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.     

Evolution of model systematic errors in the Tropical Atlantic Basin from coupled climate hindcasts

Significant systematic errors in the tropical Atlantic Ocean are common in state-of-the-art coupled ocean–atmosphere general circulation models. In this study, a set of ensemble hindcasts from the NCEP coupled forecast system (CFS) is used to examine the initial growth of the coupled model bias. These CFS hindcasts are 9-month integrations starting from perturbed real-time oceanic and atmospheric analyses for 1981–2003. The large number of integrations from a variety of initial states covering all months provides a good opportunity to examine how the model systematic errors grow. The monthly climatologies of ensemble hindcasts from various initial months are compared with both observed and analyzed oceanic and atmospheric datasets. Our analyses show that two error patterns are dominant in the hindcasts. One is the warming of the sea surface temperature (SST) in the southeastern tropical Atlantic Ocean. This error grows faster in boreal summer and fall and peaks in November–December at round 2°C in the open ocean. It is caused by an excessive model surface shortwave radiative flux in this region, especially from boreal summer to fall. The excessive radiative forcing is in turn caused by the CFS inability to reproduce the observed amount of low cloud cover in the southeastern ocean and its seasonal increase. According to a comparison between the seasonal climatologies from the CFS hindcasts and a long-term simulation of the atmospheric model forced with observed SST, the CFS low cloud and radiation errors are inherent to its atmospheric component. On the other hand, the SST error in CFS is a major cause of the model’s southward bias of the intertropical convergence zone (ITCZ) in boreal winter and spring. An analysis of the SST errors of the 6-month ensemble hindcasts by seven coupled models in the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction project shows that this SST error pattern is common in coupled climate hindcasts. The second error pattern is an excessive deepening of the model thermocline depth to the north of the equator from the western coast toward the central ocean. This error grows fastest in boreal summer. It is forced by an overly strong local anticyclonic surface wind stress curl and is in turn related to the weakened northeast trade winds in summer and fall. The thermocline error in the northwest delays the annual shoaling of the equatorial thermocline in the Gulf of Guinea remotely through the equatorial waveguide.     

SST and ENSO variability and change simulated in historical experiments of CMIP5 models

This work documents the diversity in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models in simulating different aspects of sea surface temperature (SST) variability, particularly those associated with the El Niño–Southern Oscillation (ENSO), as well as the impact of low-frequency variations on the ENSO variability and its global teleconnection. The historical simulations (1870–2005) include 10 models with ensemble member ranging from 3 to 10 that are forced with observed atmospheric composition changes reflecting both natural and anthropogenic forcings. It is shown that the majority of the CMIP5 models capture the relative large SST anomaly variance in the tropical central and eastern Pacific, as well as in North Pacific and North Atlantic. The frequency of ENSO is not well captured by almost all models, particularly for the period of 5–6 years. The low-frequency variations in SST caused by external forcings affect the SST variability and also modify the global teleconnection of ENSO. The models reproduce the global averaged SST low-frequency variations, particularly since 1970s. However, majority of the models are unable to correctly simulate the spatial pattern of the observed SST trends. These results suggest that it is still a challenge to reproduce the features of global historical SST variations with the state-of-the-art coupled general circulation model.     

Walker circulation controls ENSO atmospheric feedbacks in uncoupled and coupled climate model simulations

Many climate models strongly underestimate the two most important atmospheric feedbacks operating in El Niño/Southern Oscillation (ENSO), the positive (amplifying) zonal surface wind feedback and negative (damping) surface-heat flux feedback (hereafter ENSO atmospheric feedbacks, EAF). This hampers a realistic representation of ENSO dynamics in these models. Here we show that the atmospheric components of climate models participating in the 5th phase of the Coupled Model Intercomparison Project (CMIP5) when forced by observed sea surface temperatures (SST), already underestimate EAF on average by 23%, but less than their coupled counterparts (on average by 54%). There is a pronounced tendency of atmosphere models to simulate stronger EAF, when they exhibit a stronger mean deep convection and enhanced cloud cover over the western equatorial Pacific (WEP), indicative of a stronger rising branch of the Pacific Walker Circulation (PWC). Further, differences in the mean deep convection over the WEP between the coupled and uncoupled models explain a large part of the differences in EAF, with the deep convection in the coupled models strongly depending on the equatorial Pacific SST bias. Experiments with a single atmosphere model support the relation between the equatorial Pacific atmospheric mean state, the SST bias and the EAF. An implemented cold SST bias in the observed SST forcing weakens deep convection and reduces cloud cover in the rising branch of the PWC, causing weaker EAF. A warm SST bias has the opposite effect. Our results elucidate how biases in the mean state of the PWC and equatorial SST hamper a realistic simulation of the EAF.     

Analysis of the Slab Ocean El Nino atmospheric feedbacks in observed and simulated ENSO dynamics

In a recent study it was illustrated that the El Nino Southern Oscillation (ENSO) mode can exist in the absence of any ocean dynamics. This oscillating mode exists just due to the interaction between atmospheric heat fluxes and ocean heat capacity. The primary purpose of this study is to further explore these atmospheric Slab Ocean ENSO dynamics and therefore the role of positive atmospheric feedbacks in model simulations and observations. The positive solar radiation feedback to sea surface temperature (SST), due to reduced cloud cover for anomalous warm SSTs, is the main positive feedback in the Slab Ocean El Nino dynamics. The strength of this positive cloud feedback is strongly related to the strength of the equatorial cold tongue. The combination of positive latent and sensible heat fluxes to the west and negative ones to the east of positive anomalies leads to the westward propagation of the SST anomalies, which allows for oscillating behavior with a preferred period of 6–7 years. Several indications are found that parts of these dynamics are indeed observed and simulated in other atmospheric or coupled general circulation models (AGCMs or CGCMs). The CMIP3 AGCM-slab ensemble of 13 different AGCM simulations shows unstable ocean–atmosphere interactions along the equatorial Pacific related to stronger cold tongues. In observations and in the CMIP3 and CMIP5 CGCM model ensemble the strength and sign of the cloud feedback is a function of the strength of the cold tongue. In summary, this indicates that the Slab Ocean El Nino dynamics are indeed a characteristic of the equatorial Pacific climate that is only dominant or significantly contributing to the ENSO dynamics if the SST cold tongue is sufficiently strong. In the observations this is only the case during strong La Nina conditions. The presence of the Slab Ocean ENSO atmospheric feedbacks in observations and CGCM model simulations implies that the family of physical ENSO modes does have another member, which is entirely driven by atmospheric processes and does not need to have the same spatial pattern nor the same time scales as the main ENSO dynamics.     

The influence of climate regime shift on ENSO

Observations indicated that for the El Niño/Southern Oscillation (ENSO) there have been eastward displacements of the zonal wind stress (WS) anomalies and surface heat flux (short wave heat flux and latent heat flux) anomalies during El Niño episodes in the 1981–1995 regime relative to the earlier regime of 1961–1975 (without corresponding displacements during La Niña episodes). Our numerical experiments with the Zebiak–Cane coupled model generally reproduced such displacements when the model climatological fields were replaced by the observed climatologies [of sea surface temperature (SST), surface WS and surface wind atmospheric divergence] and simulated climatologies (of oceanic surface layer currents and associated upwelling) for the 1981–1995 regime. Sensitivity tests indicated that the background atmospheric state played a much more important role than the background ocean state in producing the displacements, which enhanced the asymmetry between El Niño and La Niña in the later regime. The later regime climatology state resulted in the eastward shifts in the ENSO system (WS and SST) only during El Niño, through the eastward shift of the atmosphere convergence heating rate in the coupled model. The ENSO period and ENSO predictability were also enhanced in the coupled model under the later regime climatology. That the change in the mean state of the tropical Pacific atmosphere and ocean after the mid 1970s could have produced the observed changes in ENSO properties is consistent with our findings.     

A Hybrid Coupled Ocean–Atmosphere Model and Its Simulation of ENSO and Atmospheric Responses

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.     

一个改进的混合型海气耦合模式：ENSO模拟

通过在中国科学院大气物理研究所热带太平洋环流模式与一个统计大气模式所建立的混合型海气耦合模式中引入次表层上卷海温非局地参数化方案, 对比分析了次表层上卷海温对耦合模式模拟结果的影响, 表明在引入次表层上卷海温非局地参数化方案前耦合模式模拟的SSTA最大变率中心位于日界线附近赤道南北狭窄范围内, 而在赤道东太平洋及南美沿岸一带变率过低, 周期呈准2年振荡。改进后, 耦合模式模拟结果的分布不论在东西方向亦或南北方向与观测更为相近, 振荡周期为4年左右, 而且还能模拟出观测中ENSO振荡的季节依赖性特征。进一步分析改进的耦合模式中海气耦合特征, 表明 “延迟振子” 理论、 “西太平洋振子” 理论、 “充电-放电振子” 理论及 “平流-反射” 理论所揭示的一些规律在该模式中都能被不同程度地描述出来, 这说明在实际的ENSO循环过程中, 可能有多种机制在同时起作用。     

ENSIP: the El Niño simulation intercomparison project

An ensemble of twenty four coupled ocean-atmosphere models has been compared with respect to their performance in the tropical Pacific. The coupled models span a large portion of the parameter space and differ in many respects. The intercomparison includes TOGA (Tropical Ocean Global Atmosphere)-type models consisting of high-resolution tropical ocean models and coarse-resolution global atmosphere models, coarse-resolution global coupled models, and a few global coupled models with high resolution in the equatorial region in their ocean components. The performance of the annual mean state, the seasonal cycle and the interannual variability are investigated. The primary quantity analysed is sea surface temperature (SST). Additionally, the evolution of interannual heat content variations in the tropical Pacific and the relationship between the interannual SST variations in the equatorial Pacific to fluctuations in the strength of the Indian summer monsoon are investigated. The results can be summarised as follows: almost all models (even those employing flux corrections) still have problems in simulating the SST climatology, although some improvements are found relative to earlier intercomparison studies. Only a few of the coupled models simulate the El Niño/Southern Oscillation (ENSO) in terms of gross equatorial SST anomalies realistically. In particular, many models overestimate the variability in the western equatorial Pacific and underestimate the SST variability in the east. The evolution of interannual heat content variations is similar to that observed in almost all models. Finally, the majority of the models show a strong connection between ENSO and the strength of the Indian summer monsoon.     

The variability of the East Asian summer monsoon and its relationship to ENSO in a partially coupled climate model

The variability of the East Asian summer monsoon (EASM) is studied using a partially coupled climate model (PCCM) in which the ocean component is driven by observed monthly mean wind stress anomalies added to the monthly mean wind stress climatology from a fully coupled control run. The thermodynamic coupling between the atmospheric and oceanic components is the same as in the fully coupled model and, in particular, sea surface temperature (SST) is a fully prognostic variable. The results show that the PCCM simulates the observed SST variability remarkably well in the tropical and North Pacific and Indian Oceans. Analysis of the rainfall-SST and rainfall-SST tendency correlation shows that the PCCM exhibits local air-sea coupling as in the fully coupled model and closer to what is seen in observations than is found in an atmospheric model driven by observed SST. An ensemble of experiments using the PCCM is analysed using a multivariate EOF analysis to identify the two major modes of variability of the EASM. The PCCM simulates the spatial pattern of the first two modes seen in the ERA40 reanalysis as well as part of the variability of the first principal component (correlation up to 0.5 for the model ensemble mean). Different from previous studies, the link between the first principal component and ENSO in the previous winter is found to be robust for the ensemble mean throughout the whole period of 1958–2001. Individual ensemble members nevertheless show the breakdown in the relationship before the 1980’s as seen in the observations.     

Attribution of SST variability in global oceans and the role of ENSO

Based on a novel design of coupled model simulations where sea surface temperature (SST) variability in the equatorial tropical Pacific was constrained to follow the observed El Niño—Southern Oscillation (ENSO) variability, while rest of the global oceans were free to evolve, the ENSO response in SSTs over the other ocean basins was analyzed. Conceptually the experimental setup was similar to discerning the contribution of ENSO variability to interannual variations in atmospheric anomalies. A unique feature of the analysis was that it was not constrained by a priori assumptions on the nature of the teleconnected response in SSTs. The analysis demonstrated that the time lag between ENSO SST and SSTs in other ocean basins was about 6 months. A signal-to-noise analysis indicated that between 25 and 50 % of monthly mean SST variance over certain ocean basins can be attributed to SST variability over the equatorial tropical Pacific. The experimental setup provides a basis for (a) attribution of SST variability in global oceans to ENSO variability, (b) a method for separating the ENSO influence in SST variations, and (c) understanding the contribution from other external factors responsible for variations in SSTs, for example, changes in atmospheric composition, volcanic aerosols, etc.     

IAP第四代大气环流模式的耦合气候系统模式模拟性能评估

本文首先扼要介绍了基于中国科学院大气物理研究所(简称IAP)第四代大气环流模式的新气候系统模式-CAS-ESM-C(中国科学院地球系统模式气候系统模式分量)的发展和结构,之后主要对该模式在模拟大气、海洋、陆面和海冰的气候平均态、季节循环以及主要的年际变率等方面的能力做一个初步的评估.结果表明:模式没有明显的气候漂移,各...     

Sensitivity of ENSO characteristics to a new interactive flux correction scheme in a coupled GCM

A fast coupled global climate model (CGCM) is used to study the sensitivity of El Ni?o Southern Oscillation (ENSO) characteristics to a new interactive flux correction scheme. With no flux correction applied our CGCM reveals typical bias in the background state: for instance, the cold tongue in the tropical east Pacific becomes too cold, thus degrading atmospheric sensitivity to variations of sea surface temperature (SST). Sufficient atmospheric sensitivity is essential to ENSO. Our adjustment scheme aims to sustain atmospheric sensitivity by counteracting the SST drift in the model. With reduced bias in the forcing of the atmosphere, the CGCM displays ENSO-type variability that otherwise is absent. The adjustment approach employs a one-way anomaly coupling from the ocean to the atmosphere: heat fluxes seen by the ocean are based on full SST, while heat fluxes seen by the atmosphere are based on anomalies of SST. The latter requires knowledge of the model??s climatological SST field, which is accumulated interactively in the spin-up phase (??training??). Applying the flux correction already during the training period (by utilizing the evolving SST climatology) is necessary for efficiently reducing the bias. The combination of corrected fluxes seen by the atmosphere and uncorrected fluxes seen by the ocean implies a restoring mechanism that counteracts the bias and allows for long stable integrations in our CGCM. A suite of sensitivity runs with varying training periods is utilized to study the effect of different levels of bias in the background state on important ENSO properties. Increased duration of training amplifies the coupled sensitivity in our model and leads to stronger amplitudes and longer periods of the Nino3.4 index, increased emphasis of warm events that is reflected in enhanced skewness, and more pronounced teleconnections in the Pacific. Furthermore, with longer training durations we observe a mode switch of ENSO in our model that closely resembles the observed mode switch related to the mid-1970s ??climate shift??.     

Future changes in tropical cyclone genesis in fully dynamic ocean- and mixed layer ocean-coupled climate models: a low-resolution model study

The global and regional projected changes in tropical cyclone (TC) genesis due to increased CO₂ concentrations has been investigated through a large-scale TC genesis parameter (convective seasonal genesis parameter, ConvGP) in two perturbed physics ensembles. The ensembles are based on the third generation Hadley Centre atmosphere?Cocean general circulation model with the first ensemble using a coupled fully dynamic ocean (HadCM3) and the second coupled to a simplified mixed layer thermodynamic ocean (HadSM3) both consisting of 17 members. In each ensemble, parameters are identically perturbed to provide a wide range of climate sensitivity whilst retaining a credible present-day climate simulation. It is found, by comparing the ConvGP climatology from reanalysis data with the best track genesis, that it is possible to reproduce the observed genesis distribution. Future changes in the spatial ConvGP distribution are explored with respect to each tropical ocean basin. Whilst there is a similarity in the gross pattern of the ensemble-mean projected ConvGP change between HadCM3 and HadSM3, there is a non-trivial difference in the tropical Pacific Ocean, arising from different patterns of tropical Pacific sea surface temperature change. This indicates that ocean representation can be important for regional scale projections. The quantitative contribution of individual constituent parameters (i.e. vorticity parameter, shear parameter and convective potential) to the projected ConvGP change is estimated. It is found that all three large-scale parameters generally contribute constructively, but with different magnitude, in the regions where a large doubled CO₂ response is found.     

Interannual and interdecadal variabilities in the Pacific in an MRI coupled GCM

Interannual and interdecadal variabilities in the Pacific are investigated with a coupled atmosphere-ocean GCM developed at MRI, Japan. The model is run for 70 years with flux adjustments. The model shows interannual variability in the tropical Pacific which has several typical characteristics shared with the observed ENSO. A basin-scale feature of the principal SST variation for the ENSO time scale shows negative correlation in the central North Pacific with the tropical SST, similar to that of the observed one. Associated variation of the model atmosphere indicates an intensification of the Aleutian Low and a PNA-like teleconnection pattern as a response to the tropical warm SST anomaly. The ENSO time scale variability in the midlatitude ocean consists of the westward propagation of the subsurface temperature signal and the temperature variation within the shallow mixed layer forced by the anomalous atmospheric heat fluxes. For the interdecadal time scale, variation of the SST is simulated realistically with a geographical pattern similar to that for the ENSO time scale, but it has a larger relative amplitude in the northern Pacific. For the atmosphere, spatial structure of the variation in the interdecadal time scale is also similar to that in the ENSO time scale, but has smaller amplitude in the northern Pacific. Long oceanic spin-up time (>∼10 y) in the mid-high latitude, however, makes oceanic response in the interdecadal time scale larger than that in the ENSO time scale. The lagged-regression analysis for the ocean temperature variation relative to the wind stress variation indicates that interdecadal variation of the ocean subsurface at the mid-high latitudes is considered as enhanced ocean gyre spin-up process in response to the atmospheric circulation change at the mid-high latitudes, remotely forced by the interdecadal variation of the tropical SST. Received: 6 November 1995 / Accepted: 19 April 1996     

Using idealized snow forcing to test teleconnections with the Indian summer monsoon in the Hadley Centre GCM

Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible heating over the Tibetan Plateau, and accounting for the majority of cooling through the troposphere.     

A deep learning–based U-Net model for ENSO-related precipitation responses to sea surface temperature anomalies over the tropical Pacific

SST–precipitation feedback plays an important role in ENSO evolution over the tropical Pacific and thus it is critically important to realistically represent precipitation-induced feedback for accurate simulations and predictions of ENSO. Typically, in hybrid coupled modeling for ENSO predictions, statistical atmospheric models are adopted to determine linear precipitation responses to interannual SST anomalies. However, in current coupled climate models, the observed precipitation–SST relationship is not well represented. In this study, a data-driven deep learning-based U-Net model was used to construct a nonlinear response model of interannual precipitation variability to SST anomalies. It was found that the U-Net model outperformed the traditional EOF-based method in calculating the precipitation variability. Particularly over the western-central tropical Pacific, the mean-square error (MSE) of the precipitation estimates in the U-Net model was smaller than that in the EOF model. The performance of the U-Net model was further improved when additional tendency information on SST and precipitation variability was also introduced as input variables, leading to a pronounced MSE reduction over the ITCZ.摘要SST–降水反馈过程在热带太平洋ENSO演变过程中起着重要作用, 能否真实地在数值模式中表征SST–降水年际异常之间的关系及相关反馈过程, 对于准确模拟和预测ENSO至关重要. 例如, 在一些模拟ENSO的混合型耦合模式中, 通常采用大气统计模型 (如经验正交函数; EOF) 来表征降水 (海气界面淡水通量的一个重要分量) 对SST年际异常的线性响应. 然而在当前的耦合模式中, 真实观测到的降水–SST统计关系还不能被很好地再现出来, 从而引起 ENSO模拟误差和不确定性. 在本研究中, 使用基于深度学习的U-Net模型来构建热带太平洋降水异常场对SST年际异常的非线性响应模型. 研究发现: U-Net模型的性能优于传统的基于EOF方法的模型. 特别是在热带西太平洋海区, U-Net模型估算的降水误差远小于EOF模型的模拟. 此外, 当SST和降水异常的趋势信息作为输入变量也被同时引入以进一步约束模式训练时, U-Net模型的性能可以进一步提高, 如能使热带辐合带区域的误差显著降低.     

Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.     

Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs

The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique.     

Tropical Pacific internal atmospheric dynamics and resolution in a coupled GCM

A noise reduction technique, namely the interactive ensemble (IE) approach is adopted to reduce noise at the air–sea interface due to internal atmospheric dynamics in a state-of-the-art coupled general circulation model (CGCM). The IE technique uses multiple realization of atmospheric general circulation models coupled to a single ocean general circulation model. The ensembles mean fluxes from the atmospheric simulations are communicated to the ocean component. Each atmospheric simulation receives the same SST coming from the ocean component. The only difference among the atmospheric simulations comes from perturbed initial conditions, thus the atmospheric states are, in principle synoptically independent. The IE technique can be used to better understand the importance of weather noise forcing of natural variability such as El Niño Southern Oscillation (ENSO). To study the impact of weather noise and resolution in the context of a CGCM, two IE experiments are performed at different resolutions. Atmospheric resolution is an important issue since the noise statistics will depend on the spatial scales resolved. A simple formulation to extract atmospheric internal variability is presented. The results are compared to their respective control cases where internal atmospheric variability is left unchanged. The noise reduction has a major impact on the coupled simulation and the magnitude of this effect strongly depends on the horizontal resolution of the atmospheric component model. Specifically, applying the noise reduction technique reduces the overall climate variability more effectively at higher resolution. This suggests that “weather noise” is more important in sustaining climate variability as resolution increases. ENSO statistics, dynamics, and phase asymmetry are all modified by the noise reduction, in particular ENSO becomes more regular with less phase asymmetry when noise is reduced. All these effects are more marked for the higher resolution case. In contrast, ENSO frequency is unchanged by the reduction in the weather noise, but its phase-locking to the annual cycle is strongly dependent on noise and resolution. At low resolution the noise structure is similar to the signal, whereas the spatial structure of the noise deviates from the spatial structure of the signal as resolution increases. It is also suggested that event-to-event differences are largely driven by atmospheric noise as opposed to chaotic dynamics within the context of the large-scale coupled system, suggesting that there is a well-defined “canonical” event.