Decadal climate variability in the Mediterranean region: roles of large-scale forcings and regional processes

We analyze decadal climate variability in the Mediterranean region using observational datasets over the period 1850–2009 and a regional climate model simulation for the period 1960–2000, focusing in particular on the winter (DJF) and summer (JJA) seasons. Our results show that decadal variability associated with the winter and summer manifestations of the North Atlantic Oscillation (NAO and SNAO respectively) and the Atlantic Multidecadal Oscillation (AMO) significantly contribute to decadal climate anomalies over the Mediterranean region during these seasons. Over 30% of decadal variance in DJF and JJA precipitation in parts of the Mediterranean region can be explained by NAO and SNAO variability respectively. During JJA, the AMO explains over 30% of regional surface air temperature anomalies and Mediterranean Sea surface temperature anomalies, with significant influence also in the transition seasons. In DJF, only Mediterranean SST still significantly correlates with the AMO while regional surface air temperature does not. Also, there is no significant NAO influence on decadal Mediterranean surface air temperature anomalies during this season. A simulation with the PROTHEUS regional ocean–atmosphere coupled model is utilized to investigate processes determining regional decadal changes during the 1960–2000 period, specifically the wetter and cooler 1971–1985 conditions versus the drier and warmer 1986–2000 conditions. The simulation successfully captures the essence of observed decadal changes. Model set-up suggests that AMO variability is transmitted to the Mediterranean/European region and the Mediterranean Sea via atmospheric processes. Regional feedbacks involving cloud cover and soil moisture changes also appear to contribute to observed changes. If confirmed, the linkage between Mediterranean temperatures and the AMO may imply a certain degree of regional decadal climate predictability. The AMO and other decadal influences outlined here should be considered along with those from long-term increases in greenhouse gas forcings when making regional climate out-looks for the Mediterranean 10–20?years out.     

CMIP5模式对AMO与PDO模拟评估及未来预估

利用1880-2009年海表温度(Sea Surface Temperature,SST)观测资料以及耦合模式比较计划第五阶段(Coupled Model Intercomparison Project phase 5,CMIP5)中4种情景(piControl、historical、RCP2.6、RCP4.5)下的模...     

Decadal scale oscillations and trend in the Indian monsoon rainfall

The emerging need for extended climate prediction requires a consideration of the relative roles of climate change and low-frequency natural variability on decadal scale. Addressing this issue, this study has shown that the variability of the Indian monsoon rainfall (IMR) consists of three decadal scale oscillations and a nonlinear trend during 1901–2004. The space–time structures of the decadal oscillations are described. The IMR decadal oscillations are shown to be associated with Atlantic Multidecadal Oscillation (AMO), Atlantic tripole oscillation and Pacific Decadal Oscillation (PDO). The sea surface temperatures (SSTs) of the North Pacific and North Atlantic Oceans are also resolved as nonlinear decadal oscillations. The SST AMO mode has high positive correlation with IMR while the SST tripole mode and SST PDO have negative correlation. The trend in IMR increases during the first half of the period and decreases during the second half. The IMR trend is modified when combined with the three decadal oscillations.     

长江梅雨的长期变率与海洋的关系及其可预报性研究

采用最新发布的梅雨国家标准资料,以长江区域梅雨为代表,在分析区域梅雨的多时间尺度变化特征的基础上,从海洋外强迫影响因子角度探讨了梅雨的可预报性来源,进一步综合海洋背景变率和预测模型回报试验讨论梅雨异常的可预报性。结果表明:（1）长江梅雨呈现周期为3-4、6-8、12-16、32、64 a的多时间尺度变化分量和长期减少趋势。其中,3-4 a准周期变化是梅雨异常变化的主要分量。梅雨的干湿位相转变受12-16 a的准周期变化调制,极端涝年易出现在12-16 a准周期变化湿位相和3-4 a变化分量峰值位相叠加的情况。（2）长江梅雨的各准周期变化分量有不同的海洋外强迫背景,是梅雨可预报性的重要来源。与时间尺度较短的年际变化分量相关联的海温关键区主要分布于热带,而与时间尺度较长的年代际或多年代际变化分量相联系的海温关键区则来自中高纬度。3-4 a准周期变化分量的海洋外强迫强信号随季节变化由前冬的ENSO（厄尔尼诺-南方涛动）转为春末夏初的印度洋偶极子（IOD）。6-8和12-16 a年准周期变化分量的海洋强迫关键区主要位于太平洋。准32和准64 a周期振荡则受北太平洋多年代际变化（PDO）和北大西洋多年代际变化（AMO）的共同影响。梅雨的长期变化趋势则与全球变暖背景及以PDO为代表的年代际海洋外强迫因子相联系。（3）尽管梅雨异常与ENSO的正相关关系呈现减弱趋势,但20世纪70年代以后的梅雨异常年际变化分量的可预报性有所增大。（4）将梅雨各变化分量作为预测对象分别建模,进一步构建梅雨异常预测统计模型。采用该模型对近5年梅雨预测进行独立样本检验,有较好的回报效果,验证了梅雨异常年际分量可预报性的稳定性以及基于多时间尺度分离建立梅雨预测模型的优越性。      

Influence of the Atlantic Multidecadal Oscillation on the winter climate of East China

The Atlantic Multidecadal Oscillation （AMO）, the multidecadal variation of North Atlantic sea surface temperature （SST）, exhibits an oscillation with a period of 65-80 years and an amplitude of 0.4℃. Observational composite analyses reveal that the warm phase AMO is linked to warmer winters in East China, with enhanced precipitation in the north of this region and reduced precipitation in the south, on multidecadal time scales. The pattern is reversed during the cold phase AMO. Whether the AMO acts as a forcing of the multidecadal winter climate of East China is explored by investigating the atmospheric response to warm AMO SST anomalies in a large ensemble of atmospheric general circulation model （AGCM） experiments. The results from three AGCMs are consistent and suggest that the AMO warmth favors warmer winters in East China. This influence is realized through inducing negative surface air pressure anomalies in the hemispheric-wide domain extending from the midlatitude North Atlantic to midlatitude Eurasia. These negative surface anomalies favor the weakening of the Mongolian Cold High, and thus induce a weaker East Asian Winter Monsoon.     

CMIP5多模式对东亚地区地面气温年际变率的回报研究

对CMIP5全球气候模式中年代际回报试验的气温资料及其简单集合平均(Multi-model ensemble mean,EMN)和贝叶斯模式平均的结果(Bayesian Model Averaging,BMA)进行经验正交函数(Empirical Orthogonal Function,EOF)分解和Morlet小波分析,检验评估各个模式及其EMN和BMA对东亚地面气温的方差、气温时空分布特征及周期变化的回报能力。结果表明,10个模式、EMN、BMA都能很好地回报出1981—2010年东亚地面气温的方差分布,其中BMA回报效果最好。EOF分析表明,BMA能较好地回报出东亚地面气温第一模态的时空分布。MIROC5能较好地回报出第二模态的趋势变化,但却不能回报出气温的年际变率。绝大多数模式和EMN、BMA虽然能回报出东亚地面气温的变化趋势,但是对气温年际变率的回报仍然是比较困难的。CMCC-CM对气温变化主模态的3~5 a的周期变化特征回报效果最好,和NCEP资料的结果最为接近。     

欧洲多个耦合气候模式对东亚冬季气候的预测性能研究

在短期气候预测方法中,多模式集合预测作为一种实用方法得到了广泛的研究。利用DEMETER多模式集合预测系统1980—2001年的回报试验,研究了欧洲7个耦合模式对东亚地区(0°—60°N,70°—140°E)冬季大气环流和气候异常的预测效能。研究的气候要素是冬季500 hPa高度场、850 hPa风场、表面气温场和降水场。集合平均(EM)是最基本的多模式集合构建方法。为了进一步订正模式预测的误差,基于经验正交函数分解进行订正,产生“合成数据集”,并利用该数据集进行合成集合平均或合成超级集合(SEM/SSE)。研究表明,东亚地区冬季气候异常的模式预测效能热带高于中高纬度地区,海洋高于内陆。多模式集合平均和合成集合平均或合成超级集合均从整体上对东亚地区冬季气候异常的预测效能有一定程度的提高,体现了其相对于7个单一模式的优势。两类不同的多模式集合方法对预测结果也有一定的影响,其中,合成集合平均或合成超级集合对冬季500 hPa高度场、850 hPa风场和降水场异常的预测效能优于集合平均;但是对于冬季表面气温场异常的预测,集合平均优于合成集合平均或合成超级集合。     

Decadal potential predictability of twenty-first century climate

Decadal prediction of the coupled climate system is potentially possible given enough information and knowledge. Predictability will reside in both externally forced and in long timescale internally generated variability. The ??potential predictability?? investigated here is characterized by the fraction of the total variability accounted for by these two components in the presence of short-timescale unpredictable ??noise?? variability. Potential predictability is not a classical measure of predictability nor a measure of forecast skill but it does identify regions where long timescale variability is an appreciable fraction of the total and hence where prediction on these scale may be possible. A multi-model estimate of the potential predictability variance fraction (ppvf) as it evolves through the first part of the twenty-first century is obtained using simulation data from the CMIP3 archive. Two estimates of potential predictability are used which depend on the treatment of the forced component. The multi-decadal estimate considers the magnitude of the forced component as the change from the beginning of the century and so becomes largely a measure of climate change as the century progresses. The next-decade estimate considers the change in the forced component from the past decade and so is more pertinent to an actual forecast for the next decade. Long timescale internally generated variability provides additional potential predictability beyond that of the forced component. The ppvf may be expressed in terms of a signal-to-noise ratio and takes on values between 0 and 1. The largest values of the ppvf for temperature are found over tropical and mid-latitude oceans, with the exception of the equatorial Pacific, and some but not all tropical land areas. Overall the potential predictability for temperature generally declines with latitude and is relatively low over mid- to high-latitude land. Potential predictability for precipitation is generally low and due almost entirely to the forced component and then mainly at high latitudes. To the extent that the multi-model ppvf reflects both the behaviour of the actual climate system and the possibility of decadal prediction, the results give some indication as to where and to what extent decadal forecasts might be possible.     

Opposing Trends of Winter Cold Extremes over Eastern Eurasia and North America under Recent Arctic Warming

Under recent Arctic warming, boreal winters have witnessed severe cold surges over both Eurasia and North America,bringing about serious social and economic impacts. Here, we investigated the changes in daily surface air temperature(SAT) variability during the rapid Arctic warming period of 1988/89–2015/16, and found the daily SAT variance, mainly contributed by the sub-seasonal component, shows an increasing and decreasing trend over eastern Eurasia and North America, respectively. Increasing c...     

Possible Origins of the Western Pacific Warm Pool Decadal Variability

In this study,the impacts of the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) on the western Pacific warm pool (WPWP) were investigated.Our results show that the WPWP is linked with the PDO and the AMO at multiple time scales.On the seasonal time scales,the WPWP and the PDO/AMO reinforce each other,while at decadal time scales the forcing roles of the PDO and the AMO dominate.Notably,a positive PDO tends to enlarge the WPWP at both seasonal and decadal time scales,while a positive AMO tends to reduce the WPWP at decadal time scales.Furthermore,the decadal variability of the WPWP can be well predicted based on the PDO and AMO.     

A Possible Approach for Decadal Prediction of the PDO

The Pacific Decadal Oscillation(PDO) is a leading mode of decadal sea surface temperature variability in the North Pacific. Skillful PDO prediction can be beneficial in many aspects because of its global and regional impacts.However, current climate models cannot provide satisfied decadal prediction of the PDO and related decadal variability of sea surface temperature. In this study, we propose a new approach, i.e., the increment method, to predicting the PDO. A series of validations demonstrate that the increment method is effective in improving decadal prediction of PDO and it can well capture the phase change of PDO with high accuracy. The prediction processes include three steps. First, a five-year smoothing is performed; second, effective preceding predictors for PDO are selected, with all predictors and predictands in the form of a three-year decadal increment(DI); third, the prediction model is set up for PDO three-year decadal increment(DI_PDO), and PDO prediction can be obtained by adding the predicted DI_PDO to the observed PDO three years ago. This new method can also be applied for decadal climate prediction of other modes(e.g., Atlantic multidecadal oscillation) and predictands(e.g., sea surface temperature).     

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.     

太平洋年代际振荡的年代际预测方法

太平洋年代际振荡(PDO)是北太平洋海表温度年代际变率的主模态。由于太平洋年代际振荡对区域乃至全球气候的显著影响,其合理的预测结果可以带来多方面收益。然而,针对太平洋年代际振荡及其有关的海表温度的年代际预测,目前气候模式的预测水平还十分有限,因此,提出了一个新的增量方法。一系列的验证结果表明,增量方法可以有效预测太平洋年代际振荡,其中包括成功预测出其振荡的年代际转折。增量方法的预测过程主要包括3个步骤:(1)采用5 a滑动平均得到太平洋年代际振荡的年代际变率;(2)利用3 a增量形式的预测因子构建预测模型,预测3 a增量的太平洋年代际振荡(DI_PDO);(3)将预测得到的DI_PDO加上3 a前的观测PDO,得到最后预测的PDO。增量方法亦可以应用到气候系统年代际内部变率的其他模态(如:北大西洋年代际振荡)和其他气候变量的年代际预测(如:海表温度)。     

Daily atmospheric variability in the South American monsoon system

The space–time structure of the daily atmospheric variability in the South American monsoon system has been studied using multichannel singular spectrum analysis of daily outgoing longwave radiation. The three leading eigenmodes are found to have low-frequency variability while four other modes form higher frequency oscillations. The first mode has the same time variability as that of El Nino-Southern Oscillation (ENSO) and exhibits strong correlation with the Pacific sea surface temperature (SST). The second mode varies on a decadal time scale with significant correlation with the Atlantic SST suggesting an association with the Atlantic multidecadal oscillation (AMO). The third mode also has decadal variability but shows an association with the SST of the Pacific decadal oscillation (PDO). The fourth and fifth modes describe an oscillation that has a period of about 165 days and is associated with the North Atlantic oscillation (NAO). The sixth and seventh modes describe an intraseasonal oscillation with a period of 52 days which shows strong relation with the Madden-Julian oscillation. There exists an important difference in the variability of convection between Amazon River Basin (ARB) and central-east South America (CESA). Both regions have similar variations due to ENSO though with higher magnitude in ARB. The AMO-related mode has almost identical variations in the two regions, whereas the PDO-related mode has opposite variations. The interseasonal NAO-related mode also has variations of opposite sign with comparable magnitudes in the two regions. The intraseasonal variability over the CESA is robust while it is very weak over the ARB region. The relative contributions from the low-frequency modes mainly determine the interannual variability of the seasonal mean monsoon although the interseasonal oscillation may contribute in a subtle way during certain years. The intraseasonal variability does not seem to influence the interannual variability in either region.     

Decadal predictability of the Atlantic meridional overturning circulation and climate in the IPSL-CM5A-LR model

This study explores the decadal potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) as represented in the IPSL-CM5A-LR model, along with the predictability of associated oceanic and atmospheric fields. Using a 1000-year control run, we analyze the prognostic potential predictability (PPP) of the AMOC through ensembles of simulations with perturbed initial conditions. Based on a measure of the ensemble spread, the modelled AMOC has an average predictive skill of 8 years, with some degree of dependence on the AMOC initial state. Diagnostic potential predictability of surface temperature and precipitation is also identified in the control run and compared to the PPP. Both approaches clearly bring out the same regions exhibiting the highest predictive skill. Generally, surface temperature has the highest skill up to 2 decades in the far North Atlantic ocean. There are also weak signals over a few oceanic areas in the tropics and subtropics. Predictability over land is restricted to the coastal areas bordering oceanic predictable regions. Potential predictability at interannual and longer timescales is largely absent for precipitation in spite of weak signals identified mainly in the Nordic Seas. Regions of weak signals show some dependence on AMOC initial state. All the identified regions are closely linked to decadal AMOC fluctuations suggesting that the potential predictability of climate arises from the mechanisms controlling these fluctuations. Evidence for dependence on AMOC initial state also suggests that studying skills from case studies may prove more useful to understand predictability mechanisms than computing average skill from numerous start dates.     

Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part I. The leading forced mode of atmospheric circulation

Using observations and 1-month lead hindcast data from six coupled atmosphere–ocean climate models, this study investigates the interdecadal change in the leading maximum covariance analysis mode (MCA1) of atmospheric circulation in response to the changes in the El Niño and Southern Oscillation (ENSO) occurred around late 1970s. We focus on boreal winter climate variability and predictability over the North Pacific–North American (NPNA) region using December–January–February prediction initiated from November 1st in the period of 1960–1980 (P1) and 1981–2001 (P2). Observed analysis reveals that ENSO variability, the related tropical convective activity, and thus the MCA1 are considerably enhanced from P1 to P2. As a result, surface climate anomalies over the NPNA are more significantly correlated with the MCA1 in P2 than P1, particularly over North America. The six coupled models and their multi-model ensemble not only are capable of capturing the interdecadal change of the MCA1 and its relationship with surface air temperature and precipitation over the NPNA regions but also have significantly higher forecast skills for the MCA1 and the surface climate anomalies in P2 than P1. However, models have systematic biases in the spatial distribution of the MCA1. It is demonstrated that the interdecadal change in the MCA1 should contribute to the improved forecast skill of the NPNA climate during recent epoch.     

北大西洋地区气候准20年周期的观测和模拟分析

北大西洋地区除了存在约70 a周期的AMO（Atlantic Multidecadal Oscillation,北大西洋年代际振荡）之外,历史长期气候记录中英格兰温度（Central England Temperature,CET）与格陵兰冰芯净雪累计率还存在显著的20 a周期波动。本研究利用CCSM4（Community Climate System Model version 4）耦合模式工业革命前控制试验（piControl）结果中的海表面温度（Sea Surface Temperature,SST）,通过10～50 a带通滤波与扩展经验正交函数（Extended Empirical Orthogonal Function,EEOF）分解,得到在北大西洋副极地海区存在准20 a振荡的逆时针旋转模态。此周期与其临近地区的CET、格陵兰冰芯净雪累计率的准20 a振荡周期相吻合,说明这种北大西洋副极地海区准20 a振荡的海洋模态与其临近地区的大气准20 a振荡之间可能存在相应的联系。进一步利用CAM4（the Community Atmosphere Model version4）大气模式,以北大西洋副极地海区准20 a振荡SST旋转模态为强迫场进行敏感性试验,进一步验证了这种联系。     

The relative influence of soil moisture and SST in climate predictability explored within ensembles of AMIP type experiments

Three ensembles of AMIP-type simulations using the Arpege-climat coupled land–atmosphere model have been designed to assess the relative influence of SST and soil moisture (SM) on climate variability and predictability. The study takes advantage of the GSWP2 land surface reanalysis covering the 1986–1995 period. The GSWP2 forcings have been used to derive a global SM climatology that is fully consistent with the model used in this study. One ensemble of ten simulations has been forced by climatological SST and the simulated SM is relaxed toward the GSWP2 reanalysis. Another ensemble has been forced by observed SST and SM is evolving freely. The last ensemble combines the observed SST forcing and the relaxation toward GSWP2. Two complementary aspects of the predictability have been explored, the potential predictability (analysis of variance) and the effective predictability (skill score). An analysis of variance has revealed the effects of the SST and SM boundary forcings on the variability and potential predictability of near-surface temperature, precipitation and surface evaporation. While in the tropics SST anomalies clearly maintain a potentially predictable variability throughout the annual cycle, in the mid-latitudes the SST forced variability is only dominant in winter and SM plays a leading role in summer. In a similar fashion, the annual cycle of the hindcast skill (evaluated as the anomalous correlation coefficient of the three ensemble means with respect to the “observations”) indicates that the SST forcing is the dominant contributor over the tropical continents and in the winter mid-latitudes but that SM is supporting a significant part of the skill in the summer mid-latitudes. Focusing on boreal summer, we have then investigated different aspects of the SM and SST contribution to climate variations in terms of spatial distribution and time-evolution. Our experiments suggest that SM is potentially an additional source of climate predictability. A realistic initialization of SM and a proper representation of the land–atmosphere feedbacks seem necessary to improve state-of-the-art dynamical seasonal predictions, but will be actually efficient only in the areas where SM anomalies are themselves predictable at the monthly to seasonal timescale (since remote effects of SM are probably much more limited than SST teleconnections).     

Decadal prediction skill in a multi-model ensemble

Decadal climate predictions may have skill due to predictable components in boundary conditions (mainly greenhouse gas concentrations but also tropospheric and stratospheric aerosol distributions) and initial conditions (mainly the ocean state). We investigate the skill of temperature and precipitation hindcasts from a multi-model ensemble of four climate forecast systems based on coupled ocean-atmosphere models. Regional variations in skill with and without trend are compared with similarly analysed uninitialised experiments to separate the trend due to monotonically increasing forcings from fluctuations around the trend due to the ocean initial state and aerosol forcings. In temperature most of the skill in both multi-model ensembles comes from the externally forced trends. The rise of the global mean temperature is represented well in the initialised hindcasts, but variations around the trend show little skill beyond the first year due to the absence of volcanic aerosols in the hindcasts and the unpredictability of ENSO. The models have non-trivial skill in hindcasts of North Atlantic sea surface temperature beyond the trend. This skill is highest in the northern North Atlantic in initialised experiments and in the subtropical North Atlantic in uninitialised simulations. A similar result is found in the Pacific Ocean, although the signal is less clear. The uninitialised simulations have good skill beyond the trend in the western North Pacific. The initialised experiments show some skill in the decadal ENSO region in the eastern Pacific, in agreement with previous studies. However, the results in this study are not statistically significant (p?≈?0.1) by themselves. The initialised models also show some skill in forecasting 4-year mean Sahel rainfall at lead times of 1 and 5?years, in agreement with the observed teleconnection from the Atlantic Ocean. Again, the skill is not statistically significant (p?≈?0.2). Furthermore, uninitialised simulations that include volcanic aerosols have similar skill. It is therefore still an open question whether initialisation improves predictions of Sahel rainfall. We conclude that the main source of skill in forecasting temperature is the trend forced by rising greenhouse gas concentrations. The ocean initial state contributes to skill in some regions, but variations in boundary forcings such as aerosols are as important in decadal forecasting.     

Twentieth century north atlantic climate change. Part I: assessing determinism

Boreal winter North Atlantic climate change since 1950 is well described by a trend in the leading spatial structure of variability, known as the North Atlantic Oscillation (NAO). Through diagnoses of ensembles of atmospheric general circulation model (AGCM) experiments, we demonstrate that this climate change is a response to the temporal history of sea surface temperatures (SSTs). Specifically, 58 of 67 multi-model ensemble members (87%), forced with observed global SSTs since 1950, simulate a positive trend in a winter index of the NAO, and the spatial pattern of the multi-model ensemble mean trend agrees with that observed. An ensemble of AGCM simulations with only tropical SST forcing further suggests that variations in these SSTs are of primary importance. The probability distribution function (PDF) of 50-year NAO index trends from the forced simulations are, moreover, appreciably different from the PDF of a control simulation with no interannual SST variability, although chaotic atmospheric variations are shown to yield substantial 50-year trends. Our results thus advance the view that the observed linear trend in the winter NAO index is a combination of a strong tropically forced signal and an appreciable noise component of the same phase. The changes in tropical rainfall of greatest relevance include increased rainfall over the equatorial Indian Ocean, a change that has likely occurred in nature and is physically consistent with the observed, significant warming trend of the underlying sea surface.