ENSO对冬季北太平洋水汽输送及大气河的影响

利用1979-2016 年ERA-Interim 再分析资料,分析了ENSO 对冬季北太平洋地区水汽输送特征的影响,包括整层水汽含量、整层水汽输送及其散度和大气河频率.结果表明,在El Ni?o年冬季,东北太平洋地区的气旋式环流异常增强了自副热带太平洋向北美西海岸的水汽输送,导致区域性的水汽辐合与辐散异常;La Ni?...     

The seasonal footprinting mechanism in CFSv2: simulation and impact on ENSO prediction

The seasonal footprinting mechanism (SFM) is thought to be a pre-cursor to the El Nino Southern Oscillation (ENSO). Fluctuations in the North Pacific Oscillation (NPO) impact the ocean via surface heat fluxes during winter, leaving a sea-surface temperature (SST) “footprint” in the subtropics. This footprint persists through the spring, impacting the tropical Pacific atmosphere–ocean circulation throughout the following year. The simulation of the SFM in the National Centers for Environmental Prediction (NCEP)/Climate Forecast System, version 2 (CFSv2) is likely to have an impact on operational predictions of ENSO and potentially seasonal predictions in the United States associated with ENSO teleconnection patterns. The ability of the CFSv2 to simulate the SFM and the relationship between the SFM and ENSO prediction skill in the NCEP/CFSv2 are investigated. Results indicate that the CFSv2 is able to simulate the basic characteristics of the SFM and its relationship with ENSO, including extratropical sea level pressure anomalies associated with the NPO in the winter, corresponding wind and SST anomalies that impact the tropics, and the development of ENSO-related SST anomalies the following winter. Although the model is able to predict the correct sign of ENSO associated with the SFM in a composite sense, probabilistic predictions of ENSO following a positive or negative NPO event are generally less reliable than when the NPO is not active.     

The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST

The impact of realistic atmospheric initialisation on the seasonal prediction of tropical Pacific sea surface temperatures is explored with the Predictive Ocean–Atmosphere Model for Australia (POAMA) dynamical seasonal forecast system. Previous versions of POAMA used data from an Atmospheric Model Intercomparison Project (AMIP)-style simulation to initialise the atmosphere for the hindcast simulations. The initial conditions for the hindcasts did not, therefore, capture the true intra-seasonal atmospheric state. The most recent version of POAMA has a new Atmosphere and Land Initialisation scheme (ALI), which captures the observed intra-seasonal atmospheric state. We present the ALI scheme and then compare the forecast skill of two hindcast datasets, one with AMIP-type initialisation and one with realistic initial conditions from ALI, focussing on the prediction of El Niño. For eastern Pacific (Niño3) sea surface temperature anomalies (SSTAs), both experiments beat persistence and have useful SSTA prediction skill (anomaly correlations above 0.6) at all lead times (forecasts are 9 months duration). However, the experiment with realistic atmospheric initial conditions from ALI is an improvement over the AMIP-type initialisation experiment out to about 6 months lead time. The improvements in skill are related to improved initial atmospheric anomalies rather than an improved initial mean state (the forecast drift is worse in the ALI hindcast dataset). Since we are dealing with a coupled system, initial atmospheric errors (or differences between experiments) are amplified though coupled processes which can then lead to long lasting errors (or differences).     

The impact of ENSO periodicity on North Pacific SST variability

The periodicity of ENSO in nature varies. Here we examine how changes in the frequency of ENSO impacts remote teleconnections in the North Pacific. The numerical experiments presented here are designed to simulate perfectly periodic ENSO in the tropical Pacific, and to enable the air–sea interaction in other regions (i.e., the North Pacific) via a simple mixed layer ocean model. The temporal evolution and spatial structure of the North Pacific SST teleconnection patterns are relatively insensitive to the frequency of ENSO, but the amplitude of the variability is sensitive. Specifically, the 2-year period ENSO experiment (P2) shows weak event-by-event consistency in the ENSO response mature pattern. This is because there is not enough time to damp the previously forced ENSO teleconnections (i.e., 1 year earlier). The 4-year period ENSO experiment (P4) has 1 year damping time before a successive ENSO event matures, so the structure of the response pattern is stably repeated. However, the event-by-event variance of anomaly magnitude, specifically responding to El Niño, is still larger than that in the 6-year ENSO experiment (P6), which has 2-year damping time between consecutive ENSO events. In addition, we tested whether the variability due to tropical remote forcing is linearly independent of the extratropical local variability. Statistical tests indicate that tropical remote forcing can constructively or destructively interfere with local variability in the North Pacific. Lastly, there is a non-linear rectification of the ENSO events that can be detected in the climatology.     

Inter-decadal modulation of the impact of ENSO on Australia

 The success of an ENSO-based statistical rainfall prediction scheme and the influence of ENSO on Australia are shown to vary in association with a coherent, inter-decadal oscillation in surface temperature over the Pacific Ocean. When this Inter-decadal Pacific Oscillation (IPO) raises temperatures in the tropical Pacific Ocean, there is no robust relationship between year-to-year Australian climate variations and ENSO. When the IPO lowers temperature in the same region, on the other hand, year-to-year ENSO variability is closely associated with year-to-year variability in rainfall, surface temperature, river flow and the domestic wheat crop yield. The contrast in ENSO’s influence between the two phases of the IPO is quite remarkable. This highlights exciting new avenues for obtaining improved climate predictions. Received: 21 October 1998 / Accepted: 27 November 1998     

非线性误差增长理论在大气可预报性中的应用

为了能从非线性误差增长动力学的角度来研究大气的可预报性问题,在非线性动力系统的理论和方法基础上,文中引入了可预报性研究的新方法--非线性局部Lyapunov指数.非线性局部Lyapunov指数及其相关统计量能够用来定量地确定混沌系统可预报性的大小,真正地实现了对可预报性的定量化研究.首先给出了利用大气单个变量的实际观测资料获得其可预报期限估计的计算方法,因而解决了将非线性误差增长理论应用到大气实际的可预报性研究中的问题.然后,以位势高度场为例,详细讨论了逐日时间尺度上全球可预报性的时空分布,得到的主要结论为:(1)在水平方向上,全球位势高度场可预报性表现为一定的南北纬向带状分布,赤道地区和南极地区的可预报期限最长,可以达到两周左右;北极地区次之,可预报期限大约为9-12 d;北半球中高纬度地区可预报期限相对较短,可预报期限大约为6-9 d;而在南半球的中纬度地区最短,可预报期限仅为4-6 d.此外,500 hPa位势高度场可预报性分市随季节有明显变化,季节不同一些可预报期限的高值区和低值区所在的纬度和经度也会不同,总体来说,全球大部分地区的可预报性冬季都大于夏季,尤其在南极地区、热带印度洋以及北太平洋地区.(2)在垂直方向上,位势高度场可预报期限随高度升商而增加,可预报期限从对流层下层的两周以下增加到平流层下层的1个月左右,对流层和平流层天气尺度运动的可预报期限与其时间尺度是十分一致的.     

The impact of land cover change on the atmospheric circulation

 The NCAR Community Climate Model (version 3), coupled to the Biosphere Atmosphere Transfer scheme and a mixed layer ocean model is used to investigate the impact on the climate of a conservative change from natural to present land cover. Natural vegetation cover was obtained from an ecophysiologically constrained biome model. The current vegetation cover was obtained by perturbing the natural cover from forest to grass over areas where land cover has been observed to change. Simulations were performed for 17 years for each case (results from the last 15 years are presented here). We find that land cover changes, largely constrained to the tropics, SE Asia, North America and Europe, cause statistically significant changes in regional temperature and precipitation but cause no impact on the globally averaged temperature or precipitation. The perturbation in land cover in the tropics and SE Asia teleconnect to higher latitudes by changing the position and strength of key elements of the general circulation (the Hadley and Walker circulations). Many of the areas where statistically significant changes occur are remote from the location of land cover change. Historical land cover change is not typically included in transitory climate simulations, and it may be that the simulation of the patterns of temperature change over the twentieth century by climate models will be further improved by taking it into account. Received: 27 May 1999 / Accepted: July 2000     

A review of ENSO prediction studies

A hierarchy of ENSO (El Niño/Southern Oscillation) prediction schemes has been developed which includes statistical schemes and physical models. The statistical models are, in general, based on advanced statistical techniques and can be classified into models which use either low-frequency variations in the atmosphere (sea level pressure or surface wind) or upper ocean heat content as predictors. The physical models consist of coupled ocean-atmosphere models of varying degrees of complexity, ranging from simplified coupled models of the shallow water-type to coupled general circulation models. All models, statistical and physical, perform considerably better than the persistence forecast on predicting typical indices of ENSO on lead times of 6 to 12 months. The most successful prediction schemes, the fully physical coupled ocean-atmosphere models, show significant prediction abilities at lead times exceeding one year period. We therefore conclude that ENSO is predictable at least one year in advance. However, all of this applies to gross indices of ENSO such as the Southern Oscillation Index. Despite the demonstrated predictability, little is known about the predictability of specific features known to be associated with ENSO (e.g. Indian Monsoon rainfall, Southern African drought, or even off-equatorial sea surface temperature). Nor has the relative importance for prediction of different regional anomalies or different physical processes yet been established. A seasonal dependence in predictability is well established, but the processes responsible for it are not fully understood.     

关于ENSO及其统计预测方法评估

结合近年来“九五”国家重中之重项目有关ENSO业务预报系统研究工作的体会和见解 ,简要综述了近年来ENSO的预报问题 ,尤其是ENSO统计预测方法的研究成果 ,并对各种预报方法的效果进行评价。     

Extra-tropical atmospheric response to ENSO in the CMIP5 models

The seasonal mean extra-tropical atmospheric response to El Niño/Southern Oscillation (ENSO) is assessed in the historical and pre-industrial control CMIP5 simulations. This analysis considers two types of El Niño events, characterized by positive sea surface temperature (SST) anomalies in either the central equatorial Pacific (CP) or eastern equatorial Pacific (EP), as well as EP and CP La Niña events, characterized by negative SST anomalies in the same two regions. Seasonal mean geopotential height anomalies in key regions typify the magnitude and structure of the disruption of the Walker circulation cell in the tropical Pacific, upper tropospheric ENSO teleconnections and the polar stratospheric response. In the CMIP5 ensembles, the magnitude of the Walker cell disruption is correlated with the strength of the mid-latitude responses in the upper troposphere i.e., the North Pacific and South Pacific lows strengthen during El Niño events. The simulated responses to El Niño and La Niña have opposite sign. The seasonal mean extra-tropical, upper tropospheric responses to EP and CP events are indistinguishable. The ENSO responses in the MERRA reanalysis lie within the model scatter of the historical simulations. Similar responses are simulated in the pre-industrial and historical CMIP5 simulations. Overall, there is a weak correlation between the strength of the tropical response to ENSO and the strength of the polar stratospheric response. ENSO-related polar stratospheric variability is best simulated in the “high-top” subset of models with a well-resolved stratosphere.     

Simulation of state-dependent high-frequency atmospheric variability associated with ENSO

High-frequency atmospheric variability depends on the phase of El Nino/Southern Oscillation (ENSO). Recently, there is increasing evidence that state-dependent high-frequency atmospheric variability significantly modulates ENSO characteristics. Hence, in this study, we examine the model simulations of high-frequency atmospheric variability and, further, its dependency on the El Nino phase, using atmospheric and coupled GCMs (AGCM and CGCM). We use two versions of physical packages here—with and without convective momentum transport (CMT)—in both models. We found that the CMT simulation gives rise to a large climatological zonal wind difference over the Pacific. Also, both the climate models show a significantly improved performance in simulating the state-dependent noise when the CMT parameterization is implemented. We demonstrate that the better simulation of the state-dependent noise results from a better representation of anomalous, as well as climatological, zonal wind. Our further comparisons between the simulations, demonstrates that low-frequency wind is a crucial factor in determining the state-dependency of high-frequency wind variability. Therefore, it is suggested that the so-called state-dependent noise is directly induced by the low-frequency wind anomaly, which is caused by SST associated with ENSO.     

ENSO事件对东亚副热带西风急流影响的诊断分析

本文利用NCEP/NCAR月平均再分析资料,用合成分析和相关分析方法就ENSO事件对东亚副热带西风急流的影响进行诊断分析.主要结论为:El Nino年冬季200 hPa东亚副热带西风急流主要在急流出口区纬向风有正距平,急流增强东扩.而La Nina年冬季急流在急流出口区纬向风有负距平,急流减弱西移.El Nino年夏季急流增强,主要在急流区内的偏南部纬向风有正距平.La Nina年夏季急流减弱,主要在急流区内的偏南部纬向风有负距平;相关分析表明东亚副热带西风急流冬、夏季纬向风与热带中东太平洋冬、夏季海表温度有显著的相关.研究表明,ENSO年冬、夏季对流层中上层有较大的气温异常,并由此产生大的经向温度梯度的异常,这可能是ENSO事件影响东亚副热带西风急流的原因之一.     

侧向边界条件处理方式对局部地区数值天气预报误差的影响

在[1]中,已以最简单的正压模式为例,根据守恒定律构造了差分格式,并证明在一定条件下,这些格式都是可以预报的,其可预报期的长短则与格式参数、粘性系数、初始条件观测误差,计算舍入误差和大气变化剧烈程度等因素有关。在[2]中,还分析了侧向边界     

The impact of internal atmospheric variability on the North Pacific SST variability

The impact of internal atmospheric variability on North Pacific sea surface temperature (SST) variability is examined based on three coupled general circulation model simulations. The three simulations differ only in the level of atmospheric noise occuring over the ocean at the air-sea interface. The amplitude of atmospheric noise is controlled by use of the interactive ensemble technique. This technique simultaneously couples multiple realizations of a single atmospheric model to a single realization of an ocean model. The atmospheric component models all experience the same SST, but the ocean component is forced by the ensemble averaged fluxes thereby reducing the impact of internal atmospheric dynamics at the air-sea interface. The ensemble averaging is only applied at the air-sea interface so that the internal atmospheric dynamics (i.e., transients) of each atmospheric ensemble member is unaffected. This interactive ensemble technique significantly reduces the SST variance throughout the North Pacific. The reduction in SST variance is proportional to the number of ensemble members indicating that most of the variability can simply be explained as the response to atmospheric stochastic forcing. In addition, the impact of the internal atmospheric dynamics at the air-sea interface masks out much of the tropical-midlatitude SST teleconnections on interannual time scales. Once this interference is reduced (i.e., applying the interactive ensemble technique), tropical-midlatitude SST teleconnections are easily detected.     

中国热带海-气相互作用与ENSO动力学及预测研究进展

国际上针对海洋-大气系统的观测、理论和模拟方面已经开展了广泛而深入的研究,为短期气候预测水平的不断提升奠定了坚实基础,这其中中国学者做出了许多重要贡献。文中简要回顾了中国学者70年来在热带海-气相互作用与ENSO动力学及预测方面的研究进展。其中,热带海-气相互作用部分主要涉及4个方面的内容:热带太平洋气候特征与ENSO现象、热带印度洋海温主要模态及其与太平洋相互作用、热带大西洋海温主要模态及与海盆的相互作用、中高纬度海-气系统对ENSO的影响;ENSO动力学包括7个方面的内容:基本理论的相关研究、ENSO相关的诊断与模拟研究、两类ENSO相关研究、ENSO触发机制相关研究、ENSO与其他现象的相互作用、外部强迫与大气遥相关、气候变化与ENSO响应;ENSO预测主要包括2个方面的内容:动力-统计ENSO预测方法、ENSO预测系统与应用。最后,还讨论了上述相关方面亟待解决的问题。     

四个耦合模式ENSO后报试验的“春季预报障碍”

用CliPAS计划中3个气候模式和中国科学院大气物理研究所耦合模式FGOALS-g短期气候异常回报试验结果,将动力和统计方法相结合,考察了1982—2003年厄尔尼诺/拉尼娜事件发展期和衰减期海表温度春季可预报性障碍现象。结果表明,所考察的耦合模式对ENSO事件预报的误差发展存在明显的季节依赖性,最大误差增长通常发生在春季,发生显著的可预报性障碍现象。进一步分析发现厄尔尼诺事件和拉尼娜事件在发展期的季节预报障碍现象比衰减期明显,以厄尔尼诺事件发展期春季可预报性障碍现象最为显著,拉尼娜事件衰减期季节预报障碍现象不显著。研究还发现,预报误差的增长在ENSO事件冷暖位相具有显著的非对称性,发展期暖位相预报误差强于冷位相,而衰减期冷位相的预报误差比暖位相大。通过回归分析,诊断了海-气相互作用的强度,发现耦合系统在春季最不稳定,使预报误差最易在春季发展,从而导致可预报性障碍。     

The influence of atmospheric stratification on the growth of water waves

The atmospheric surface layer over sea has a density stratification which varies with moisture content and air/sea temperature difference. This influences the growth of water waves. To study the effect quantitatively, the Reynolds equations are solved numerically. For given wind speed and surface roughness, wave growth is found to be more rapid in unstably stratified conditions than in stable conditions. This is due to an increase in turbulence, primarily caused by an increase of mixing length.Under the assumption of a Charnock relation between surface roughness and friction velocity, it is found that for large inverse wave age (u _*/c>0.07), the effect of stratification on wave growth is weell described by Monin-Obukhov scaling of the friction velocity. For smaller values ofu _*/c, Monin-Obukhov scaling overpredicts.The effect on duration-limited wave growth is studied with the third-generation WAM surface wave model driven by 10 m winds. Effects of stratification on the significant wave height are found to be of the order of 10%. The results are comparable to those of a recent reanalysis of field measurements, although the measured stratification effect is somewhat stronger. Implementation of a stratification-dependent growth in wave models is recommended, as it can lead to small but significant improvements in wave forecasts when accurate air and sea temperatures are available.