Seasonal predictability of ENSO teleconnections: the role of the remote ocean response

In this modelling study, the teleconnections of ENSO are studied using an atmospheric general circulation model (AGCM), HadAM3. The influence of sea surface temperature anomalies (SSTAs) remote from the tropical Pacific but teleconnected with ENSO is investigated. Composite cycles of El Niño and La Niña SSTs are created and imposed on HadAM3. These SSTs are imposed in different areas, with climatological SSTs elsewhere, in order to find the influences of SSTs in different regions. It is found that most of the reproducible response to ENSO is forced directly from the tropical Pacific before the peak of the event. However, during the peak and decay of ENSO, remote SSTs become increasingly influential throughout the tropics (at the 98% significance level). This could lead to extended ENSO-related predictability due to the memory of the remote oceans. The Indian Ocean and Maritime Continent SSTs are found to be particularly influential. Indian Ocean SSTAs dampen the teleconnections from the tropical Pacific and force the atmosphere above the tropical Atlantic. More generally, when a tropical SSTA is imposed, atmospheric anomalies are forced locally with anomalies of the opposite sign to the west. Some of the reproducible response to ENSO in the tropical Atlantic is forced, not directly from the tropical Pacific but from the Indian ocean, which in turn is forced by the tropical Pacific. Subsequently, delayed SSTAs in the tropical Atlantic damp the local response and force the atmosphere above the tropical Pacific in the opposite manner.     

On the robustness of ENSO teleconnections

Using observations covering the last 128 years we show that apparent changes in El Niño-Southern Oscillation (ENSO) teleconnections can be explained by chance and stem from sampling variability. This result is backed by experiments in which an atmosphere model is driven by 123 years of observed sea surface temperature. The possibility of ENSO teleconnection changes in a warming climate is further investigated using coupled GCMs driven by past and projected future greenhouse gas concentrations. These runs do not exclude physical changes in the teleconnection strength but do not agree on their magnitude and location. If existing at all, changes in the strength of ENSO teleconnection, other than obtained by chance, are small and will only be detectable on centennial time scales.     

An analysis of seasonal predictability in coupled model forecasts

In the recent decade, operational seasonal prediction systems based on initialized coupled models have been developed. An analysis of how the predictability of seasonal means in the initialized coupled predictions evolves with lead-time is presented. Because of the short lead-time, such an analysis for the temporal behavior of seasonal predictability involves a mix of both the predictability of the first and the second kind. The analysis focuses on the lead-time dependence of ensemble mean variance, and the forecast spread. Further, the analysis is for a fixed target season of December?CJanuary?CFebruary, and is for sea surface temperature, rainfall, and 200-mb height. The analysis is based on a large set of hindcasts from an initialized coupled seasonal prediction system. Various aspects of predictability of the first and the second kind are highlighted for variables with long (for example, SST), and fast (for example, atmospheric) adjustment time scale. An additional focus of the analysis is how the predictability in the initialized coupled seasonal predictions compares with estimates based on the AMIP simulations. The results indicate that differences in the set up of AMIP simulations and coupled predictions, for example, representation of air?Csea interactions, and evolution of forecast spread from initial conditions do not change fundamental conclusion about the seasonal predictability. A discussion of the analysis presented herein, and its implications for the use of AMIP simulations for climate attribution, and for time-slice experiments to provide regional information, is also included.     

ENSO teleconnections in projections of future climate in ECHAM5/MPI-OM

The teleconnections of the El Niño/Southern Oscillation (ENSO) in future climate projections are investigated using results of the coupled climate model ECHAM5/MPI-OM. For this, the IPCC SRES scenario A1B and a quadrupled CO₂ simulation are considered. It is found that changes of the mean state in the tropical Pacific are likely to condition ENSO teleconnections in the Pacific North America (PNA) region and in the North Atlantic European (NAE) region. With increasing greenhouse gas emissions the changes of the mean states in the tropical and sub-tropical Pacific are El Niño-like in this particular model. Sea surface temperatures in the tropical Pacific are increased predominantly in its eastern part and redistribute the precipitation further eastward. The dynamical response of the atmosphere is such that the equatorial east–west (Walker) circulation and the eastern Pacific inverse Hadley circulation are decreased. Over the subtropical East Pacific and North Atlantic the 200 hPa westerly wind is substantially increased. Composite maps of different climate parameters for positive and negative ENSO events are used to reveal changes of the ENSO teleconnections. Mean sea level pressure and upper tropospheric zonal winds indicate an eastward shift of the well-known teleconnection patterns in the PNA region and an increasing North Atlantic oscillation (NAO) like response over the NAE region. Surface temperature and precipitation underline this effect, particularly over the North Pacific and the central North Atlantic. Moreover, in the NAE region the 200 hPa westerly wind is increasingly related to the stationary wave activity. Here the stationary waves appear NAO-like.     

An effect of finite differences on the estimation of predictability

It is shown that the use of finite differences tends to underestimate the growth of small errors, but that the underestimation is not serious provided the resolution is sufficient.     

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。      

Reproducibility of seasonal ensemble integrations with ECMWF GCM and its association with ENSO

Summary This study evaluates seasonal climate potential predictability with a dataset of nine-member ensemble seasonal integrations produced by the ECMWF GCM for the ERA-15 period (1979–1993). The methodology used here is the measure of the ensemble reproducibility for a particular season defined by Yang et al (1998). High reproducibility reflects the dominant role of the lower boundary forcing in seasonal climate anomaly, indicating good potential predictability. Spatial patterns of the reproducibility for selected variables are documented, which exhibit obvious regionality and seasonality. Such variables are always highly reproducible over most of the tropical regions. Over the northern extratropics, primary reproducible information, taking the 500hPa geopotential height for example, is found over the PNA region during winter while over most of Asia during summer. Winter has the largest reproducible area; autumn has the lowest, while summer and spring are in between. Association of the reproducibility with ENSO events was examined regionally. Internal variances due to ensemble spread were broken down for individual years, and the reproducibility was computed for four categories: El Niño, La Niña, ENSO, and non-ENSO years. The reproducibility during winter especially over the PNA region is insensitive to ENSO events, with exceptions over the tropical western Pacific, central Siberia and Western Europe. Contrarily, ENSO events have significant impacts on the reproducibility over the southwest USA and most of Asian monsoon region during summer. These results suggest that ENSO events may not be helpful to the seasonal climate predictability over the PNA region during winter, but they may increase predictable information over many regions of the northern extratropical continents during summer.     

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。     

Seasonal precipitation reconstruction and teleconnections with ENSO based on tree ring analysis of Pinus cooperi

Tendencies of climatic variability indicate that northern Mexico will soon suffer from severe drought. Modeling the influence of climate and ecological processes would help researchers better understand the future implication of climatic variations. Here, we reconstructed historical seasonal precipitation using dendrochronological indices of Pinus cooperi and El Niño southern oscillation (ENSO). Correlation analysis was conducted to establish the precipitation response period; then a reconstruction model using independent variables was constructed using regression procedures. Available data were calibrated and verified to strengthen and validate the modeled reconstruction. Precipitation from the previous winter was best correlated with tree growth. Regression procedures showed that the residual chronology associated in a linear model with El Niño 3.4 explained 47 % of seasonal precipitation variability. This study contributes to a better understanding of historical variations in precipitation and the influence of ENSO in common tree species of northern Mexico to help land managers improve local forest management in a climate change scenario.     

Intrinsic modulation of ENSO predictability viewed through a local Lyapunov lens

The presence of rich ENSO variability in the long unforced simulation of GFDL’s CM2.1 motivates the use of tools from dynamical systems theory to study variability in ENSO predictability, and its connections to ENSO magnitude, frequency, and physical evolution. Local Lyapunov exponents (LLEs) estimated from the monthly NINO3 SSTa model output are used to characterize periods of increased or decreased predictability. The LLEs describe the growth of infinitesimal perturbations due to internal variability, and are a measure of the immediate predictive uncertainty at any given point in the system phase-space. The LLE-derived predictability estimates are compared with those obtained from the error growth in a set of re-forecast experiments with CM2.1. It is shown that the LLEs underestimate the error growth for short forecast lead times (less than 8 months), while they overestimate it for longer lead times. The departure of LLE-derived error growth rates from the re-forecast rates is a linear function of forecast lead time, and is also sensitive to the length of the time series used for the LLE calculation. The LLE-derived error growth rate is closer to that estimated from the re-forecasts for a lead time of 4 months. In the 2,000-year long simulation, the LLE-derived predictability at the 4-month lead time varies (multi)decadally only by 9–18 %. Active ENSO periods are more predictable than inactive ones, while epochs with regular periodicity and moderate magnitude are classified as the most predictable by the LLEs. Events with a deeper thermocline in the west Pacific up to five years prior to their peak, along with an earlier deepening of the thermocline in the east Pacific in the months preceding the peak, are classified as more predictable. Also, the GCM is found to be less predictable than nature under this measure of predictability.     

Interdecadal change of interannual variability and predictability of two types of ENSO

A significant interdecadal climate shift of interannual variability and predictability of two types of the El Niño-Southern Oscillation (ENSO), namely the canonical or eastern Pacific (EP)-type and Modoki or central Pacific (CP) type, are investigated. Using the retrospective forecasts of six-state-of-the-art coupled models and their multi-model ensemble (MME) for December–January–February during the period of 1972–2005 along with corresponding observed and reanalyzed data, we examine the climate regime shift that occurred in the winter of 1988/1989 and how the shift affected interannual variability and predictability of two types of ENSO for the two periods of 1972–1988 (hereafter PRE) and 1989–2005 (hereafter POST). The result first shows substantial interdecadal changes of observed sea surface temperature (SST) in mean state and variability over the western and central Pacific attributable to the significant warming trend in the POST period. In the POST period, the SST variability increased (decreased) significantly over the western (eastern) Pacific. The MME realistically reproduces the observed interdecadal changes with 1- and 4-month forecast lead time. It is found that the CP-type ENSO was more prominent and predictable during the POST than the PRE period while there was no apparent difference in the variability and predictability of the EP-type ENSO between two periods. Note that the second empirical orthogonal function mode of the Pacific SST during the POST period represents the CP-type ENSO but that during the PRE period captures the ENSO transition phase. The MME better predicts the former than the latter. We also investigate distinctive regional impacts associated with the two types of ENSO during the two periods.     

Observed precipitation in the Paraná-Plata hydrological basin: long-term trends, extreme conditions and ENSO teleconnections

The Paraná-Plata basin is the second largest hydrological basin in South America and is of great importance for the countries of the region (Argentina, Bolivia, Brazil, Paraguay and Uruguay). The present study focuses on the long-term trends in basin-scale precipitation with special emphasis on the role of distribution changes in extreme large-scale precipitation events and on the characteristics and evolution of ENSO teleconnections over the last 50 years. First, we defined a Paraná-Plata basin total precipitation index (PTPI) as the precipitations spatially averaged over the hydrological basin. On interannual time scales, such an index is mainly representative of anomalous monsoon precipitations in the northern part of the basin and large convective precipitation anomalies in the center of the basin (Paraguay-southern Brazil-Uruguay-northern Argentina) typical of the canonical ENSO teleconnection pattern. Our major findings clearly highlight a positive trend in yearly averaged PTPI mainly from the late 1960s to the early 1980s with a strong dependence from month-to-month. The largest precipitation increase is observed from November to May in southern Brazil and Argentina. A close examination of PTPI distributions during the two halves of the period 1950–2001 shows that the changes in the mean state from 1950–1975 to 1976–2001 result from significant changes in each calendar month mean state and in the tails of the PTPI anomaly distributions in May with lesser and weaker large-scale dry events and stronger large-scale wet events. Further studies will be needed to assess whether the observed trend in large-scale extreme precipitation conditions can be related to natural climate variability or anthropogenic activities and whether it is associated to changes in local/regional extreme events. The stronger wet conditions in different months seem to be associated to changes in ENSO characteristics (amplitude, propagation, spatial structure, ...) since the 1982–1983 El Niño. Indeed, spatial ENSO teleconnections (stronger in November and April–May) have greatly evolved from 1950–1975 to 1976–2001. Moreover, we demonstrate that there is a strong modulation and displacement of the teleconnection patterns from one event to another, impeding the definition of robust statistical relationship between ENSO and precipitation in the Paraná-Plata basin (except maybe over a very limited area near the common border between Paraguay, Argentina and Brazil). Finally, the non-antisymmetrical patterns of precipitation between El Niño and La Niña conditions and the non-linear relationship between precipitation and either Niño3.4 or Niño1+2 sea surface temperature indices show that linear statistical forecast systems are actually of very limited use for impact predictions on society on a local or regional scale.     

晚秋与后冬间欧亚遥相关型波列反相现象探究

围绕1979/1980—2013/2014年晚秋(11月)与后冬(次年1、2月)间欧亚遥相关(EU)型波列关系展开研究,揭示了晚秋与后冬间欧亚遥相关指数存在显著负相关,即二者主要呈反位相变化。对比晚秋与后冬间欧亚遥相关型呈反位相和同位相变化时的环流演变规律发现,反位相变化年晚秋环流异常对后冬有显著的指示意义,而同位相变化年晚秋环流异常对后冬指示意义较弱。就可能的外部成因而言,反位相与同位相变化过程均与北大西洋湍流热通量(NATU)异常有较好的对应关系。具体物理过程表现为:当北大西洋湍流热通量正(负)异常时,有利于北大西洋50°N附近上升(下沉)运动及对流层中低层水汽含量显著增多(减少),相应北大西洋上空高度场乃至整个欧亚遥相关型波列表现为负(正)异常。     

Relative contribution of soil moisture and snow mass to seasonal climate predictability: a pilot study

Land surface hydrology (LSH) is a potential source of long-range atmospheric predictability that has received less attention than sea surface temperature (SST). In this study, we carry out ensemble atmospheric simulations driven by observed or climatological SST in which the LSH is either interactive or nudged towards a global monthly re-analysis. The main objective is to evaluate the impact of soil moisture or snow mass anomalies on seasonal climate variability and predictability over the 1986–1995 period. We first analyse the annual cycle of zonal mean potential (perfect model approach) and effective (simulated vs. observed climate) predictability in order to identify the seasons and latitudes where land surface initialization is potentially relevant. Results highlight the influence of soil moisture boundary conditions in the summer mid-latitudes and the role of snow boundary conditions in the northern high latitudes. Then, we focus on the Eurasian continent and we contrast seasons with opposite land surface anomalies. In addition to the nudged experiments, we conduct ensembles of seasonal hindcasts in which the relaxation is switched off at the end of spring or winter in order to evaluate the impact of soil moisture or snow mass initialization. LSH appears as an effective source of surface air temperature and precipitation predictability over Eurasia (as well as North America), at least as important as SST in spring and summer. Cloud feedbacks and large-scale dynamics contribute to amplify the regional temperature response, which is however, mainly found at the lowest model levels and only represents a small fraction of the observed variability in the upper troposphere.