupled model developed at the Institute of Oceanology, Chinese Academy of Sciences). To seek the SST-OPRs of ENSO in the ICM, non-ENSO events simulated by the ICM are chosen as the basic state. Then, the gradient-definition-based method (GD method) is employed to solve the CNOP for different initial months of the basic years to obtain the SST-OPRs. The experimental results show that the obtained SST-OPRs present a positive anomaly signal in the western-central equatorial Pacific, and obvious differences exist in the patterns between the different seasonal SST-OPRs along the equatorial western-central Pacific, showing seasonal dependence to some extent. Furthermore, the non-El Ni?o events can eventually evolve into El Ni?o events when the SST-OPRs are superimposed on the corresponding seasons; the peaks of the Ni?o3.4 index occur at the ends of the years, which is consistent with the evolution of the real El Ni?o. These results show that the GD method is an effective way to obtain SST-OPRs for ENSO events in the ICM. Moreover, the OPRs for ENSO depicted using the GD method provide useful information for finding the early signal of ENSO in the ICM. 相似文献
8.
To extend the linear stochastically forced paradigm of tropical sea surface temperature (SST) variability to the subsurface ocean, a linear inverse model (LIM) is constructed from the simultaneous and 3-month lag covariances of observed 3-month running mean anomalies of SST, thermocline depth, and zonal wind stress. This LIM is then used to identify the empirically-determined linear dynamics with physical processes to gauge their relative importance to ENSO evolution. Optimal growth of SST anomalies over several months is triggered by both an initial SST anomaly and a central equatorial Pacific thermocline anomaly that propagates slowly eastward while leading the amplifying SST anomaly. The initial SST and thermocline anomalies each produce roughly half the SST amplification. If interactions between the sea surface and the thermocline are removed in the linear dynamical operator, the SST anomaly undergoes less optimal growth but is also more persistent, and its location shifts from the eastern to central Pacific. Optimal growth is also found to be essentially the result of two stable eigenmodes with similar structure but differing 2- and 4-year periods evolving from initial destructive to constructive interference. Variations among ENSO events could then be a consequence not of changing stability characteristics but of random excitation of these two eigenmodes, which represent different balances between surface and subsurface coupled dynamics. As found in previous studies, the impact of the additional variables on LIM SST forecasts is relatively small for short time scales. Over time intervals greater than about 9?months, however, the additional variables both significantly enhance forecast skill and predict lag covariances and associated power spectra whose closer agreement with observations enhances the validation of the linear model. Moreover, a secondary type of optimal growth exists that is not present in a LIM constructed from SST alone, in which initial SST anomalies in the southwest tropical Pacific and Indian ocean play a larger role than on shorter time scales, apparently driving sustained off-equatorial wind stress anomalies in the eastern Pacific that result in a more persistent equatorial thermocline anomaly and a more protracted (and predictable) ENSO event. 相似文献
9.
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
10.
变分同化方法反演海气耦合模型参数的研究 总被引：1，自引：2，他引：1
采用变分资料同化技术,结合最优控制思想,对一个海气耦合模型的模式参数和强迫项进行了反演。结果表明,采用该方法对模式进行优化,既可以补偿模式参数不准确性给预报带来的误差,又可以对模式参数本身进行修正和估计,为将来在实际应用中改善更复杂的预报模式、提高预报准确率提供了一个可借鉴的思路。 相似文献
11.
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
12.
Regional-Eta-Coordinate-Model(REM)中尺度模式对中国区域性降水显示出公认的较高预报能力,建立其四维变分资料同化系统是完善该模式,进一步提高其预报效果的重要工作。本研究编写了REM模式的切线性模式和伴随模式,介绍了建立REM模式伴随系统的过程,并利用实际天气个例资料,分别对REM模式的切线性模式、伴随模式及定义的目标函数梯度进行了正确性检验,检验结果表明对REM模式的切线性模式及伴随模式编写是成功的。利用REM模式的伴随系统,对1998年06月08日00时到09日00时和2000年08月01日00时到02日00时两个实际天气个例进行了四维变分资料同化试验。从数值试验的结果分析可以看到,进行四维变分资料同化后,两个天气个例在预报结束时刻其预报结果对风场和湿度场的预报都有明显改善,对温度场和高度场的预报也有所改善。对于累积降水的预报,两个个例利用四维变分资料同化后得到的初始场进行的预报结果则有较大不同,在个例1中,变分同化后对降水中心的位置和降水强度的预报都有明显改善,预报结果更接近于观测场;个例2中,变分同化后对降水中心位置和强度的预报则没有改善,产生这种现象的原因可能是由于定义的目标函数中没有加进背景场项,也可能是由于采用的观测资料时次比较少,还需要进一步进行研究和试验。 相似文献
13.
Vertical stratification changes at low frequency over the last decades are the largest in the western-central Pacific and have the potential to modify the balance between ENSO feedback processes. Here we show evidence of an increase in thermocline feedback in the western-central equatorial Pacific over the last 50 years, and in particular after the climate shift of 1976. It is demonstrated that the thermocline feedback becomes more effective due to the increased stratification in the vicinity of the mean thermocline. This leads to an increase in vertical advection variability twice as large as the increase resulting from the stronger ENSO amplitude (positive asymmetry) in the eastern Pacific that connects to the thermocline in the western-central Pacific through the basin-scale ‘tilt’ mode. Although the zonal advective feedback is dominant over the western-central equatorial Pacific, the more effective thermocline feedback allows for counteracting its warming (cooling) effect during warm (cold) events, leading to the reduced covariability between SST and thermocline depth anomalies in the NINO4 (160°E–150°W; 5°S–5°N) region after the 1976 climate shift. This counter-intuitive relationship between thermocline feedback strength as derived from the linear relationship between SST and thermocline fluctuations and stratification changes is also investigated in a long-term general circulation coupled model simulation. It is suggested that an increase in ENSO amplitude may lead to the decoupling between eastern and central equatorial Pacific sea surface temperature anomalies through its effect on stratification and thermocline feedback in the central-western Pacific. 相似文献
14.
Two important atmospheric features affecting El Niño-Southern Oscillation (ENSO) are atmospheric noise and a nonlinear atmospheric response to SST. In this article, we investigate the roles of these atmospheric features in ENSO in observations and coupled Global Climate Models (GCMs). We first quantify the most important linear couplings between the ocean and atmosphere. We then characterize atmospheric noise by its patterns of standard deviation and skewness and by spatial and temporal correlations. GCMs tend to simulate lower noise amplitudes than observations. Additionally, we investigate the strength of a nonlinear response of wind stress to SST. Some GCMs are able to simulate a nonlinear response of wind stress to SST, although weaker than in observations. These models simulate the most realistic SST skewness. The influence of the couplings and noise terms on ENSO are studied with an Intermediate Climate Model (ICM). With couplings and noise terms fitted to either observations or GCM output, the simulated climates of the ICM versions show differences in ENSO characteristics similar to differences in ENSO characteristics in the original data. In these model versions the skewness of noise is of minor influence on ENSO than the standard deviation of noise. Both the nonlinear response of wind stress to SST anomalies and the relation of noise to the background SST contribute to SST skewness. The ICM is not yet fully evolved, the results rather show that this is a promising route. Overall, atmospheric noise with realistic standard deviation pattern and spatial correlations seems to be important for simulating an irregular ENSO. Both a nonlinear atmospheric response to SST and the dependence of noise on the background SST influence the El Niño/La Niña asymmetry. 相似文献
15.
Impact of improved assimilation of temperature and salinity for coupled model seasonal forecasts 总被引：1，自引：0，他引：1
We assess the impact of improved ocean initial conditions for predicting El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) using the Bureau of Meteorology’s Predictive Ocean Atmosphere Model for Australia (POAMA) coupled seasonal prediction model for the period 1982–2006. The new ocean initial conditions are provided by an ensemble-based analysis system that assimilates subsurface temperatures and salinity and which is a clear improvement over the previous optimal interpolation system which used static error covariances and was univariate (temperature only). Hindcasts using the new ocean initial conditions have better skill at predicting sea surface temperature (SST) variations associated with ENSO than do the hindcasts initialized with the old ocean analyses. The improvement derives from better prediction of subsurface temperatures and the largest improvements come during ENSO–IOD neutral years. We show that improved prediction of the Niño3.4 SST index derives from improved initial depiction of the thermocline and halocline in the equatorial Pacific but as lead time increases the improved depiction of the initial salinity field in the western Pacific become more important. Improved ocean initial conditions do not translate into improved skill for predicting the IOD but we do see an improvement in the prediction of subsurface temperatures in the Indian Ocean (IO). This result reflects that the coupling between subsurface and surface temperature variations is weaker in the IO than in the Pacific, but coupled model errors may also be limiting predictive skill in the IO. 相似文献
16.
In this study, the El Nino-Southern Oscillation (ENSO) phase-locking to the boreal winter in CMIP3 and CMIP5 models is examined. It is found that the models that are poor at simulating the winter ENSO peak tend to simulate colder seasonal-mean sea-surface temperature (SST) during the boreal summer and associated shallower thermocline depth over the eastern Pacific. These models tend to amplify zonal advection and thermocline depth feedback during boreal summer. In addition, the colder eastern Pacific SST in the model can reduce the summertime mean local convective activity, which tends to weaken the atmospheric response to the ENSO SST forcing. It is also revealed that these models have more serious climatological biases over the tropical Pacific, implying that a realistic simulation of the climatological fields may help to simulate winter ENSO peak better. The models that are poor at simulating ENSO peak in winter also show excessive anomalous SST warming over the western Pacific during boreal winter of the El Nino events, which leads to strong local convective anomalies. This prevents the southward shift of El Nino-related westerly during boreal winter season. Therefore, equatorial westerly is prevailed over the western Pacific to further development of ENSO-related SST during boreal winter. This bias in the SST anomaly is partly due to the climatological dry biases over the central Pacific, which confines ENSO-related precipitation and westerly responses over the western Pacific. 相似文献
17.
The bio-physical feedback process between the marine ecosystem and the tropical climate system is investigated using both an ocean circulation model and a fully-coupled ocean–atmosphere circulation model, which interact with a biogeochemical model. We found that the presence of chlorophyll can have significant impact on the characteristics of the El Niño-Southern Oscillation (ENSO), including its amplitude and asymmetry, as well as on the mean state. That is, chlorophyll generally increases mean sea surface temperature (SST) due to the direct biological heating. However, SST in the eastern equatorial Pacific decreases due to the stronger indirect dynamical response to the biological effects outweighing the direct thermal response. It is demonstrated that this biologically-induced SST cooling is intensified and conveyed to other tropical-ocean basins when atmosphere–ocean coupling is taken into account. It is also found that the presence of chlorophyll affects the magnitude of ENSO by two different mechanisms; one is an amplifying effect by the mean chlorophyll, which is associated with shoaling of the mean thermocline depth, and the other is a damping effect derived from the interactively-varying chlorophyll coupled with the physical model. The atmosphere–ocean coupling reduces the biologically-induced ENSO amplifying effect through the weakening of atmospheric feedback. Lastly, there is also a biological impact on ENSO which enhances the positive skewness. This skewness change is presumably caused by the phase dependency of thermocline feedback which affects the ENSO magnitude. 相似文献
18.
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
19.
20.
The impact of diabatic processes on 4-dimensional variational data assimilation (4D-Var) was studied using the 1995 version of NCEP's global spectral model with and without full physics.The adjoint was coded manually.A cost function measuring spectral errors of 6-hour forecasts to "observation" (the NCEP reanalysis data) was minimized using the L-BFGS (the limited memory quasi-Newton algorithm developed by Broyden,Fletcher,Goldfard and Shanno) for optimizing parameters and initial conditions.Minimization of the cost function constrained by an adiabatic version of the NCEP global model converged to a minimum with a significant amount of decrease in the value of the cost function.Minimization of the cost function using the diabatic model, however,failed after a few iterations due to discontinuities introduced by physical parameterizations.Examination of the convergence of the cost function in different spectral domains reveals that the large-scale flow is adjusted during the first 10 iterations,in which discontinuous diabatic parameterizations play very little role.The adjustment produced by the minimization gradually moves to relatively smaller scales between 10-20th iterations.During this transition period,discontinuities in the cost function produced by "on-off" switches in the physical parameterizations caused the cost function to stay in a shallow local minimum instead of continuously decreasing toward a deeper minimum. Next,a mixed 4D-Var scheme is tested in which large-scale flows are first adiabatically adjusted to a sufficient level,followed by a diabatic adjustment introduced after 10 to 20 iterations. The mixed 4D-Var produced a closer fit of analysis to observations,with 38% and 41% more decrease in the values of the cost function and the norm of gradient,respectively,than the standard diabatic 4D-Var,while the CPU time is reduced by 21%.The resulting optimal initial conditions improve the short-range forecast skills of 48-hour statistics.The detrimental effect of parameterization discontinuities on minimization was also reduced. 相似文献