The Atlantic Multidecadal Oscillation in twentieth century climate simulations: uneven progress from CMIP3 to CMIP5

Decadal variability in the climate system from the Atlantic Multidecadal Oscillation (AMO) is one of the major sources of variability at this temporal scale that climate models must properly incorporate because of its climate impact. The current analysis of historical simulations of the twentieth century climate from models participating in the CMIP3 and CMIP5 projects assesses how these models portray the observed spatiotemporal features of the sea surface temperature (SST) and precipitation anomalies associated with the AMO. A short sample of the models is analyzed in detail by using all ensembles available of the models CCSM3, GFDL-CM2.1, UKMO-HadCM3, and ECHAM5/MPI-OM from the CMIP3 project, and the models CCSM4, GFDL-CM3, UKMO-HadGEM2-ES, and MPI-ESM-LR from the CMIP5 project. The structure and evolution of the SST anomalies of the AMO have not progressed consistently from the CMIP3 to the CMIP5 models. While the characteristic period of the AMO (smoothed with a binomial filter applied fifty times) is underestimated by the three of the models, the e-folding time of the autocorrelations shows that all models underestimate the 44-year value from observations by almost 50 %. Variability of the AMO in the 10–20/70–80 year ranges is overestimated/underestimated in the models and the variability in the 10–20 year range increases in three of the models from the CMIP3 to the CMIP5 versions. Spatial variability and correlation of the AMO regressed precipitation and SST anomalies in summer and fall indicate that models are not up to the task of simulating the AMO impact on the hydroclimate over the neighboring continents. This is in spite of the fact that the spatial variability and correlations in the SST anomalies improve from CMIP3 to CMIP5 versions in two of the models. However, a multi-model mean from a sample of 14 models whose first ensemble was analyzed indicated there were no improvements in the structure of the SST anomalies of the AMO or associated regional precipitation anomalies in summer and fall from CMIP3 to CMIP5 projects.     

An evaluation of the CMIP3 and CMIP5 simulations in their skill of simulating the spatial structure of SST variability

The natural sea surface temperature (SST) variability in the global oceans is evaluated in simulations of the Climate Model Intercomparison Project Phase 3 (CMIP3) and CMIP5 models. In this evaluation, we examine how well the spatial structure of the SST variability matches between the observations and simulations on the basis of their leading empirical orthogonal functions-modes. Here we focus on the high-pass filter monthly mean time scales and the longer 5 years running mean time scales. We will compare the models and observations against simple null hypotheses, such as isotropic diffusion (red noise) or a slab ocean model, to illustrate the models skill in simulating realistic patterns of variability. Some models show good skill in simulating the observed spatial structure of the SST variability in the tropical domains and less so in the extra-tropical domains. However, most models show substantial deviations from the observations and from each other in most domains and particularly in the North Atlantic and Southern Ocean on the longer (5 years running mean) time scale. In many cases the simple spatial red noise null hypothesis is closer to the observed structure than most models, despite the fact that the observed SST variability shows significant deviations from this simple spatial red noise null hypothesis. The CMIP models tend to largely overestimate the effective spatial number degrees of freedom and simulate too strongly localized patterns of SST variability at the wrong locations with structures that are different from the observed. However, the CMIP5 ensemble shows some improvement over the CMIP3 ensemble, mostly in the tropical domains. Further, the spatial structure of the SST modes of the CMIP3 and CMIP5 super ensemble is more realistic than any single model, if the relative explained variances of these modes are scaled by the observed eigenvalues.     

表面气温内部变率估算方法的比较研究

本文利用37个CMIP5模式和CESM（Community Earth System Model）包含40个成员的超级集合试验的表面气温预估数据，比较了工业革命前气候参照试验、多项式拟合法和方差分析方法这三种目前在国际上运用较多的方法所估算的表面气温内部变率的异同，分析了内部变率的估算对气候预估中信号萌芽时间（TOE）的影响。结果表明:若采用CMIP5多模式集合，则工业革命前气候参照试验和多项式拟合法都是估算内部变率的合理方法，而方差分析方法则由于包含模式性能自身的影响会夸大内部变率故不推荐使用。内部变率的全球分布呈现出极向强化的现象，中高纬度地区的内部变率幅度远大于热带、副热带地区。内部变率受不同排放情景的影响较小，且随时间无显著变化，但方差分析方法估算的内部变率在热带地区容易受到排放情景的影响。若基于类似CESM这样的单个气候模式的超级集合模拟试验来估算内部变率，三种方法估算的结果相似。不同方法估算的内部变率对TOE的影响主要位于北大西洋拉布拉多海、南大洋威德尔海和罗斯海等邻近海洋深对流区。对于中国区域平均来说，基于CESM超级集合模拟试验，三种方法估算的内部变率与强迫信号之比都小于15%；对CMIP5多模式集合，采用工业革命前气候参照试验和多项式拟合法得到的结果与此接近，但若采用方差分析方法则显著高估内部变率的作用。     

The CLIVAR C20C project: skill of simulating Indian monsoon rainfall on interannual to decadal timescales. Does GHG forcing play a role?

The ability of atmospheric general circulation models (AGCMs), that are forced with observed sea surface temperatures (SSTs), to simulate the Indian monsoon rainfall (IMR) variability on interannual to decadal timescales is analyzed in a multimodel intercomparison. The multimodel ensemble has been performed within the CLIVAR International “Climate of the 20th Century” (C20C) Project. This paper is part of a C20C intercomparison of key climate time series. Whereas on the interannual timescale there is modest skill in reproducing the observed IMR variability, on decadal timescale the skill is much larger. It is shown that the decadal IMR variability is largely forced, most likely by tropical sea surface temperatures (SSTs), but as well by extratropical and especially Atlantic Multidecadal Oscillation (AMO) related SSTs. In particular there has been a decrease from the late 1950s to the 1990s that corresponds to a general warming of tropical SSTs. Using a selection of control integrations from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3), it is shown that the increase of greenhouse gases (GHG) in the twentieth century has not significantly contributed to the observed decadal IMR variability.     

The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century

The boreal summer Asian monsoon has been evaluated in 25 Coupled Model Intercomparison Project-5 (CMIP5) and 22 CMIP3 GCM simulations of the late twentieth Century. Diagnostics and skill metrics have been calculated to assess the time-mean, climatological annual cycle, interannual variability, and intraseasonal variability. Progress has been made in modeling these aspects of the monsoon, though there is no single model that best represents all of these aspects of the monsoon. The CMIP5 multi-model mean (MMM) is more skillful than the CMIP3 MMM for all diagnostics in terms of the skill of simulating pattern correlations with respect to observations. Additionally, for rainfall/convection the MMM outperforms the individual models for the time mean, the interannual variability of the East Asian monsoon, and intraseasonal variability. The pattern correlation of the time (pentad) of monsoon peak and withdrawal is better simulated than that of monsoon onset. The onset of the monsoon over India is typically too late in the models. The extension of the monsoon over eastern China, Korea, and Japan is underestimated, while it is overestimated over the subtropical western/central Pacific Ocean. The anti-correlation between anomalies of all-India rainfall and Niño3.4 sea surface temperature is overly strong in CMIP3 and typically too weak in CMIP5. For both the ENSO-monsoon teleconnection and the East Asian zonal wind-rainfall teleconnection, the MMM interannual rainfall anomalies are weak compared to observations. Though simulation of intraseasonal variability remains problematic, several models show improved skill at representing the northward propagation of convection and the development of the tilted band of convection that extends from India to the equatorial west Pacific. The MMM also well represents the space–time evolution of intraseasonal outgoing longwave radiation anomalies. Caution is necessary when using GPCP and CMAP rainfall to validate (1) the time-mean rainfall, as there are systematic differences over ocean and land between these two data sets, and (2) the timing of monsoon withdrawal over India, where the smooth southward progression seen in India Meteorological Department data is better realized in CMAP data compared to GPCP data.     

Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.     

Climate Comparisons and Change Projections for the Northwest Atlantic from Six CMIP5 Models

Abstract

Key physical variables for the Northwest Atlantic (NWA) are examined in the “historical” and two future Representative Concentration Pathway (RCP) simulations of six Earth System Models (ESMs) available through Phase 5 of the Climate Model Intercomparison Project (CMIP5). The variables are air temperature, sea-ice concentration, surface and subsurface ocean temperature and salinity, and ocean mixed-layer depth. Comparison of the historical simulations with observations indicates that the models provide a good qualitative and approximate quantitative representation of many of the large-scale climatological features in the NWA (e.g., annual cycles and spatial patterns). However, the models represent the detailed structure of some important NWA ocean and ice features poorly, such that caution is needed in the use of their projected future changes. Monthly “climate change” fields between the bidecades 1986–2005 and 2046–2065 are described, using ensemble statistics of the changes across the six ESMs. The results point to warmer air temperatures everywhere, warmer surface ocean temperatures in most areas, reduced sea-ice extent and, in most areas, reduced surface salinities and mixed-layer depths. However, the magnitudes of the inter-model differences in the projected changes are comparable to those of the ensemble-mean changes in many cases, such that robust quantitative projections are generally not possible for the NWA.     

AMO’s structure and climate footprint in observations and IPCC AR5 climate simulations

This study aims to characterize the spatiotemporal features of the low frequency Atlantic Multidecadal Oscillation (AMO), its oceanic and atmospheric footprint and its associated hydroclimate impact. To accomplish this, we compare and evaluate the representation of AMO-related features both in observations and in historical simulations of the twentieth century climate from models participating in the IPCC’s CMIP5 project. Climate models from international leading research institutions are chosen: CCSM4, GFDL-CM3, UKMO-HadCM3 and ECHAM6/MPI-ESM-LR. Each model employed includes at least three and as many as nine ensemble members. Our analysis suggests that the four models underestimate the characteristic period of the AMO, as well as its temporal variability; this is associated with an underestimation/overestimation of spectral peaks in the 70–80 year/10–20 year range. The four models manifest the mid-latitude focus of the AMO-related SST anomalies, as well as certain features of its subsurface heat content signal. However, they are limited when it comes to simulating some of the key oceanic and atmospheric footprints of the phenomenon, such as its signature on subsurface salinity, oceanic heat content and geopotential height anomalies. Thus, it is not surprising that the models are unable to capture the majority of the associated hydroclimate impact on the neighboring continents, including underestimation of the surface warming that is linked to the positive phase of the AMO and is critical for the models to be trusted on projections of future climate and decadal predictions.     

North Pacific SST Forcing on the Central United States “Warming Hole” as Simulated in CMIP5 Coupled Historical and Uncoupled AMIP Experiments

The central United States experienced a cooling trend during the twentieth century, called the “warming hole,” most notably in the last quarter of the century when global warming accelerated. The coupled simulations of the models that participated in the Coupled Model Intercomparison Project, Phases 3 and 5 (CMIP3/5), have been unable to reproduce this abnormal cooling phenomenon satisfactorily. An unrealistic representation of the observed phasing of the Pacific Decadal Oscillation (PDO)—one of the proposed forcing mechanisms for the warming hole—in the models is considered to be one of the main causes of this effect. The CMIP5’s uncoupled Atmospheric Model Intercomparison Project (AMIP) experiment, whose duration approximately coincides with the peak warming hole cooling period, provides an opportunity, when compared with the coupled historical experiment, to examine the role of the variation in Pacific Ocean sea surface temperature (SST) in the warming hole’s formation and also to assess the skill of the models in simulating the teleconnection between Pacific SST and the continental climate in North America. Accordingly, this study compared AMIP and historical runs in the CMIP5 suite thereby isolating the role of SST forcing in the formation of the warming hole and its maintenance mechanisms. It was found that, even when SST forcing in the AMIP run was “perfectly” prescribed in the models, the skill of the models in simulating the warming hole cooling in the central United States showed little improvement over the historical run, in which SST is calculated interactively, even though the AMIP run overestimated the anti-correlation between temperature in the central United States and the PDO index. The fact that better simulation of the PDO phasing in the AMIP run did not translate into an improved summer cooling trend in the central United States suggests that the inability of the coupled CMIP5 models to reproduce the warming hole under the historical run is not mainly a result of the mismatch between simulated and observed PDO phasing, as believed.     

Climate impacts of recent multidecadal changes in Atlantic Ocean Sea Surface Temperature: a multimodel comparison

During the twentieth century sea surface temperatures in the Atlantic Ocean exhibited prominent multidecadal variations. The source of such variations has yet to be rigorously established—but the question of their impact on climate can be investigated. Here we report on a set of multimodel experiments to examine the impact of patterns of warming in the North Atlantic, and cooling in the South Atlantic, derived from observations, that is characteristic of the positive phase of the Atlantic Multidecadal Oscillation (AMO). The experiments were carried out with six atmospheric General Circulation Models (including two versions of one model), and a major goal was to assess the extent to which key climate impacts are consistent between the different models. The major climate impacts are found over North and South America, with the strongest impacts over land found over the United States and northern parts of South America. These responses appear to be driven by a combination of an off-equatorial Gill response to diabatic heating over the Caribbean due to increased rainfall within the region and a Northward shift in the Inter Tropical Convergence Zone (ITCZ) due to the anomalous cross-equatorial SST gradient. The majority of the models show warmer US land temperatures and reduced Mean Sea Level Pressure during summer (JJA) in response to a warmer North Atlantic and a cooler South Atlantic, in line with observations. However the majority of models show no significant impact on US rainfall during summer. Over northern South America, all models show reduced rainfall in southern hemisphere winter (JJA), whilst in Summer (DJF) there is a generally an increase in rainfall. However, there is a large spread amongst the models in the magnitude of the rainfall anomalies over land. Away from the Americas, there are no consistent significant modelled responses. In particular there are no significant changes in the North Atlantic Oscillation (NAO) over the North Atlantic and Europe in Winter (DJF). Additionally, the observed Sahel drying signal in African rainfall is not seen in the modelled responses. Suggesting that, in contrast to some studies, the Atlantic Multidecadal Oscillation was not the primary driver of recent reductions in Sahel rainfall.     

北大西洋年代际振荡（AMO）气候影响的研究评述

北大西洋年代际振荡（theAtlantic Multidecadal Oscillation,AMO）是发生在北大西洋区域空间上具有海盆尺度、时间上具有多十年尺度的海表温度（sea surface temperature,SST）准周期性暖冷异常变化。它具有65～80a周期,振幅为0.4℃。AMO的形成与热盐环流的准周期性振荡有关,它是气候系统的一种自然变率。诸多研究表明,AMO在北大西洋局地气候及全球其他区域气候演变中发挥了重要影响。欧亚大陆的表面气温,美国大陆、巴西东北部、西非以及南亚的降水,北大西洋飓风等都与之密切相关。AMO对东亚季风气候的年代际变化有显著的调制作用,暖位相AMO增强东亚夏季风,减弱冬季风,冷位相则相反。本文总结了这方面的研究进展,讨论了AMO对未来气候预测的意义,认为最近20多年来我国冬季的显著增暖与AMO处于暖位相有关,是人类温室气体强迫与暖位相AMO（自然因子）两种增暖影响相叠加的结果。随着AMO逐渐转入冷位相,我国冬季变暖趋势将放慢,并有望于21世纪20年代中期逆转。     

Atlantic Multidecadal Oscillation and Northern Hemisphere’s climate variability

Proxy and instrumental records reflect a quasi-cyclic 50–80-year climate signal across the Northern Hemisphere, with particular presence in the North Atlantic. Modeling studies rationalize this variability in terms of intrinsic dynamics of the Atlantic Meridional Overturning Circulation influencing distribution of sea-surface-temperature anomalies in the Atlantic Ocean; hence the name Atlantic Multidecadal Oscillation (AMO). By analyzing a lagged covariance structure of a network of climate indices, this study details the AMO-signal propagation throughout the Northern Hemisphere via a sequence of atmospheric and lagged oceanic teleconnections, which the authors term the “stadium wave”. Initial changes in the North Atlantic temperature anomaly associated with AMO culminate in an oppositely signed hemispheric signal about 30?years later. Furthermore, shorter-term, interannual-to-interdecadal climate variability alters character according to polarity of the stadium-wave-induced prevailing hemispheric climate regime. Ongoing research suggests mutual interaction between shorter-term variability and the stadium wave, with indication of ensuing modifications of multidecadal variability within the Atlantic sector. Results presented here support the hypothesis that AMO plays a significant role in hemispheric and, by inference, global climate variability, with implications for climate-change attribution and prediction.     

IAP-DecPreS年代际气候预测系统及其预报技巧

针对未来1~10 a气候状态的近期气候预测(年代际预测)是当前国际气候领域的研究热点。本文综述了中国科学院大气物理研究所发展的基于耦合气候系统模式的年代际气候预测系统IAP-DecPreS相关的研究进展。IAP-DecPreS系统的核心部分是耦合模式海洋分量初始化方案,“集合最优插值-分析增量更新”(EnOI-IAU)方案,该方案将集合最优插值(EnOI)和增量分析更新(IAU)结合起来,能够同化原始的海洋次表层温度廓线观测资料,对耦合模式进行初始化。系统的年代际回报试验表明,IAP-DecPreS对太平洋年代际振荡和大西洋多年代际变率的预测技巧与耦合模式比较计划第五阶段(CMIP5)技巧较高的模式相当。IAP-DecPreS系统被广泛应用于气候预测相关研究,包括火山气溶胶对年代际预测技巧的影响,全场同化和异常场同化两种不同的初始化方法对ENSO、印度洋偶极子模态和印度洋洋盆模态等的预测技巧的影响。最后,结合国际发展态势,对未来IAP-DecPreS的发展进行了讨论。     

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).     

Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region

One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.     

A further assessment of vegetation feedback on decadal Sahel rainfall variability

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM (“SPEEDY”) is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.     

大样本初始化十年际预测试验（CESM-DPLE）对东亚夏季气候预测的评估

基于气温和降水观测资料以及美国国家环境预报中心/国家大气研究中心(NCEP/NCAR)大气再分析资料,系统评估了大样本初始化十年际预测试验(CESM-DPLE)对1959—2016年东亚夏季气候预测的能力。结果表明,CESM-DPLE能较好地模拟东亚夏季气候以及相关主要大气环流系统的基本态特征,在年际尺度上对东亚气温有很高的预测技巧但对降水几乎没有预测能力。CESM-DPLE再现了北大西洋多年代际振荡(AMO)经由激发遥相关波列所引起的中高纬度大气环流、东亚夏季风和气候的异常。20世纪90年代末之后,北大西洋多年代际振荡由冷位相转为暖位相,遥相关波列位相调整,东亚受异常低压控制,东亚夏季风偏强,夏季气温偏高、降水偏多。总体上,尽管还存在着不足,但CESM-DPLE对东亚夏季温度年际变化以及与20世纪90年代末北大西洋多年代际振荡位相转变相联的东亚夏季气候年代际变化具备一定的预测能力,是目前研究和预测东亚气候变化的一套较好试验数据。     

Evaluation of twentieth-century Atlantic Warm Pool simulations in historical CMIP5 runs

State-of-the-art coupled global climate models are evaluated for their simulation of the Atlantic Warm Pool (AWP). Historical runs from 17 coupled climate models included in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) serve as the basis for this model evaluation study. The model simulations are directly compared to observations and reanalysis data to evaluate the climatological features and variability of the AWP within each individual model. Results reveal that a select number of models—namely the GISS-E2-R, CSIRO-Mk3.6, and MPI-ESM-LR—are successful at resolving an appropriately sized AWP with some reasonable climatological features. However, these three models exhibit an erroneously broad seasonal peak of the AWP, and its variability is significantly underestimated. Furthermore, all of the CMIP5 models exhibit a significant cold bias across the tropical Atlantic basin, which hinders their ability to accurately resolve the AWP.     

The Indian Ocean subtropical dipole mode simulated in the CMIP3 models

Using observation data and outputs from the “twentieth-century climate in coupled models” (20c3m) control runs of coupled general circulation models submitted to the Coupled Model Intercomparison Project, phase 3 (CMIP3), the ability of CMIP3 models to simulate the Indian Ocean subtropical dipole (IOSD) and its influence on the rainfall anomaly over the southern African region is investigated. Many models simulate the IOSD, but the location and shape of the sea surface temperature anomaly vary among models. This model bias is closely linked to the bias in simulating the anomalous strengthening and southward shift of the subtropical high. Almost all models fail to simulate the rainfall anomaly associated with the IOSD owing to the inaccurate simulation of the location of sea surface temperature and sea level pressure anomalies.     

Interdecadal Modulation of AMO on the Winter North Pacific Oscillation-Following Winter ENSO Relationship

It is known that the wintertime North Pacific Oscillation (NPO) is an important extratropical forcing for the occurrence of an El Ni?o?Southern Oscillation (ENSO) event in the subsequent winter via the “seasonal footprinting mechanism” (SFM). This study reveals that the Atlantic Multidecadal Oscillation (AMO) can notably modulate the relationship between the winter NPO and the following winter ENSO. During the negative AMO phase, the winter NPO has significant impacts on the following winter ENSO via the SFM. In contrast, the influence of the winter NPO on ENSO is not robust at all during the positive AMO phase. Winter NPO-generated westerly wind anomalies over the equatorial western Pacific during the following spring are much stronger during negative than positive AMO phases. It is suggested that the AMO impacts the winter NPO-induced equatorial westerly winds over the western Pacific via modulating the precipitation climatology over the tropical central Pacific and via modulating the connection of the winter NPO with spring sea surface temperature in the tropical North Atlantic.