An objective analysis of the observed spatial structure of the tropical Indian Ocean SST variability

The observed interannual Indian Ocean sea surface temperature (SST) variability from 1950 to 2008 is analyzed in respect to the spatial structure of the variability. The analysis is based on an objective comparison of the leading empirical orthogonal function modes against the stochastic null hypothesis of spatial red noise (isotropic diffusion). Starting from this red noise assumption, the analysis searches for those structures that are most distinct from the red noise hypothesis. This objective approach will put previously well and less known modes of variability into the context of the multivariate SST variability. The Indian Ocean SST variability is marked by relatively weak SST variability, which is strongly dominated by a basin wide monopole pattern that is caused by different processes. The leading modes of variability are the El Nino Southern Oscillation (ENSO) variability and the warming trend, which both project onto the basin wide monopole structure. Other more characteristic spatial patterns of internal variability are much less dominant in the tropical Indian Ocean, which is quite different from all other ocean basin, where characteristic teleconnection patterns exist. The remaining, ENSO independent, detrended variability is dominated by multi-pole patterns from the southern Indian Ocean reaching into the tropical Indian Ocean, which are probably primarily caused by extra-tropical atmospheric forcings. The large scale tropical Indian Ocean internal variability itself has no dominant structure. The currently often used dipole mode index (DMI) does not appear to present a dominant teleconnection pattern of the Indian Ocean internal SST variability. In the context of the objective analysis presented here, the DMI partly reflects the ENSO variability and is also a representation of the multi-dimensional, chaotic spatial red noise (isotropic diffusion) process. As such the DMI cannot be interpreted as a coherent teleconnection between the two poles.     

What Drives the Decadal Variability of Global Tropical Storm Days from 1965 to 2019?

The tropical storm day(TSD)is a combined measure of genesis and lifespan.It reflects tropical cyclone(TC)overall activity,yet its variability has rarely been studied,especially globally.Here we show that the global total TSDs exhibit pronounced interannual(3-6 years)and decadal(10 years)variations over the past five-to-six decades without a significant trend.The leading modes of the interannual and decadal variability of global TSD feature similar patterns in the western Pacific and Atlantic,but different patterns in the Eastern Pacific and the Southern Indian Ocean.The interannual and decadal leading modes are primarily linked to El Ni?o-Southern Oscillation(ENSO)and Pacific Decadal Oscillation(PDO),respectively.The TSDs-ENSO relationship has been steady during the entire 55-year period,but the TSDs-PDO relationship has experienced a breakdown in the 1980 s.We find that the decadal variation of TSD in the Pacific is associated with the PDO sea surface temperature(SST)anomalies in the tropical eastern Pacific(PDO-E),while that in the Atlantic and the Indian Ocean is associated with the PDO SST anomalies in the western Pacific(PDO-W).However,the PDO-E and PDO-W SST anomalies are poorly coupled in the 1980 s,and this"destructive PDO"pattern results in a breakdown of the TSDs-PDO relationship.The results here have an important implication for seasonal to decadal predictions of global TSD.     

基于慢特征分析方法研究陆地表面气温变率的驱动力

慢特征分析（SFA）方法可以从非平稳时间序列中提取出慢变的外强迫信息。近年来,SFA方法被应用于气候变化研究领域,用于探究气候变化的潜在驱动力及相关的动力学机制。本文基于SFA方法,提取全球陆地表面气温（LSAT）的慢变外强迫信息,研究全球LSAT慢变驱动力的空间结构特征及低频变率的主要驱动因子。SFA方法提取的LSAT慢变驱动力与历史时期全球辐射强迫（GRF）和全球海表温度（SST）的主模态（大西洋多年代际振荡AMO、热带太平洋ENSO变率和太平洋年代际振荡PDO）有显著的相关关系,表明全球大部分地区LSAT的变率受到GRF和三个SST模态的显著影响。GRF对LSAT变率的影响有全球一致性的特征,而三个SST模态对LSAT变率的影响则呈现出明显的区域特点。此外,由于SFA方法可以有效降低原始LSAT序列中随机噪声的干扰,GRF和SST模态对LSAT变率的解释方差显著提高,进一步表明GRF和SST模态是全球LSAT低频变率主要的驱动因子。最后,利用历史海温驱动AGCM试验（即AMIP试验）的结果,验证了三个SST模态对区域LSAT变率的显著影响。     

Precipitation over eastern South America and the South Atlantic Sea surface temperature during neutral ENSO periods

The dominant mode of coupled variability over the South Atlantic Ocean is known as “South Atlantic Dipole” (SAD) and is characterized by a dipole in sea surface temperature (SST) anomalies with centers over the tropical and the extratropical South Atlantic. Previous studies have shown that variations in SST related to SAD modulate large-scale patterns of precipitation over the Atlantic Ocean. Here we show that variations in the South Atlantic SST are associated with changes in daily precipitation over eastern South America. Rain gauge precipitation, satellite derived sea surface temperature and reanalysis data are used to investigate the variability of the subtropical and tropical South Atlantic and impacts on precipitation. SAD phases are assessed by performing Singular value decomposition analysis of sea level pressure and SST anomalies. We show that during neutral El Niño Southern Oscillation events, SAD plays an important role in modulating cyclogenesis and the characteristics of the South Atlantic Convergence Zone. Positive SST anomalies over the extratropical South Atlantic (SAD negative phase) are related to increased cyclogenesis near southeast Brazil as well as the migration of extratropical cyclones further north. As a consequence, these systems organize convection and increase precipitation over eastern South America.     

Simulating the influence of the South Atlantic dipole on the South Atlantic convergence zone during neutral ENSO

The South Atlantic Convergence Zone (SACZ) is an intrinsic characteristic of the South American Summer Monsoon. In a recent study, we verified that the main mode of coupled variability over the South Atlantic (South Atlantic Dipole (SAD)) plays a role in modulating the position of extratropical cyclones that affect the SACZ precipitation. In this study, we perform numerical experiments to further investigate the mechanisms between SAD and the SACZ. Numerical experiments forced with prescribed SST anomalies showed that, even though the Atlantic SST affects the position of the cyclone associated with the SACZ, the atmospheric response and precipitation patterns over land are opposed to the observations. On the other hand, experiments forced with prescribed anomalous driving fields showed that the atmospheric component of SAD plays a significant role for the right position and intensity of precipitation associated with the SACZ. SAD negative anomalies provide the low-level and upper-level atmospheric support for the intensification of the cyclone at surface and for the increase in precipitation over the land portion of the SACZ. Therefore, the numerical experiments suggest that, during El Niño Southern Oscillation neutral conditions, the SACZ precipitation variability associated with SAD is largely dependent on the atmospheric variability rather than the underlying SST.     

Inter-annual temperature and precipitation variations over the Litani Basin in response to atmospheric circulation patterns

This study examines the sensitivity of a mid-size basin’s temperature and precipitation response to different global and regional climate circulation patterns. The implication of the North Atlantic Oscillation (NAO), El Ni?o Southern Oscillation (ENSO), Indian Monsoon and ten other teleconnection patterns of the Northern Hemisphere are investigated. A methodology to generate a basin-scale, long-term monthly surface temperature and precipitation time series has been established using different statistical tests. The Litani River Basin is the focus of this study. It is located in Lebanon, east of the Mediterranean Basin, which is known to have diverse geophysical and environmental characteristics. It was selected to explore the influence of the diverse physical and topographical features on its hydroclimatological response to global and regional climate patterns. We also examine the opportunity of conducting related studies in areas with limited long-term measured climate and/or hydrological data. Litani's monthly precipitation and temperature data have been collected and statistically extrapolated using remotely sensed data products from satellites and as well as in situ gauges. Correlations between 13 different teleconnection indices and the basin’s precipitation and temperature series are investigated. The study shows that some of the annual and seasonal temperature and precipitation variance can be partially associated with many atmospheric circulation patterns. This would give the opportunity to relate the natural climate variability with the watershed’s hydroclimatology performance and thus differentiate it from other anthropogenic induced climate change outcomes.     

Sahel rainfall and decadal to multi-decadal sea surface temperature variability

Decadal Sahelian rainfall variability was mainly driven by sea surface temperatures (SSTs) during the twentieth century. At the same time SSTs showed a marked long-term global warming (GW) trend. Superimposed on this long-term trend decadal and multi-decadal variability patterns are observed like the Atlantic Multidecadal Oscillation (AMO) and the inter-decadal Pacific Oscillation (IPO). Using an atmospheric general circulation model we investigate the relative contribution of each component to the Sahelian precipitation variability. To take into account the uncertainty related to the use of different SST data sets, we perform the experiments using HadISST1 and ERSSTv3 reconstructed sets. The simulations show that all three SST signals have a significant impact over West Africa: the positive phases of the GW and the IPO lead to drought over the Sahel, while a positive AMO enhances Sahel rainfall. The tropical SST warming is the main cause for the GW impact on Sahel rainfall. Regarding the AMO, the pattern of anomalous precipitation is established by the SSTs in the Atlantic and Mediterranean basins. In turn, the tropical SST anomalies control the impact of the IPO component on West Africa. Our results suggest that the low-frequency evolution of Sahel rainfall can be interpreted as the competition of three factors: the effect of the GW, the AMO and the IPO. Following this interpretation, our results show that 50% of the SST-driven Sahel drought in the 1980s is explained by the change to a negative phase of the AMO, and that the GW contribution was 10%. In addition, the partial recovery of Sahel rainfall in recent years was mainly driven by the AMO.     

我国西南地区干湿季降水的主模态分析

利用我国西南地区26个台站降水资料,通过经验正交函数（EOF）分解的方法,分析了1980～2009年该地区干季（10～4月）和湿季（5～9月）降水的主模态。我国西南地区干季降水的时空变化存在两种主模态,它们分别可以解释总方差的22.4%和15.6%。第1主模态为全区一致型,具有准两年周期振荡的年际变化特征;第2主模态为东南—西北反向型,从20世纪90年代中期至21世纪初呈现2～3年的变化周期。我国西南地区湿季降水的时空变化存在三种主模态,它们分别可以解释总方差的17.1%,13.8%和11.1%。第1主模态为全区一致型,20世纪90年代初期具有较强的2～4年周期;第2主模态为经向偶极子型分布,并具有显著的4年周期;第3主模态为纬向偶极子型分布,具有2～4年的年际变化信号。进一步利用NCEP/NCAR再分析资料以及美国国家海洋和大气管理局（NOAA）的海表面温度（SST）资料,通过合成分析和回归分析的方法探讨了与干湿季降水各主模态对应的大尺度大气环流和海温状况。我国西南地区干季降水第1主模态与北极涛动（AO）有明显的正相关关系,对应的大气环流和海温状况表现为高纬北冰洋与中纬度地区上空高度场的反向异常分布,北大西洋和北太平洋海温低纬与中高纬的偶极子型异常分布;第2主模态与中高纬欧亚大陆上空高度场经向偶极子型异常分布有关,中纬度北太平洋的海温异常与该模态具有紧密的联系。我国西南地区湿季降水第1主模态与北大西洋涛动（NAO）显著负相关,对应的大气环流和海温状况表现为北大西洋上,高纬度与中纬度地区上空高度场的偶极子型异常分布,海温从低纬到中高纬的三极子型异常分布;第2主模态受欧亚大陆上空高度场经向三极子型异常分布影响,并与北太平洋海温异常的一致型分布有关;第3主模态可能与El Ni?o Modoki有关,同时受到南亚高压的影响,赤道太平洋海温的纬向三极子型异常分布对该模态具有一定的潜在预报意义。     

La Niña diversity and Northwest Indian Ocean Rim teleconnections

The differences in tropical Pacific sea surface temperature (SST) expressions of El Niño-Southern Oscillation (ENSO) events of the same phase have been linked with different global atmospheric circulation patterns. This study examines the dynamical forcing of precipitation during October–December (OND) and March–May (MAM) over East Africa and during December–March (DJFM) over Central-Southwest Asia for 1950–2010 associated with four tropical Pacific SST patterns characteristic of La Niña events, the cold phase of ENSO. The self-organizing map method along with a statistical distinguishability test was used to isolate La Niña events, and seasonal precipitation forcing was investigated in terms of the tropical overturning circulation and thermodynamic and moisture budgets. Recent La Niña events with strong opposing SST anomalies between the central and western Pacific Ocean (phases 3 and 4), force the strongest global circulation modifications and drought over the Northwest Indian Ocean Rim. Over East Africa during MAM and OND, subsidence is forced by an enhanced tropical overturning circulation and precipitation reductions are exacerbated by increases in moisture flux divergence. Over Central-Southwest Asia during DJFM, the thermodynamic forcing of subsidence is primarily responsible for precipitation reductions, with moisture flux divergence acting as a secondary mechanism to reduce precipitation. Eastern Pacific La Niña events in the absence of west Pacific SST anomalies (phases 1 and 2), are associated with weaker global teleconnections, particularly over the Indian Ocean Rim. The weak regional teleconnections result in statistically insignificant precipitation modifications over East Africa and Central-Southwest Asia.     

Predictable patterns and predictive skills of monsoon precipitation in Northern Hemisphere summer in NCEP CFSv2 reforecasts

The predictable patterns and predictive skills of monsoon precipitation in the Northern Hemisphere summer (June–July–August) are examined using reforecasts (1983–2010) from the National Center for Environmental Prediction Climate Forecast System version 2 (CFSv2). The possible connections of these predictable patterns with global sea surface temperature (SST) are investigated. The empirical orthogonal function analysis with maximized signal-to-noise ratio is used to isolate the predictable patterns of the precipitation for three regional monsoons: the Asian and Indo-Pacific monsoon (AIPM), the Africa monsoon (AFM), and the North America monsoon (NAM). Overall, the CFSv2 well predicts the monsoon precipitation patterns associated with El Niño-South Oscillation (ENSO) due to its good prediction skill for ENSO. For AIPM, two identified predictable patterns are an equatorial dipole pattern characterized by opposite variations between the equatorial western Pacific and eastern Indian Ocean, and a tropical western Pacific pattern characterized by opposite variations over the tropical northwestern Pacific and the Philippines and over the regions to its west, north, and southeast. For NAM, the predictable patterns are a tropical eastern Pacific pattern with opposite variations in the tropical eastern Pacific and in Mexico, the Guyana Plateau and the equatorial Atlantic, and a Central American pattern with opposite variations in the eastern Pacific and the North Atlantic and in the Amazon Plains. The CFSv2 can predict these patterns at least 5 months in advance. However, compared with the good skill in predicting AIPM and NAM precipitation patterns, the CFSv2 exhibits little predictive skill for AFM precipitation, probably because the variability of the tropical Atlantic SST plays a more important than ENSO in the AFM precipitation variation and the prediction skill is lower for the tropical Atlantic SST than the tropical Pacific SST.     

Prediction of primary climate variability modes at the Beijing Climate Center

Climate variability modes, usually known as primary climate phenomena, are well recognized as the most important predictability sources in subseasonal–interannual climate prediction. This paper begins by reviewing the research and development carried out, and the recent progress made, at the Beijing Climate Center (BCC) in predicting some primary climate variability modes. These include the El Niño–Southern Oscillation (ENSO), Madden–Julian Oscillation (MJO), and Arctic Oscillation (AO), on global scales, as well as the sea surface temperature (SST) modes in the Indian Ocean and North Atlantic, western Pacific subtropical high (WPSH), and the East Asian winter and summer monsoons (EAWM and EASM, respectively), on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system (CPPS) and completed a hindcast experiment for the period 1991–2014. The performance of the CPPS in predicting such climate variability modes is systematically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole (IOD) and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improvements in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC’s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.     

Interannual variability of summer monsoon precipitation over the Indochina Peninsula in association with ENSO

The interannual variability of summer monsoon precipitation (1979–2011) over the Indochina Peninsula (ICP) is characterized using the first empirical orthogonal function of 5-month total precipitation (May to September). The leading mode, with a monopole pattern, accounts for 30.6 % of the total variance. Dynamic composites and linear regression analysis indicate that the rainy season precipitation over the ICP is linked to El Niño–Southern Oscillation (ENSO) on interannual scales. The preceding winter [D(?1)JF(0)] negative sea surface temperature (SST) over the Niño-3.4 region is predominantly correlated with the rainy season precipitation over the ICP. Notably, the simultaneous correlation between remote SST anomalies in the Niño-3.4 region and the rainy season precipitation over the ICP is weak. The interannual variation of tropical cyclones modulated by ENSO is a significant contributing factor to the rainy season precipitation over the ICP. However, this relationship is not homogeneous over the ICP if ENSO is considered. Before removing the ENSO signal, enhanced precipitation is present over the northeastern part of the ICP and reduced precipitation appears in the western ICP, especially in coastal areas. In contrast, after removing ENSO, only a minor significant positive precipitation anomaly occurs over the northeastern part of the ICP and the negative anomaly appears particularly in the western and eastern coastal regions. The results obtained through the present study are useful for our understanding of circulation mechanisms and provide information for assessing the ability of regional and global climate models in simulating the climate of Southeast Asia.     

Modes of SST variability and the fluctuation of global mean temperature

Annually averaged global mean land air temperature and sea surface temperature (SST) combined, and global mean SST alone share similar fluctuations. We examine contributions by modes of SST variability in the global mean SST based on a new version (version 3) of global sea-ice and SST (GISST3). Besides a trend mode, the dominant modes are El Niño-Southern Oscillation (ENSO), interhemispheric oscillation, and North Pacific oscillation. Statistics over the period of 1880–1997 show that excluding a warming trend the fluctuation on interannual (IA) and decadal-interdecadal (DID) time scales is dominated by IA ENSO and DID ENSO-like variability. However, the contribution by IA ENSO cycles experiences significant fluctuations, and there appears to be strong modulations by ENSO-like variability on DID or longer time scales: during several decade-long periods, when DID ENSO-like variability raises the temperature in the equatorial eastern Pacific, the contribution by IA ENSO cycles weakens to an insignificant level. The latest example of such modulation is the period since about 1980; despite the exceptional strength of El Niño events, the contribution by IA ENSO cycles weakens, suggesting that the exceptional strength is a consequence of superposition of IA El Niño events, a warming phase of DID ENSO-like variability, and possibly an ENSO-like warming trend.     

GCM Hindcasts of SST Forced Climate Variability over Agriculturally Intensive Regions

The NASA/Goddard Institute for Space Studies (GISS) climatemodel is forced with globally observed sea-surfacetemperatures (SST) in five simulations, 1969–1991,with individual runs beginning from altered initialatmospheric conditions. The interannual variability ofmodeled anomalies of the Southern Oscillation Index,mid-tropospheric temperatures, 850 mb zonal winds andOutgoing Longwave Radiation over the tropical PacificOcean, which has the largest SST anomaly forcing, arestrongly correlated with observed trends which reflectENSO cycles. The model's rainfall variability overthree agriculturally intensive regions, two tropicaland one mid-latitude, is investigated in order toevaluate the potential usefulness of GCM predictionsfor agricultural planning. The correct sign ofZimbabwe seasonal precipitation anomalies was hindcastwithin a useful range of consensus only for selectseasons corresponding to extreme ENSO events for whichanomalous circulation patterns were ratherrealistically simulated. The correlation betweenhindcasts of Nordeste monthly precipitation andobservations increases with time smoothing, reaching0.64 for 5-month running means. Consensus betweenindividual runs is directly proportional to theabsolute value of Niño3 SST so that during ElNiño and La Niña years most simulations agreeon the sign of predicted Nordeste rainfall anomalies.We show that during selected seasons the uppertropospheric divergent circulation and near surfacemeridional displacements of the ITCZ are realisticallyrepresented by the ensemble mean of the simulations.This realistic simulation of both the synopticmechanisms and the resulting precipitation changesincreases confidence in the GCM's potential forseasonal climate prediction.     

Is the Indian Ocean SST variability a homogeneous diffusion process?

Whereas the predominance of El Niño Southern Oscillation (ENSO) mode in the tropical Pacific sea surface temperature (SST) variability is well established, no such consensus seems to have been reached by climate scientists regarding the Indian Ocean. While a number of researchers think that the Indian Ocean SST variability is dominated by an active dipolar-type mode of variability, similar to ENSO, others suggest that the variability is mostly passive and behaves like an autocorrelated noise. For example, it is suggested recently that the Indian Ocean SST variability is consistent with the null hypothesis of a homogeneous diffusion process. However, the existence of the basin-wide warming trend represents a deviation from a homogeneous diffusion process, which needs to be considered. An efficient way of detrending, based on differencing, is introduced and applied to the Hadley Centre ice and SST. The filtered SST anomalies over the basin (23.5N–29.5S, 30.5E–119.5E) are then analysed and found to be inconsistent with the null hypothesis on intraseasonal and interannual timescales. The same differencing method is then applied to the smaller tropical Indian Ocean domain. This smaller domain is also inconsistent with the null hypothesis on intraseasonal and interannual timescales. In particular, it is found that the leading mode of variability yields the Indian Ocean dipole, and departs significantly from the null hypothesis only in the autumn season.     

Role of the Indian Ocean sea surface temperature in shaping the natural variability in the flow of Nile River

A significant fraction of the inter-annual variability in the Nile River flow is shaped by El Niño Southern Oscillation (ENSO). Here, we investigate a similar role for the Indian Ocean (IO) sea surface temperature (SST) in shaping the inter-annual variability of the Nile River flow. Using observations of global SST distribution and river flow in addition to atmospheric general circulation model sensitivity experiments, we show that North and Middle IO SSTs play a significant intermediate role in the teleconnection between ENSO and the Nile flow. Applying partial coherency analyses, we demonstrate that the connection between North and Middle IO SSTs and Nile flow is strongly coupled to ENSO. During El Niño events, SST in the North and Middle IO increases in response to the warming in the Tropical Eastern Pacific Ocean and forces a Gill-type circulation with enhanced westerly low-level flow over East Africa and the Western IO. This anomalous low-level flow enhances the low-level flux of air and moisture away from the Upper Blue Nile (UBN) basin resulting in reduction of rainfall and river flow. SSTs in the South IO also play a significant role in shaping the variability of the Nile flow that is independent from ENSO. A warming over the South IO, generates a cyclonic flow in the boundary layer, which reduces the cross-equatorial meridional transport of air and moisture towards the UBN basin, favoring a reduction in rainfall and river flow. This independence between the roles of ENSO and South IO SSTs allows for development of new combined indices of SSTs to explain the inter-annual variability of the Nile flow. The proposed teleconnections have important implications regarding mechanisms that shape the regional impacts of climate change over the Nile basin.     

Impacts of large-scale teleconnections on climate variability over Southwest Asia

The atmospheric low frequency variability at a regional or global scale is represented by teleconnection. Using monthly dataset of the Climatic Research Unit (CRU) for the period 1971–2016, the impacts of four large-scale teleconnection patterns on the climate variability over Southwest Asia are investigated. The large-scale features include the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the East Atlantic (EA) teleconnection patterns, as well as western tropical Indian Ocean (WTIO) sea surface temperature anomaly index. Results indicate that ENSO and EA are the first leading modes that explain variation of Southwest Asian precipitation, with positive (negative) anomalies during El Niño (La Niña) and the negative (positive) phase of EA. Variation of Southwest Asian near-surface temperature is most strongly related to WTIO index, with above-average (below-average) temperature during the positive (negative) phase of WTIO index, although the negative (positive) phase of NAO also favours the above-average (below-average) temperature. On the other hand, temperature (precipitation) over Southwest Asia shows the least response to ENSO (WTIO). ENSO and EA individually explain 13 percent annual variance of precipitation, while WTIO index explains 36 percent annual variance of near-surface temperature over Southwest Asia. Analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis Interim (ERA-Interim) data indicated establishments of negative (positive) geopotential height anomalies in the middle troposphere over Southwest Asia during El Niño (La Niña) or the negative (positive) phase of NAO, EA and WTIO. The response of precipitation variability over Southwest Asia to NAO is opposite to that expected from the geopotential height anomalies, but the correlation between precipitation and NAO is not statistically significant. Due to predictability of large-scale teleconnections, results of this study are encouraging for improvement of the state-of-the-art seasonal prediction of the climate over Southwest Asia.     

An empirical model of decadal ENSO variability

This paper assesses potential predictability of decadal variations in the El Ni?o/Southern Oscillation (ENSO) characteristics by constructing and performing simulations using an empirical nonlinear stochastic model of an ENSO index. The model employs decomposition of global sea-surface temperature (SST) anomalies into the modes that maximize the ratio of interdecadal-to-subdecadal SST variance to define low-frequency predictors called the canonical variates (CVs). When the whole available SST time series is so processed, the leading canonical variate (CV-1) is found to be well correlated with the area-averaged SST time series which exhibits a non-uniform warming trend, while the next two (CV-2 and CV-3) describe secular variability arguably associated with a combination of Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) signals. The corresponding ENSO model that uses either all three (CVs 1–3) or only AMO/PDO-related (CVs 2 and 3) predictors captures well the observed autocorrelation function, probability density function, seasonal dependence of ENSO, and, most importantly, the observed interdecadal modulation of ENSO variance. The latter modulation, and its dependence on CVs, is shown to be inconsistent with the null hypothesis of random decadal ENSO variations simulated by multivariate linear inverse models. Cross-validated hindcasts of ENSO variance suggest a potential useful skill at decadal lead times. These findings thus argue that decadal modulations of ENSO variability may be predictable subject to our ability to forecast AMO/PDO-type climate modes; the latter forecasts may need to be based on simulations of dynamical models, rather than on a purely statistical scheme as in the present paper.     

La Plata basin precipitation variability in spring: role of remote SST forcing as simulated by GCM experiments

An ensemble of nine experiments with the same interannually varying sea surface temperature (SST), as boundary forcing, and different initial conditions is used to investigate the role of tropical oceans in modulating precipitation variability in the region of La Plata Basin (LPB). The results from the ensemble are compared with a twentieth-century experiment performed with a coupled ocean-atmosphere model, sharing the same atmospheric component. A rotated empirical orthogonal functions analysis of South America precipitation shows that the dominant mode of variability in spring is realistically captured in both experiments. Its principal component (RPC1) correlated with global SST and atmospheric fields identifies the pattern related to El Niño Southern Oscillation and its large-scale teleconnections. Overall the pattern is well simulated in the tropical southern Pacific Ocean, mainly in the ensemble, but it is absent or too weak in other oceanic areas. The coupled model experiment shows a more realistic correlation in the subtropical South Atlantic where air-sea interactions contribute to the relationship between LPB precipitation and SST. The correspondence between model and data is much improved when the composite analysis of SST and atmospheric fields is done over the ensemble members having an RPC1 in agreement with the observations: the improvement relies on avoiding climate noise by averaging only over members that are statistically similar. Furthermore, the result suggests the presence of a high level of uncertainty due to internal atmospheric variability. The analysis of some individual years selected from the model and data RPC1 comparison reveals interesting differences among rainy springs in LPB. For example, 1982, which corresponds to a strong El Niño year, represents a clean case with a distinct wave train propagating from the central Pacific and merging with another one from the eastern tropical south Indian Ocean. The year 2003 is an example of a rainy spring in LPB not directly driven by remote SST forcing. In this case the internal variability has a dominant role, as the model is not able to reproduce the correct local precipitation pattern.     

Interdecadal changes in the relationship between Southern China winter-spring precipitation and ENSO

Winter-spring precipitation in southern China tends to be higher (lower) than normal in El Niño (La Niña) years during 1953–1973. The relationship between the southern China winter-spring precipitation and El Niño-Southern Oscillation (ENSO) is weakened during 1974–1994. During 1953–1973, above-normal southern China rainfall corresponds to warmer sea surface temperature (SST) in the equatorial central Pacific. There are two anomalous vertical circulations with ascent over the equatorial central Pacific and ascent over southern China and a common branch of descent over the western North Pacific that is accompanied by an anomalous lower-level anticyclone. During 1974–1994, above-normal southern China rainfall corresponds to warmer SST in eastern South Indian Ocean and cooler SST in western South Indian Ocean. Two anomalous vertical circulations act to link southern China rainfall and eastern South Indian Ocean SST anomalies, with ascent over eastern South Indian Ocean and southern China and a common branch of descent over the western North Pacific. Present analysis shows that South Indian Ocean SST anomalies can contribute to southern China winter-spring precipitation variability independently. The observed change in the relationship between southern China winter-spring rainfall and ENSO is likely related to the increased SST variability in eastern South Indian Ocean and the modulation of the Pacific decadal oscillation.