Climate variability in the south-eastern tropical Pacific and its relation with ENSO: a GCM study

About a third of the El-Niño/Southern Oscillation (ENSO) variability in the HadCM3 coupled general-circulation model is shown to be associated with variability in the south-east tropical Pacific (SETP) area. Sea-surface temperature (SST) anomalies along the east Pacific tend to precede ENSO anomalies. In HadCM3, SST tendencies in the SETP area are controlled mainly by surface latent heat fluxes and short-wave cloud forcing. Interannual SST anomalies in the SETP tend to propagate meridionally. In the winter season (JJA), this is consistent with a wind-evaporation-SST (WES) mode. Coupling with the strato-cumulus cloud (Sc) cover is critical in reducing the evaporative damping of the WES mode, and external forcing is provided by extratropical circulation anomalies. In spring, SETP variability and ENSO are coupled via the low-level circulation, resulting in a mutual reinforcement. Cloud-cover anomalies are not strongly controlled by local SSTs, and appear mainly dependent on atmospheric meridional advection. The apparent association between cold SSTs and Sc cover does not reflect a positive local feedback. These conclusions are not sensitive to the model’s warm SST bias, associated with reduced stratocumulus clouds and weak southerly wind stress, which depends on erroneous near-field orographic forcing of the coastal circulation. Some of our results are supported by similar evidence from observational datasets and other CMIP3 models.     

ECMWF seasonal forecast system 3 and its prediction of sea surface temperature

The latest operational version of the ECMWF seasonal forecasting system is described. It shows noticeably improved skill for sea surface temperature (SST) prediction compared with previous versions, particularly with respect to El Nino related variability. Substantial skill is shown for lead times up to 1?year, although at this range the spread in the ensemble forecast implies a loss of predictability large enough to account for most of the forecast error variance, suggesting only moderate scope for improving long range El Nino forecasts. At shorter ranges, particularly 3?C6?months, skill is still substantially below the model-estimated predictability limit. SST forecast skill is higher for more recent periods than earlier ones. Analysis shows that although various factors can affect scores in particular periods, the improvement from 1994 onwards seems to be robust, and is most plausibly due to improvements in the observing system made at that time. The improvement in forecast skill is most evident for 3-month forecasts starting in February, where predictions of NINO3.4 SST from 1994 to present have been almost without fault. It is argued that in situations where the impact of model error is small, the value of improved observational data can be seen most clearly. Significant skill is also shown in the equatorial Indian Ocean, although predictive skill in parts of the tropical Atlantic are relatively poor. SST forecast errors can be especially high in the Southern Ocean.     

Impact of horizontal resolution on seasonal integrations

 The effects of changing horizontal resolution are studied using ensembles of seasonal simulations made by a relatively recent version of the ECMWF model. The model is integrated at T63, T_L159 and T_L319 spectral resolutions. The last corresponds approximately to a 0.56° latitude-longitude grid and may be considered, by climate modelling standards, as very high resolution. Though, on average, no dramatically large differences in ensemble mean quantities are found between the three resolutions, some monotonic (systematic) differences with increasing resolution are evident. Whilst the better representation of orography with increasing resolution accounts for many differences between the resolutions considered, not all variations can be associated with changes in local orographic features. The existence of systematic changes with resolution indicates that the development of numerical models, especially physical parametrizations, should be carried out simultaneously at various resolutions. The study indicates that the highest model resolution does not always give the best results in terms of verification. In addition, reanalysis parameters that are mainly driven by model physics may not be optimal for the verification in such resolution studies. Received: 11 August 2000 / Accepted: 13 February 2001     

ENSO stability in coupled climate models and its association with mean state

In this study, using the Bjerknes stability (BJ) index analysis, we estimate the overall linear El Niño-Southern Oscillation (ENSO) stability and the relative contribution of positive feedbacks and damping processes to the stability in historical simulations of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. When compared with CMIP3 models, the ENSO amplitudes and the ENSO stability as estimated by the BJ index in the CMIP5 models are more converged around the observed, estimated from the atmosphere and ocean reanalysis data sets. The reduced diversity among models in the simulated ENSO stability can be partly attributed to the reduced spread of the thermocline feedback and Ekman feedback terms among the models. However, a systematic bias persists from CMIP3 to CMIP5. In other words, the majority of the CMIP5 models analyzed in this study still underestimate the zonal advective feedback, thermocline feedback and thermodynamic damping terms, when compared with those estimated from reanalysis. This discrepancy turns out to be related with a cold tongue bias in coupled models that causes a weaker atmospheric thermodynamical response to sea surface temperature changes and a weaker oceanic response (zonal currents and zonal thermocline slope) to wind changes.     

ECMWF全风速场集合预报结果的偏差订正与预报不一致性分析

采用卡尔曼滤波类型自适应误差订正法和滑动自适应权重法,对2012年夏季ECMWF 10 m全风速场集合预报结果进行偏差订正,对订正前后的预报结果进行评估,并通过Jumpiness指数对预报结果订正前后的预报不一致性特征进行分析。结果表明,卡尔曼滤波类型自适应误差订正法能有效降低集合预报的均方根误差,且当起报时刻为00时对中低纬度地区的订正效果更显著,当起报时刻为12时对中高纬度地区的订正效果更明显;卡尔曼滤波类型自适应误差订正法能有效改善Talagrand的U型或L型分布;由均方根误差分析结果知道,ECMWF 10 m全风速场集合预报本身存在较大的预报不一致性,经过卡尔曼滤波类型自适应误差订正后,集合预报的预报不一致性明显降低,偏差订正可有效改善集合预报的预报不一致性,且随着预报时效的延长,卡尔曼滤波误差法对预报不一致性的改善效果更加明显;从预报不一致性的发生次数特征来看,单点跳跃出现的次数最多,异号三点跳跃的次数最少;经过卡尔曼滤波类型自适应误差订正后,单点跳跃、异号两点跳跃、异号三点跳跃次数都有所下降。     

Improved reliability of ENSO hindcasts with multi-ocean analyses ensemble initialization

Currently, ensemble seasonal forecasts using a single model with multiple perturbed initial conditions generally suffer from an “overconfidence” problem, i.e., the ensemble evolves such that the spread among members is small, compared to the magnitude of the mean error. This has motivated the use of a multi-model ensemble (MME), a technique that aims at sampling the structural uncertainty in the forecasting system. Here we investigate how the structural uncertainty in the ocean initial conditions impacts the reliability in seasonal forecasts, by using a new ensemble generation method to be referred to as the multiple-ocean analysis ensemble (MAE) initialization. In the MAE method, multiple ocean analyses are used to build an ensemble of ocean initial states, thus sampling structural uncertainties in oceanic initial conditions (OIC) originating from errors in the ocean model, the forcing flux, and the measurements, especially in areas and times of insufficient observations, as well as from the dependence on data assimilation methods. The merit of MAE initialization is demonstrated by the improved El Niño and the Southern Oscillation (ENSO) forecasting reliability. In particular, compared with the atmospheric perturbation or lagged ensemble approaches, the MAE initialization more effectively enhances ensemble dispersion in ENSO forecasting. A quantitative probabilistic measure of reliability also indicates that the MAE method performs better in forecasting all three (warm, neutral and cold) categories of ENSO events. In addition to improving seasonal forecasts, the MAE strategy may be used to identify the characteristics of the current structural uncertainty and as guidance for improving the observational network and assimilation strategy. Moreover, although the MAE method is not expected to totally correct the overconfidence of seasonal forecasts, our results demonstrate that OIC uncertainty is one of the major sources of forecast overconfidence, and suggest that the MAE is an essential component of an MME system.     

ENSO variability and atmospheric response in a global coupled atmosphere-ocean GCM

The interannual variability associated with the El Ni?o/Southern Oscillation (ENSO) cycle is investigated using a relatively high-resolution (T42) coupled general circulation model (CGCM) of the atmosphere and ocean. Although the flux correction is restricted to annual means of heat and freshwater, the annual as well as the seasonal climate of the CGCM is in good agreement with that of the atmospheric model component forced with observed sea surface temperatures (SSTs). During a 100-year simulation of the present-day climate, the model is able to capture many features of the observed interannual SST variability in the tropical Pacific. This includes amplitude, lifetime and frequency of occurrence of El Ni?o events and also the phase locking of the SST anomalies to the annual cycle. Although the SST warming during the evolution of El Ni?os is too confined spatially, and the warming along the Peruvian coast is much too weak, the patterns and magnitudes of key atmospheric anomalies such as westerly wind stress and precipitation, and also their eastward migration from the western to the central equatorial Pacific is in accord with observations. There is also a qualitative agreement with the results obtained from the atmospheric model forced with observed SSTs from 1979 through 1994. The large-scale dynamic response during the mature phase of ENSO (December through February) is characterized by an eastward displacement and weakening of the Walker cell in the Pacific while the Hadley cell intensifies and moves equatorward. Similar to the observations, there is a positive correlation between tropical Pacific SST and the winter circulation in the North Pacific. The deepening of the Aleutian low during the ENSO winters is well captured by the model as well as the cooling in the central North Pacific and the warming over Canada and Alaska. However, there are indications that the anomalies of both SST and atmospheric circulation are overemphasized in the North Pacific. Finally, there is evidence of a coherent downstream effect over the North Atlantic as indicated by negative correlations between the PNA index and the NAO index, for example. The weakening of the westerlies across the North Atlantic in ENSO winters which is related to a weakening and southwestward displacement of the Icelandic low, is in broad agreement with the observations, as well as the weak tendency for colder than normal winters in Europe. Received: 31 October 1995 / Accepted: 29 May 1996     

南亚高压季节持续性异常及其与ENSO关系

南亚高压是对流层中上层重要的大气活动中心.文中选取200hPa等压面,应用1948—2006年NCEP/NCAR月平均再分析资料、NCAR的CAM3.0大气环流模式,分析了南亚高压强度的季节持续性异常特征及其与ENSO事件的关系,结果表明南亚高压强度的冬—春—夏的季节持续性异常特征,这种长达半年以上的季节持续性异常与ENSO事件存在密切关系。进一步分析发现,南亚高压强度异常程度的时间演变特征与赤道东太平洋海温表征的ENSO信号的演变特征并不一致,南亚高压强度度异常滞后ENSO信号,对ENSO信号的响应从前一年的12月开始,一直持续到当年的9月,1—5月强度异常最强,6—9月强度异常次之。1月Nino3.4指数时滞自相关表征的ENSO事件春季开始,夏秋季发展,冬季成熟,来年春季开始减弱,夏季基水消失。不同海区数值试验结果表明:在ENSO事件成熟期的冬季,南亚高压与赤道东太平洋海温关系密切,在ENSO事件衰减期的春季,与赤道东太平洋和印度洋海温关系密切,在ENSO事件衰减期的夏季,与印度洋海温关系密切。     

ENSO及其组合模态对中国东部各季节降水的影响

基于1961-2016年中国地面台站降水观测资料和多种再分析资料,分析了东部型和中部型两类厄尔尼诺事件对中国夏季水汽输送和降水的不同影响。结果表明：（1）厄尔尼诺事件对中国夏季降水的影响在发生当年和次年有明显的不同,主要影响是在其发生的次年,中国大部分地区的夏季降水明显偏多。（2）东部型厄尔尼诺事件当年夏季,西北太平洋副热带高压（副高）偏东偏弱,水汽输送条件较弱,不利于中国大范围降水的发生;中部型事件当年夏季,低纬度印度洋和西太平洋蒸发异常偏强,来自阿拉伯海、孟加拉湾和西北太平洋向华南地区的水汽输送和净水汽收支增加,有利于华南地区降水的异常增多。（3）东部型厄尔尼诺事件次年夏季,副热带太平洋蒸发异常偏强,副高西伸,由于东亚-太平洋（EAP）遥相关型的建立,副高西侧的强西南气流将来自太平洋蒸发的大量水汽持续输送至中国中东部地区。此外,在东亚-太平洋遥相关型影响下中高纬度地区建立了亚洲双阻型环流,其间的低槽冷涡与上游阻高之间的强偏北气流有利于北冰洋的水汽持续输送到西北和华北北部地区,中国大部分地区净水汽收支均增加,中国北方和南方地区的降水均产生了明显的同步性增多响应,形成了南北两条异常雨带。中部型厄尔尼诺事件次年夏季,副高较常年偏西且偏北,来自太平洋蒸发的大量水汽输送到江淮地区,使其净水汽收支增加和降水偏多。因此,厄尔尼诺事件的发生不仅对长江流域和淮河流域等南方地区的降水有重要影响,对华北、东北和西北地区的降水异常也有相当的作用。     

ENSO及其组合模态对中国东部各季节降水的影响

近期的研究发现,热带太平洋低层大气存在两种主要模态,即经向对称ENSO模态和ENSO与海表温度(SST)年循环相互作用产生的经向反对称组合模态。主要探讨了这两种不同ENSO模态对中国东部各季节降水的影响。结果表明,厄尔尼诺年秋季,中国西南、长江及华南大部分区域呈现显著正降水异常;冬季,正降水异常范围扩大,覆盖华南、华东及华北东南部地区。这两个季节的异常降水都主要受ENSO模态的影响。与ENSO模态相关的正异常海温局地强迫导致120°E以西出现反气旋性环流,其西北侧增强的西南暖湿气流使得中国东部地区降水增多。次年春季,从中国华南延伸到东北出现正的异常降水,主要是ENSO组合模态的贡献。因为次年春季热带太平洋地区ENSO模态信号只局限于赤道地区,并没有对中国东部降水有显著的影响,而ENSO与海温年循环相互作用的组合模态使得与ENSO相关的赤道大气异常可以扩展到赤道以外地区。ENSO组合模态对中国降水异常有重要影响,在今后的研究和短期预测中需引起重视。      

Role of stochastic forcing in ENSO in observations and a coupled GCM

A procedure is presented to estimate the role of atmospheric stochastic forcing (SF) in El Ni?o–Southern Oscillation (ENSO) simulated by a coupled ocean–atmosphere general circulation model (CGCM), in direct comparison to observations represented by a global reanalysis product. SF is extracted from the CGCM and reanalysis as surface wind anomalies linearly independent of the sea-surface temperature anomalies. Madden–Julian Oscillation (MJO) is isolated from SF to quantify its role in ENSO. A coupled ocean–atmosphere model of intermediate complexity is forced with SF, as well as its MJO and non-MJO components, from the reanalysis and CGCM. The role of SF is estimated by comparing the original ENSO in observations and the CGCM with that reproduced by the intermediate model. ENSO statistics in both reanalysis and CGCM are better reproduced when the intermediate model is tuned to be weakly stable than unstable. The intermediate model driven by SF from the reanalysis reproduces most characteristics of observed ENSO, such as its spectrum, seasonal phase-locking, fast decorrelation of ENSO SST during boreal spring, and its lag-correlation with SF. In contrast, not all characteristics of ENSO in the CGCM are reproduced by the intermediate model when SF from the CGCM is used. The seasonal phase-locking of ENSO in the CGCM is not reproduced at all. ENSO, therefore, appears to be driven by SF to a lesser degree in the CGCM than in observations. Characteristics of observed ENSO reproduced by the intermediate model (driven by SF) can be largely attributed to the MJO; which, for instance, is responsible for the fast decorrelation of ENSO SST during boreal spring in both reanalysis and CGCM. The non-MJO component seems to be more responsible than the MJO for erroneous features of ENSO in the CGCM.     

2013 年汛期ECMWF集合统计量产品的降水预报检验与分析

2013年汛期ECMWF集合预报在江南、四川盆地和华北地区强降水过程中的表现如下：对江南和四川盆地强降水,概率匹配、融合产品、最大值、75%和90%分位数在大雨和暴雨预报中较确定性预报有明显正技巧,融合产品和90%分位数的技巧评分最稳定;对华北地区强降水,仅90%分位数在大雨预报中有一致的正技巧;上述统计量产品的中期预报技巧评分总体要高于短期预报,对四川盆地（华北地区）暖区强降水预报技巧评分总体要高（低）于对该区域锋面强降水预报技巧评分。根据概率匹配和融合产品各自特点,综合二者原理,设计出概率匹配-融合和融合-概率匹配两种新方案。结果显示,在暴雨和大暴雨降水预报中,融合-概率匹配的评分较融合产品有一定提高。     

On the effect of ENSO precipitation anomalies in a global ocean GCM

An ocean general circulation model is used to study the influence of positive precipitation anomalies associated with El Nino and La Nina events. In this idealized model, the precipitation over the appropriate part of the equatorial Indo-Pacific region is doubled for one year. At the surface, salinity anomalies of up to –0.9 parts per thousand result from this anomalous precipitation. Perturbation surface currents ranging from 10–100% of the climatological values are induced in the tropical Indian and Pacific Oceans. A return flow is found beneath the thermocline with upwelling (downwelling) in (outside) the region of enhanced precipitation. The net effect of the precipitation anomalies is to generate a zonal overturning cell which transports fresher surface water away from the forcing region and replaces it with cooler, more saline water from below.     

2013年汛期ECMWF集合统计量产品的降水预报检验与分析

2013年汛期ECMWF集合预报在江南、四川盆地和华北地区强降水过程中的表现如下:对江南和四川盆地强降水,概率匹配、融合产品、最大值、75%和90%分位数在大雨和暴雨预报中较确定性预报有明显正技巧,融合产品和90%分位数的技巧评分最稳定;对华北地区强降水,仅90%分位数在大雨预报中有一致的正技巧;上述统计量产品的中期预报技巧评分总体要高于短期预报,对四川盆地(华北地区)暖区强降水预报技巧评分总体要高(低)于对该区域锋面强降水预报技巧评分。根据概率匹配和融合产品各自特点,综合二者原理,设计出概率匹配-融合和融合-概率匹配两种新方案。结果显示,在暴雨和大暴雨降水预报中,融合-概率匹配的评分较融合产品有一定提高。     

Contrasting Indian Ocean SST variability with and without ENSO influence: A coupled atmosphere-ocean GCM study

Summary In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO’s influence on the interannual sea-surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSO’s influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3–5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin-wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east–west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.     

A GCM Study on the Mechanism of Seasonal Abrupt Changes

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