On the mechanism of the seasonal variability of SST in the tropical Indian Ocean

A general form of an equation that "explicitly" diagnoses SST change is derived. All other equations in wide use are its special case. Combining with the data from an ocean general circulation model (MOM2) with an integration of 10 years (1987-1996), the relative importances of various processes that determine seasonal variations of SST in the tropical Indian Ocean are compared mainly for January, April, July and October. The main results are as follows. (1) The net surface heat flux is the most important factor affecting SST over the Arabian Sea, the Bay of Bengal and the region south of the equator in January; in April, its influence covers almost the whole region studied; whereas in July and October, this term shows significance only in the regions south of 10°S and north of the equator, respectively. (2) The horizontal advection dominates in the East African-Arabian coast and the region around the equator in January and July; in October, the region is located south of 10°S. (3) The entrainment is s     

Assessment of probability multimodel seasonal forecast based on the APCC model data

The probability multimodel forecast system based on the Asia-Pacific Economic Cooperation Climate Center (APCC) model data is verified. The winter and summer seasonal mean fields T ₈₅₀ and precipitation seasonal totals are estimated. To combine the models into a multimodel ensemble, the probability forecast is calculated for each of single models first, and then these forecasts are combined using the total probability formula. It is shown that the multimodel forecast is considerably more skilful than the single-model forecasts. The forecast quality is higher in the tropics compared to the mid- and high latitudes. The multimodel ensemble temperature forecasts outperform the random and climate forecasts for Northern Eurasia in the above- and below-normal categories. Precipitation forecast is less successful. For winter, the combination of single-model ensembles provides the precipitation forecast skill exceeding that of the random forecast for both Northern Eurasia and European Russia.     

Caribbean Sea rainfall variability during the rainy season and relationship to the equatorial Pacific and tropical Atlantic SST

The present study investigates the Caribbean Sea rainfall variability during the early and late rainy seasons and its association with sea surface temperature (SST) and air?Csea interaction based on observational estimates, the NCEP Climate Forecast System (CFS) and Global Forecast System (GFS) simulations, and the CFS retrospective forecasts. Analysis of the observational estimates indicates that air?Csea interaction is important over the Caribbean Sea, whereas the atmospheric forcing of SST dominates over the Gulf of Mexico. The CFS simulation captures the basic elements of this observed air?Csea relationship. The GFS simulation produces spurious SST forcing of the atmosphere over the Gulf of Mexico largely due to prescribing SST. The CFS forecasts capture the air?Csea relationship in the late rainy season (August?COctober), but cannot reproduce the SST forcing of atmosphere over the Caribbean Sea in the early rainy season (May?CJuly). An empirical orthogonal function (EOF) analysis indicates that the leading modes of percent anomalies of the rainy season precipitation have the largest loading in the southern Caribbean Sea in observations. The model simulations and forecasts skillfully reproduce the spatial pattern, but not the temporal evolution. The Caribbean Sea rainfall variability in the early rainy season is mainly due to the tropical North Atlantic (TNA) SST anomalies in observations, is contributed by both the TNA and eastern equatorial Pacific (EEP) SST anomalies in the CFS simulation, and has an overly large impact from the EEP SST anomalies in the GFS simulation and the CFS forecasts. The observed Caribbean Sea rainfall variability in the late rainy season has a leading impact from the EEP SST anomalies, with a secondary contribution from the TNA SST anomalies. In comparison, the model simulations and forecasts overestimate the impacts of the EEP SST anomalies due to an earlier development and longer duration of the El Ni?o-Southern Oscillation in the CFS compared to observations.     

Spatio-temporal variability of seasonal rainfall in western equatorial Africa

This study reveals homogeneous sub-regions over the poorly studied area of western equatorial Africa (10S?C7N and 7E?C30E). Monthly totals of 141 stations covering the period 1955?C1984 are used. The stations are grouped based on the similarity of their interannual rainfall variability. In addition to annual totals, four different seasons are examined separately for regionalization, an approach that has lacked in previous studies. The four 3-month seasons are defined as follows: January?CFebruary?CMarch (JFM), April?CMay?CJune (AMJ), July?CAugust?CSeptember (JAS), and October?CNovember?CDecember (OND). Two different algorithms are applied and compared: the rotated principal component analysis (RPCA) in conjunction with Ward's method, and the RPCA in conjunction with k-means method. The principal components that explain about 65% of total variance are retained and then varimax rotated. The corresponding scores are utilized as input for cluster analysis. Using Ward's method, five sub-regions are recognized for AMJ, JAS and OND and 4 sub-regions for JFM and annual data. The regions are geographically well distributed over the area and consist of roughly the same number of stations. The F-test is used to evaluate the homogeneity of each sub-region. The results show that all sub-regions are strongly homogeneous. Assuming the same number of clusters, the k-means method provides comparable spatial patterns with those of Ward's method. However, there are some differences, which are more evident in JAS and OND. Like Ward's method, the values of F-ratio for the k-means algorithm also confirm the homogeneity of all seasons/sub-regions. The interannual variability of rainfall for each season/sub-region is also provided and compared.     

Weakened SST variability in the tropical Atlantic Ocean since 2000

A prominent weakening in equatorial Atlantic sea surface temperature (SST) variability, occurring around the year 2000, is investigated by means of observations, reanalysis products and the linear recharge oscillator (ReOsc) model. Compared to the time period 1982–1999, during 2000–2017 the May–June–July SST variability in the eastern equatorial Atlantic has decreased by more than 30%. Coupled air–sea feedbacks, namely the positive Bjerknes feedback and the negative net heat flux damping are important drivers for the equatorial Atlantic interannual SST variability. We find that the Bjerknes feedback weakened after 2000 while the net heat flux damping increased. The weakening of the Bjerknes feedback does not appear to be fully explainable by changes in the mean state of the tropical Atlantic. The increased net heat flux damping is related to an enhanced response of the latent heat flux to the SST anomalies (SSTa). Strengthened trade winds as well as warmer SSTs are suggested to increase the air–sea specific humidity difference and hence, enhancing the latent heat flux response to SSTa. A combined effect of those two processes is proposed to be responsible for the weakened SST variability in the eastern equatorial Atlantic. The ReOsc model supports the link between reduced SST variability, weaker Bjerknes feedback and stronger net heat flux damping.     

Correction to: New insights into the rainfall variability in the tropical Andes on seasonal and interannual time scales

Climate Dynamics - The original version of the article contained errors in Fig.     

The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST

The impact of realistic atmospheric initialisation on the seasonal prediction of tropical Pacific sea surface temperatures is explored with the Predictive Ocean–Atmosphere Model for Australia (POAMA) dynamical seasonal forecast system. Previous versions of POAMA used data from an Atmospheric Model Intercomparison Project (AMIP)-style simulation to initialise the atmosphere for the hindcast simulations. The initial conditions for the hindcasts did not, therefore, capture the true intra-seasonal atmospheric state. The most recent version of POAMA has a new Atmosphere and Land Initialisation scheme (ALI), which captures the observed intra-seasonal atmospheric state. We present the ALI scheme and then compare the forecast skill of two hindcast datasets, one with AMIP-type initialisation and one with realistic initial conditions from ALI, focussing on the prediction of El Niño. For eastern Pacific (Niño3) sea surface temperature anomalies (SSTAs), both experiments beat persistence and have useful SSTA prediction skill (anomaly correlations above 0.6) at all lead times (forecasts are 9 months duration). However, the experiment with realistic atmospheric initial conditions from ALI is an improvement over the AMIP-type initialisation experiment out to about 6 months lead time. The improvements in skill are related to improved initial atmospheric anomalies rather than an improved initial mean state (the forecast drift is worse in the ALI hindcast dataset). Since we are dealing with a coupled system, initial atmospheric errors (or differences between experiments) are amplified though coupled processes which can then lead to long lasting errors (or differences).     

Application of a serial extended forecast experiment using the ECMWF model to interpret the predictive skill of tropical intraseasonal variability

The extended-range forecast skill of the ECMWF operational forecast model is evaluated during tropical intraseasonal oscillation (ISO) events in the Indo-West Pacific warm pool. The experiment consists of ensemble extended serial forecasts including winter and summer ISO cases. The forecasts are compared with the ERA-40 analyses. The analysis focuses on understanding the origin of forecast errors by studying the vertical structure of relevant dynamical and moist convective features associated with the ISO. The useful forecast time scale for circulation anomalies is in average 13 days during winter compared to 7–8 days during summer. The forecast skill is not stationary and presents evidence of a flow-dependent nature, with states of the coupled system corresponding to long-lived convective envelopes associated with the ISO for which the skill is always low regardless of the starting date of the forecast. The model is not able to forecast skillfully the generation of specific humidity anomalies and results indicate that the convective processes in the model are associated with the erosion of the ISO forecast skill in the model. Circulation-associated anomalies are forecast better than moist convective associated anomalies. The model tends to generate a more stable atmosphere, limiting the model’s capability to reproduce deep convective events, resulting in smaller humidity and circulation anomalies in the forecasts compared to those in ERA-40.     

Relationship between South China Sea precipitation variability and tropical Indo-Pacific SST anomalies in IPCC CMIP5 models during spring-to-summer transition

The present study evaluates the precipitation variability over the South China Sea (SCS) and its relationship to tropical Indo-Pacific SST anomalies during spring-to-summer transition (April-May-June, AMJ) simulated by 23 Intergovernmental Panel on Climate Change Coupled Model Intercomparison Project Phase 5 coupled models. Most of the models have the capacity to capture the AMJ precipitation variability in the SCS. The precipitation and SST anomaly (SSTA) distribution in the SCS, tropical Pacific Ocean (TPO), and tropical Indian Ocean (TIO) domains is evaluated based on the pattern correlation coefficients between model simulations and observations. The analysis leads to several points of note. First, the performance of the SCS precipitation anomaly pattern in AMJ is model dependent. Second, the SSTA pattern in the TPO and TIO is important for capturing the AMJ SCS precipitation variability. Third, a realistic simulation of the western equatorial Pacific (WEP) and local SST impacts is necessary for reproducing the AMJ SCS precipitation variability in some models. Fourth, the overly strong WEP SST impacts may disrupt the relationship between the SCS precipitation and the TPO-TIO SST. Further work remains to be conducted to unravel the specific reasons for the discrepancies between models and observations in various aspects.     

Interdecadal change in the relationship of southern China summer rainfall with tropical Indo-Pacific SST

The present study investigates the interdecadal change in the relationship between southern China (SC) summer rainfall and tropical Indo-Pacific sea surface temperature (SST). It is found that the pattern of tropical Indo-Pacific SST anomalies associated with SC summer rainfall variability tends to be opposite between the 1950–1960s and the 1980-1990s. Above-normal SC rainfall corresponds to warmer SST in the tropical southeastern Indian Ocean (SEIO) and cooler SST in the equatorial central Pacific (ECP) during the 1950–1960s but opposite SST anomalies in these regions during the 1980–1990s. A pronounced difference is also found in anomalous atmospheric circulation linking SEIO SST and SC rainfall between the two periods. In the 1950–1960s, two anomalous vertical circulations are present between ascent over SEIO and ascent over SC, with a common branch of descent over the South China Sea that is accompanied by an anomalous low-level anticyclone. In the 1980–1990s, however, a single anomalous vertical circulation directly connects ascent over SC to descent over SEIO. The change in the rainfall–SST relationship is likely related to a change in the magnitude of SEIO SST forcing and a change in the atmospheric response to the SST forcing due to different mean states. A larger SEIO SST forcing coupled with a stronger and more extensive western North Pacific subtropical high in recent decades induce circulation anomalies reaching higher latitudes, influencing SC directly. Present analysis shows that the SEIO and ECP SST anomalies can contribute to SC summer rainfall variability both independently and in concert. In comparison, there are more cases of concerted contributions due to the co-variability between the Indian and Pacific Ocean SSTs.     

春季北太平洋风暴轴的年际与年代际变化特征及其与太平洋海温异常的关系

利用20世纪大气再分析资料和欧洲中心海温资料研究了春季西北太平洋风暴轴的年（代）际变化特征以及在不同年代际背景下风暴轴与太平洋海温关系的转变。结果表明,春季西北太平洋风暴轴主要存在两种空间变化模态,即反映其强度变化的第1模态和反映其南北位置变化的第2模态。年代际及以上时间尺度上,风暴轴强度、位置与太平洋海温的关系主要表现为大气对海洋的强迫作用。在不同年代际背景下,风暴轴与太平洋海温的关系则存在明显的年代际转变：1977年以后,风暴轴强度与太平洋海温的关系主要表现为大气对海洋的强迫作用,而在1977年之前则主要表现为海洋对大气的强迫作用,特别是同期冬季日本以东黑潮和黑潮延伸区海温异常的强迫作用;风暴轴南北位置与太平洋海温异常的关系,在1977年以后表现为大气对海洋的强迫作用,主要表现为对北太平洋中部海温的影响,但在1977年以前表现为海洋和大气的共同作用,风暴轴南北位置的变化还与同期的赤道中东太平洋海温异常有关,表明ENSO可能对风暴轴的位置变化存在影响。     

Subsurface influence on SST in the tropical Indian Ocean: structure and interannual variability

Interannual variations of subsurface influence on SST in the Indian Ocean show strong seasonality. The subsurface influence on SST confines to the southern Indian Ocean (SIO) in boreal winter and spring; it is observed on both sides of the equator in boreal summer and fall. Interannual long Rossby waves are at the heart of this influence, and contribute significantly to the coupled climate variability in the tropical Indian Ocean (TIO). Principal forcing mechanism for the generation of these interannual waves in the Indian Ocean and the relative influence of two dominant interannual signals in the tropics, namely El Niño and Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), are also discussed. Two distinct regions dominated by either of the above climate signals are identified. IOD dominates the forcing of the off-equatorial Rossby waves, north of 10°S, and the forcing comes mainly from the anomalous Ekman pumping associated with the IOD. However, after the demise of IOD activity by December, Rossby waves are dominantly forced by ENSO, particularly south of 10°S.It is found that the subsurface feedback in the northern flank of the southern Indian Ocean ridge region (north of 10°S) significantly influences the central east African rainfall in boreal fall. The Indian Ocean coupled process further holds considerable capability of predicting the east African rainfall by one season ahead. Decadal modulation of the subsurface influence is also noticed during the study period. The subsurface influence north of 10°S coherently varies with the IOD, while it varies coherently with the ENSO south of this latitude.     

Cooperative effects of tropical Pacific and Atlantic SST forcing in southern China winter precipitation variability

Climate Dynamics - This study investigates the variability of winter precipitation over southern China (SC) and the impacts of sea surface temperature (SST) forcing in the tropical Pacific and...     

SST variability in the South Indian Ocean and associated circulation and rainfall patterns over Southern Africa

Summary A general circulation model is used to study the response of the atmosphere to an idealised sea surface temperature (SST) anomaly pattern (warm throughout the southern midlatitudes, cool in the tropics) in the South Indian Ocean region. The anomaly imposed on monthly SST climatology captures the essence of patterns observed in the South Indian Ocean during both ENSO events and multidecadal epochs, and facilitates diagnosis of the model response. A previous study with this anomaly imposed in the model examined differences in the response between that on the seasonal scale (favours enhancement of the original SST anomaly) and that on the decadal scale (favours damping of the anomaly). The current study extends that work firstly by comparing the response on the intraseasonal, seasonal and interannual scales, and secondly, by assessing the changes in the circulation and rainfall over the adjoining African landmass.It is found that the atmospheric response is favourable for enhancement of the original SST anomaly on scales up to, and including, annual. However, as the scale becomes interannual (i.e., 15–21 months after imposition of the anomaly), the model response suggests that damping of the original SST anomaly becomes likely. Compared to the shorter scale response, the perturbation pressure and wind distribution on the interannual scale is shifted poleward, and is more reminiscent of the decadal response. Winds are now stronger over the warm anomaly in the southern midlatitudes suggesting enhanced surface fluxes, upper ocean mixing, and consequently, a damping of the anomaly.Examination of the circulation and rainfall patterns indicates that there are significant anomalies over large parts of southern Africa during the spring, summer and autumn seasons for both short (intraseasonal to interannual) and decadal scales. It appears that rainfall anomalies are associated with changes in the advection of moist tropical air from the Indian Ocean and its related convergence over southern Africa. Over eastern equatorial Africa, the austral autumn season (the main wet season) showed rainfall increases on all time scales, while parts of central to eastern subtropical southern Africa were dry. The signals during summer were more varied. Spring showed generally dry conditions over the eastern half of southern Africa on both short and decadal time scales, with wet areas confined to the west. In all cases, the magnitude of the rainfall anomalies accumulated over a 90 day season were of the order of 90–180 mm, and therefore represent a significant fraction of the annual total of many areas. It appears that relatively modest SST anomalies in the South Indian Ocean can lead to sizeable rainfall anomalies in the model. Although precipitation in general circulation models tends to be less accurately simulated than many other variables, the model results, together with previous observational work, emphasize the need for ongoing monitoring of SST in this region.With 14 Figures     

Skill and reproducibility of seasonal rainfall patterns in the tropics in ECHAM-4 GCM simulations with prescribed SST

 The ECHAM4 atmospheric general circulation model (GCM) has been integrated at T30 resolution through the period 1960–1994 forced with the observed sea-surface temperatures (SSTs) as compiled at the Hadley Centre (GISST2.2). Three experiments were made starting from different initial conditions. The large-scale tropical precipitation patterns simulated by the model have been studied, focusing on the skill (i.e. the capability to simulate the observed anomaly over land areas) and reproducibility (i.e. the GCM’s interannual rainfall variance that is independent from the initial conditions). Analysis of variance is used to estimate the reproducibility amongst ensemble members at each grid-box, but most emphasis is placed on large-scale patterns, as revealed by various singular value decomposition analyses (SVDAs), between observed and model fields (OM analyses) and amongst the different model runs (MM analyses). Generally, it is found that the first model mode in the MM analysis is very similar to that in the OM analysis, suggesting the model mode with strongest reproducibility is also the mode which tallies best with observations. For the global tropics, the first MM mode is highly reproducible (external variance above 90%) and the first OM couplet is very skillful (correlation between observed and model SVDA time series is over 0.84). The extent to which skill and reproducibility is related to El Nino/Southern Oscillation (ENSO) has been investigated by comparing the OM and MM time series with the Southern Oscillation Index (SOI). For the global tropics, most of the OM and MM variance is common with the SOI, though in boreal summer, the first modes do also have some clear independence from the SOI. The analyses were repeated at the regional scale for Oceania, tropical America, tropical Africa and tropical Southeast Asia. A highly reproducible mode is found in all cases except October-December in Africa. Skill, while always positive, is more variable, strongest for Oceania and tropical America and weakest for Africa. Comparisons with the SOI suggest skill in tropical America and tropical Africa has substantial components that are independent of the SOI, especially in boreal spring and summer when the tropical Atlantic SSTs are strongly related to the leading OM and MM time series. Received: 1 January 1997 / Accepted: 28 July 1997     

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.     

Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models

Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean–atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959–1979) are closer to the ‘perfect model’ (attainable) score but, large differences are observed between ‘actual’ skill and ‘perfect model’ skill in the recent period (1980–2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.     

Decadal predictability and forecast skill

The “potential predictability” of the climate system is the upper limit of available forecast skill and can be characterized by the ratio p of the predictable variance to the total variance. While the potential predictability of the actual climate system is unknown its analog q may be obtained for a model of the climate system. The usual correlation skill score r and the mean square skill score M are functions of p in the case of actual forecasts and potential correlation ρ and potential mean square skill score $\mathcal{M}$ are the same functions of q in the idealized model context. In the large ensemble limit the connection between model-based potential predictability and skill scores is particularly straightforward with $q=\rho^{2}=\mathcal{M}.$ Decadal predictions of annual mean temperature produced with the Canadian Centre for Climate Modelling and Analysis coupled climate model are analyzed for information on decadal climate predictability and actual forecast skill. Initialized forecast results are compared with the results of uninitialized climate simulations. Model-based values of potential predictability q and potential correlation skill ρ are obtained and ρ is compared with the actual forecast correlation skill r. The skill of externally forced and internally generated components of the variability are separately estimated. As expected, ρ > r and both decline with forecast range τ, at least for the first five years. The decline of skill is associated mainly with the decline of the skill of the internally generated component. The potential and actual skill of a forecast of time-averaged temperature depends on the averaging period. The skill of uninitialized simulations is low for short averaging times and increases as averaging time increases. By contrast, skill is high at short averaging times for forecasts initialized from observations and declines as averaging times increase to about three years, then increases somewhat at longer averaging times. The skills of the initialized forecasts and uninitialized simulations begin to converge for longer averaging times. The potential correlation skill ρ of the externally forced component of temperature is largest at tropical latitudes and the skill of the internally generated component is largest over the North Atlantic, parts of the Southern Ocean and to some extent the North Pacific. Potential skill over extratropical land is somewhat weaker than over oceans. The distribution of actual correlation skill r is broadly similar to that of potential skill for the externally forced component but less so for the internally generated component. Differences in potential and actual skill suggest where improvements in the forecast system might be found.