Phase‐locked and asymmetric correlations of the wintertime atmospheric patterns with the ENSO

Abstract

Teleconnections between sea surface temperature (SST) anomalies over the Pacific and the dominant patterns of wintertime Northern Hemisphere 500‐hPa height are examined by applying statistical techniques such as rotated principal component analysis and composite analysis. It is shown that the Pacific/North American (PNA) patterns in December through March are correlated most significantly with the ENSO‐related SST anomalies in the previous October, while the western Pacific (WP) patterns in December through February are most closely linked to the ENSO‐related SST anomalies in the same season. In addition, the PNA response to the ENSO signal during La Niña events is more significant than that during El Niño events, while the WP response is stronger during El Niño events than during La Niña events. A composite analysis shows that in the El Niño winters the North Pacific centre of the PNA pattern is located about 10 degrees east of its normal position, leading to a less significant correlation between the ENSO signal and the PNA pattern in these winters.

The ENSO‐related SST anomalies include a large centre of action over the tropical Pacific and an oppositely signed anomaly centre over the North Pacific. The North Pacific centre appears to the west of the dateline in September and October. This ENSO‐related seed of SST anomalies slowly moves eastward in the following months, gradually cutting off its connection with SST anomalies over the tropical Pacific and being coupled with the PNA pattern. It is pointed out that, although the wintertime SST anomaly over the North Pacific may appear as a mode linearly independent of the ENSO signal in the same season, it is partially related to the ENSO signal in the preceding autumn.

Possible dynamical explanations of the above results are discussed. It is suggested that the WP pattern can be linked to the tropical Pacific heat source via advection of vorticity by the upper‐tropospheric divergent/convergent flow, and the intensification of vorticity gradients associated with a stronger east Asian jet is likely to be responsible for a more significant WP pattern response to the ENSO signal in the El Niño winters. On the other hand, the ENSO‐related PNA pattern could be considered a manifestation of the eastward extension (El Niño) or westward withdrawal (La Niña) of the east Asian jet stream due to the local Hadley cell over the Pacific. In addition, the ENSO‐related seed of extratropical SST anomaly over the western Pacific in autumn may also play an important role in the development of the PNA pattern in the following winter.     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

Seasonal prediction of African precipitation with ECHAM4–T42 ensemble simulations using a multivariate MOS re-calibration scheme

A 15 member ensemble of 20th century simulations using the ECHAM4–T42 atmospheric GCM is utilized to investigate the potential predictability of interannual variations of seasonal rainfall over Africa. Common boundary conditions are the global sea surface temperatures (SST) and sea ice extent. A canonical correlation analysis (CCA) between observed and ensemble mean ECHAM4 precipitation over Africa is applied in order to identify the most predictable anomaly patterns of precipitation and the related SST anomalies. The CCA is then used to formulate a re-calibration approach similar to model output statistics (MOS) and to derive precipitation forecasts over Africa. Predictand is the climate research unit (CRU) gridded precipitation over Africa. As predictor we use observed SST anomalies, ensemble mean precipitation over Africa and a combined vector of mean sea level pressure, streamfunction and velocity potential at 850 hPa. The different forecast approaches are compared. Most skill for African precipitation forecasts is provided by tropical Atlantic (Gulf of Guinea) SST anomalies which mainly affect rainfall over the Guinean coast and Sahel. The El Niño/Southern Oscillation (ENSO) influences southern and East Africa, however with a lower skill. Indian Ocean SST anomalies, partly independent from ENSO, have an impact particularly on East Africa. As suggested by the large agreement between the simulated and observed precipitation, the ECHAM4 rainfall provides a skillful predictor for CRU precipitation over Africa. However, MOS re-calibration is needed in order to provide skillful forecasts. Forecasts using MOS re-calibrated model precipitation are at least as skillful as forecast using dynamical variables from the model or instantaneous SST. In many cases, MOS re-calibrated precipitation forecasts provide more skill. However, differences are not systematic for all regions and seasons, and often small.     

Impact of in-consistency between the climate model and its initial conditions on climate prediction

We investigated the influence of dynamical in-consistency of initial conditions on the predictive skill of decadal climate predictions. The investigation builds on the fully coupled global model “Coupled GCM for Earth Simulator” (CFES). In two separate experiments, the ocean component of the coupled model is full-field initialized with two different initial fields from either the same coupled model CFES or the GECCO2 Ocean Synthesis while the atmosphere is initialized from CFES in both cases. Differences between both experiments show that higher SST forecast skill is obtained when initializing with coupled data assimilation initial conditions (CIH) instead of those from GECCO2 (GIH), with the most significant difference in skill obtained over the tropical Pacific at lead year one. High predictive skill of SST over the tropical Pacific seen in CIH reflects the good reproduction of El Niño events at lead year one. In contrast, GIH produces additional erroneous El Niño events. The tropical Pacific skill differences between both runs can be rationalized in terms of the zonal momentum balance between the wind stress and pressure gradient force, which characterizes the upper equatorial Pacific. In GIH, the differences between the oceanic and atmospheric state at initial time leads to imbalance between the zonal wind stress and pressure gradient force over the equatorial Pacific, which leads to the additional pseudo El Niño events and explains reduced predictive skill. The balance can be reestablished if anomaly initialization strategy is applied with GECCO2 initial conditions and improved predictive skill in the tropical Pacific is observed at lead year one. However, initializing the coupled model with self-consistent initial conditions leads to the highest skill of climate prediction in the tropical Pacific by preserving the momentum balance between zonal wind stress and pressure gradient force along the equatorial Pacific.

     

Cross-season relation of the South China Sea precipitation variability between winter and summer

The present study reveals cross-season connections of rainfall variability in the South China Sea (SCS) region between winter and summer. Rainfall anomalies over northern South China Sea in boreal summer tend to be preceded by the same sign rainfall anomalies over southern South China Sea in boreal winter (denoted as in-phase relation) and succeeded by opposite sign rainfall anomalies over southern South China Sea in the following winter (denoted as out-of-phase relation). Analysis shows that the in-phase relation from winter to summer occurs more often in El Niño/La Niña decaying years and the out-of-phase relation from summer to winter appears more frequently in El Niño/La Niña developing years. In the summer during the El Niño/La Niña decaying years, cold/warm and warm/cold sea surface temperature (SST) anomalies develop in tropical central North Pacific and the North Indian Ocean, respectively, forming an east–west contrast pattern. The in-phase relation is associated with the influence of anomalous heating/cooling over the equatorial central Pacific during the mature phase of El Niño/La Niña events that suppresses/enhances precipitation over southern South China Sea and the impact of the above east–west SST anomaly pattern that reduces/increases precipitation over northern South China Sea during the following summer. The impact of the east–west contrast SST anomaly pattern is confirmed by numerical experiments with specified SST anomalies. In the El Niño/La Niña developing years, regional air-sea interactions induce cold/warm SST anomalies in the equatorial western North Pacific. The out-of-phase relation is associated with a Rossby wave type response to anomalous heating/cooling over the equatorial central Pacific during summer and the combined effect of warm/cold SST anomalies in the equatorial central Pacific and cold/warm SST anomalies in the western North Pacific during the mature phase of El Niño/La Niña events.     

Improving long-lead seasonal forecasts of precipitation over Southern China based on statistical downscaling using BCC_CSM1.1m

Long-lead precipitation forecasts for 1–4 seasons ahead are usually difficult in dynamical climate models due to the model deficiencies and the limited persistence of initial signals. But, these forecasts could be empirically improved by statistical approaches. In this study, to improve the seasonal precipitation forecast over the southern China (SC), the statistical downscaling (SD) models are built by using the predictors of atmospheric circulation and sea surface temperature (SST) simulated by the Beijing Climate Center Climate System Model version 1.1 m (BCC_CSM1.1 m). The different predictors involved in each SD model is selected based on both its close relationship with the target seasonal precipitation and its reasonable prediction skill in the BCC_CSM1.1 m. Cross and independent validations show the superior performance of the SD models, relative to the BCC_CSM1.1 m. The temporal correlation coefficient of SD models could reach > 0.4, exceeding the 95 % confidence level. The SC precipitation index can be much better forecasted by the SD models than by the BCC_CSM1.1 m in terms of the interannual variability. In addition, the errors of the precipitation forecast in all four seasons are significantly reduced over most of SC in the SD models. For the 2015/2016 strong El Niño event, the SD models outperform the dynamical BCC_CSM1.1 m model on the spatial and regional-average precipitation anomalies, mostly due to the effective SST predictor in the SD models and the weak response of the SC precipitation to El Niño-related SST anomalies in the BCC_CSM1.1 m.     

Nonlinear precipitation response to El Niño and global warming in the Indo-Pacific

Precipitation changes over the Indo-Pacific during El Niño events are studied using an Atmospheric General Circulation Model forced with sea-surface temperature (SST) anomalies and changes in atmospheric CO₂ concentrations. Linear increases in the amplitude of the El Niño SST anomaly pattern trigger nonlinear changes in precipitation amounts, resulting in shifts in the location and orientation of the Intertropical Convergence Zone (ITCZ) and the South Pacific Convergence Zone (SPCZ). In particular, the maximum precipitation anomaly along the ITCZ and SPCZ shifts eastwards, the ITCZ shifts south towards the equator, and the SPCZ becomes more zonal. Precipitation in the equatorial Pacific also increases nonlinearly. The effect of increasing CO₂ levels and warming SSTs is also investigated. Global warming generally enhances the tropical Pacific precipitation response to El Niño. The precipitation response to El Niño is found to be dominated by changes in the atmospheric mean circulation dynamics, whereas the response to global warming is a balance between dynamic and thermodynamic changes. While the dependence of projected climate change impacts on seasonal variability is well-established, this study reveals that the impact of global warming on Pacific precipitation also depends strongly on the magnitude of the El Niño event. The magnitude and structure of the precipitation changes are also sensitive to the spatial structure of the global warming SST pattern.     

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.     

Favorable connections between seasonal footprinting mechanism and El Niño

Previous studies suggested that the wintertime SST in the North Pacific that are generated by the concurrent North Pacific Oscillation (NPO) are able to force El Niño during subsequent winter via the so-called ‘seasonal footprinting mechanism’ (SFM). We examine how the NPO effectively generates the El Niño via the SFM in the observations and models. The occurrence ratio for El Niño under conditions of NPO forcing during the previous winters is about 41 % for the period of 61 years (1949–2009), indicating that the atmospheric forcing from the mid-latitudes through the SFM does not always trigger an El Niño. We observed certain favorable conditions under which the SFM may effectively induce El Niño. We directly compared these observations with two cases: when the wintertime NPO leads to El Niño during the following winter through the SFM, and when the wintertime NPO is not followed by El Niño. Our analysis demonstrates that the spatial structures of the NPO, associated wind speed and net heat flux in the northeast Pacific, differ between the two cases. Such differences determine the existence of a footprint SST in the northeastern Pacific during the late spring and summer, which plays a key role in initiating the El Niño via the projection of westerly wind stress anomalies onto the equatorial Pacific during the same seasons. By conducting linear baroclinic model experiments, it is found that the positions of La Niña SST forcing during the previous winter are able to modify the spatial structures of the NPO, which produces favorable conditions for the El Niño during subsequent winter via the SFM.     

A comparison of full-field and anomaly initialization for seasonal to decadal climate prediction

There are two main approaches for dealing with model biases in forecasts made with initialized climate models. In full-field initialization, model biases are removed during the assimilation process by constraining the model to be close to observations. Forecasts drift back towards the model’s preferred state, thereby re-establishing biases which are then removed with an a posterior lead-time dependent correction diagnosed from a set of historical tests (hindcasts). In anomaly initialization, the model is constrained by observed anomalies and deviates from its preferred climatology only by the observed variability. In theory, the forecasts do not drift, and biases may be removed based on the difference between observations and independent model simulations of a given period. Both approaches are currently in use, but their relative merits are unclear. Here we compare the skill of each approach in comprehensive decadal hindcasts starting each year from 1960 to 2009, made using the Met Office decadal prediction system. Both approaches are more skilful than climatology in most regions for temperature and some regions for precipitation. On seasonal timescales, full-field initialized hindcasts of regional temperature and precipitation are significantly more skilful on average than anomaly initialized hindcasts. Teleconnections associated with the El Niño Southern Oscillation are stronger with the full-field approach, providing a physical basis for the improved precipitation skill. Differences in skill on multi-year timescales are generally not significant. However, anomaly initialization provides a better estimate of forecast skill from a limited hindcast set.     

The impact of el Nino‐Southern oscillation on the temperature field over Canada: Research note

Abstract

The impact of the two phases of El Niño‐Southern Oscillation (ENSO), namely El Niño and La Niña, on the surface and lower tropospheric temperature fields over Canada is documented. Gridded surface temperature data for 91 years (1900–1990) and 500–1000 hPa thickness data for 49 years (1946–1994) have been analyzed statistically in the context of El Niño, La Niña and normal years.

Using a composite analysis, the present study conclusively demonstrates that significant positive surface temperature anomalies spread eastward from the west coast of Canada to the Labrador coast from the late fall to early spring (November through May) following the onset of El Niño episodes. The accompanying temperatures in the lower troposphere show a transition from the Pacific/North American (PNA) pattern to the Tropical/Northern Hemisphere (TNH) pattern over the North American sector during the same period. Conversely, significant negative surface temperature anomalies spread southeastward from the Yukon and extend into the upper Great Lakes region by the winter season following the onset of La Niña episodes. Furthermore, the lower tropospheric temperatures show a negatively‐phased PNA‐like pattern in early winter which weakens considerably by May of the following year. Thus, while western Canadian surface temperatures are influenced during both phases of ENSO, eastern Canadian surface temperature effects are found during the El Niño phase only. The impact of ENSO on the Canadian surface temperatures is the strongest during the winter season and nearly disappears by spring (April and May). The largest positive (negative) anomalies are found to be centred over two separate regions, one over the Yukon and the other just west of Hudson Bay in the El Niño (La Niña) years. Over western Canada, mean wintertime temperature distribution of the El Niño (La Niña) years is found to be shifted towards warmer (colder) values relative to the distribution of the normal years.

This study suggests the possibility of developing a long‐range forecasting technique for Canada using ENSO related indices.     

Documentation of a highly ENSO‐related sst region in the equatorial pacific: Research note

Abstract

A new ENSO SST index is documented that is strongly correlated to the core ENSO phenomenon. The SST anomaly in much of the east‐central and eastern tropical Pacific is closely related to ENSO. However, the anomaly from approximately the centre of the eastern half of the equatorial Pacific westward to near the date line is suggested to be most strongly ENSO‐related when data spanning the most recent several decades are used. This is the case both with respect to (1) strength of association with other oceanic/atmospheric ENSO‐related anomalies (both simultaneously and as a time‐delayed predictand), and (2) impact on remote worldwide climate anomalies. This observational insight was lacking in the early 1980s when the four “Niño” regions were developed. While a firmer dynamical foundation for this regional preference still needs to be established, the region straddling Niño 3 and Niño 4 may be regarded as an appropriate general SST index of the ENSO state by researchers, diagnosticians and forecasters. A dataset of this index, called “Niño 3.4” (5°N‐5°S, 120–170°W), is maintained on the Internet, shown in the Climate Diagnostics Bulletin, and provided in the Appendix of this note.     

Sea surface temperature anomaly in the tropical North Atlantic during El Niño decaying years

Based on reanalysis data from 1979 to 2016, this study focuses on the sea surface temperature (SST) anomaly of the tropical North Atlantic (TNA) in El Niño decaying years. The TNA SST exhibits a clear warm trend during this period. The composite result for 10 El Niño events shows that the TNA SST anomaly reaches its maximum in spring after the peak of an El Niño event and persists until summer. In general, the anomaly is associated with three factors—namely, El Niño, the North Atlantic Oscillation (NAO), and a long-term trend, leading to an increase in local SST up to 0.4°C, 0.3°C, and 0.35°C, respectively. A comparison between 1983 and 2005 indicates that the TNA SST in spring is affected by El Niño, as well as the local SST in the preceding winter, which may involve a long-term trend signal. In addition, the lead–lag correlation shows that the NAO leads the TNA SST by 2–3 months. By comparing two years with an opposite phase of the NAO in winter (i.e., 1992 and 2010), the authors further demonstrate that the NAO is another important factor in regulating the TNA SST anomaly. A negative phase of the NAO in winter will reinforce the El Niño forcing substantially, and vise versa. In other words, the TNA SST anomaly in the decaying years is more evident if the NAO is negative with El Niño. Therefore, the combined effects of El Niño and the NAO must be considered in order to fully understand the TNA SST variability along with a long-term trend.摘要基于1979年到2016年多种再分析资料, 本文分析了El Niño衰减年热带北大西洋的海温异常. 结果表明, 热带北大西洋海温在此期间呈显著变暖趋势. 10次El Niño事件的合成结果表明热带北大西洋海温异常在El Niño事件峰值之后的春季达到最大值, 并持续到夏季. 一般而言, 这种异常与三个因子有关, 即El Niño, 北大西洋涛动和长期趋势, 能分别导致局地海温上升0.4°C, 0.3°C和0.35°C. 1983年和2005年的对比分析表明, 尽管El Niño强度对春季北大西洋海温起到决定性作用, 与长期趋势密切相关的前冬海温也很重要. 此外, 超前-滞后相关结果表明北大西洋涛动超前海温约2–3个月. 比较两个冬季相反位相北大西洋涛动的年份 (即1992年和2010年) , 表明北大西洋涛动也能调制北大西洋海温异常. 冬季负位相北大西洋涛动能显著增强El Niño的强迫影响, 反之亦然. 换言之, 如果北大西洋涛动与El Niño位相相合, 衰减年北大西洋海温异常才更为显著. 因此, 为全面理解热带北大西洋海温变化, 除长期趋势外, 还必须考虑El Niño和北大西洋涛动的综合影响.     

Altered atmospheric responses to eastern Pacific and central Pacific El Niños over the North Atlantic region due to stratospheric interference

The two types of El Niño that have been identified, namely the eastern Pacific (EP) and central Pacific (CP) El Niños, are known to exert different climatic impacts on the North Atlantic region during winter. Here, we investigate the characteristics of the teleconnection of the two El Niño types with a focus on the stratosphere-troposphere coupling. During the EP El Niño, polar stratospheric warming and polar vortex weakening frequently occur with a strong tendency for downward propagation near the tropopause. Consequently, the atmospheric pattern within the troposphere over the North Atlantic sector during midwinter closely resembles the negative North Atlantic Oscillation pattern. In contrast, during CP El Niño events stratospheric warming events exhibit a much weaker downward propagation tendency. This difference in the stratospheric circulation response arises from the different seasonal evolution of the tropospheric wave response to the two El Niño types. For the EP El Niño, the Aleutian Low begins growing during December and is sustained throughout the entire winter (December to February), which provides favorable conditions for the continuous downward propagation of the stratospheric warming. We also discuss the origin of the difference in the teleconnections from the two types of El Niño associated with the distinct longitudinal position of the warm SST anomaly that determines troposphere-stratosphere coupling.     

Evolution of ENSO-related rainfall anomalies in Southeast Asia region and its relationship with atmosphere–ocean variations in Indo-Pacific sector

The Southeast Asia rainfall (SEAR) anomalies depend strongly on phases of El Niño (La Niña). Using an extended empirical orthogonal function (EEOF) analysis, it is shown that the dominant EEOF mode of SEAR anomalies evolves northeastward throughout a period from the summer when El Niño develops to spring the following year when the event weakens. This evolution is consistent with northeastward migration of the ENSO-related anomalous out going radiation field. During boreal summer (winter), the strong ENSO-related anomaly tends to reside in regions south (north) of the equator. The evolution of dominant mode of SEAR anomalies is in tandem with the evolution of ENSO-related sea surface temperature (SST) anomalies. The strengthening and weakening of “boomerang-shaped” SST in western Pacific, the changing sign of anomalous SST in Java Sea and the warming in Indian Ocean and South China Sea are all part of ENSO-related changes and all are linked to SEAR anomaly. The anomalous low-level circulation associated with ENSO-related SEAR anomaly indicates the strengthening and weakening of two off-equatorial anticyclones, one over the Southern Indian Ocean and the other over the western North Pacific. Together with patterns of El Niño minus La Niña composites of various fields, it is proposed that the northeastward evolution of SEAR anomaly is basically part of the large-scale eastward evolution of ENSO-related signal in the Indo-Pacific sector. The atmosphere–ocean interaction plays an important role in this evolution.     

Distinctive Precursory Air–Sea Signals between Regular and Super El Ni os

Statistically different precursory air–sea signals between a super and a regular El Ni no group are investigated, using observed SST and rainfall data, and oceanic and atmospheric reanalysis data. The El Ni no events during 1958–2008 are first separated into two groups: a super El Ni no group(S-group) and a regular El Ni no group(R-group). Composite analysis shows that a significantly larger SST anomaly(SSTA) tendency appears in S-group than in R-group during the onset phase[April–May(0)], when the positive SSTA is very small. A mixed-layer heat budget analysis indicates that the tendency difference arises primarily from the difference in zonal advective feedback and the associated zonal current anomaly(u).This is attributed to the difference in the thermocline depth anomaly(D) over the off-equatorial western Pacific prior to the onset phase, as revealed by three ocean assimilation products. Such a difference in D is caused by the difference in the wind stress curl anomaly in situ, which is mainly regulated by the anomalous SST and precipitation over the Maritime Continent and equatorial Pacific.     

The interannual variability of East Asian Winter Monsoon and its relation to the summer monsoon

1.IntroductionOvertheEastAsiaregion,themostprominentsurfacefeatureofthewintermonsoonisstrongnortheasterliesalongtheeastflankoftheSiberianhighandthecoastofEastAsia.At500hPathereisabroadtroughcenteredaboutatthelongitudesofJapan.Thedominantfea-tureat2O0hPaistheEastAsianjetwithitsmaximumlocatedatjustsoutheastofJapan.Thisktisassociatedwithintensebaroclinicity,largeverticalwindshearandstrongadvectionofcoldair(StaffmembersofAcademiaSinica,l957,LauandChang,1987;BoyleandChen,1987;Chenetal.,1991…     

BCC_CSM模式夏季关键区海温回报评估

利用国家气候中心气候系统模式(Beijing Climate Center Climate System Model, BCC_CSM)的汛期回报试验数据集, 评估了夏季中低纬度海表面温度(Sea Surface Temperature, SST)的预测能力。结果表明:该模式对夏季中低纬海温具有一定的预测能力, 且在低纬地区的预测技巧尤为出色。对太平洋、热带印度洋和北大西洋这三个关键区进一步分析发现, 该模式对不同海区海温的预测能力有所不同。其中, 模式对夏季北太平洋海温及Ni?o 3.4指数表现出显著的预测技巧, 对热带印度洋、北大西洋海温及热带印度洋全区一致海温模态(Indian Ocean Basin-wide Warming, IOBW)也表现出一定的预测技巧, 而对北大西洋海温三极子模态(North Atlantic Tripole, NAT)的技巧相对较低。研究发现, 预测技巧与前冬的ENSO状态密切相关, 当前冬位于ENSO异常位相时, BCC_CSM模式对于三大海区夏季海温的预测技巧要高于前冬位于ENSO正常位相时, 且对NAT指数也具有更高的预测技巧。前冬ENSO所处的位相对于该模式对夏季Ni?o 3.4指数及IOBW指数的预测技巧影响不明显。此外, 该模式对夏季海温的预测技巧依赖于超前时间, 预测技巧在大部分情形下超前1个月的预测技巧相对更高。     

Dynamical seasonal prediction of Southern African summer precipitation

Prediction skill for southern African (16°–33°E, 22°–35°S) summer precipitation in the Scale Interaction Experiment-Frontier coupled model is assessed for the period of 1982–2008. Using three different observation datasets, deterministic forecasts are evaluated by anomaly correlation coefficients, whereas scores of relative operating characteristic and relative operating level are used to evaluate probabilistic forecasts. We have found that these scores for December–February precipitation forecasts initialized on October 1st are significant at 95 % confidence level. On a local scale, the level of prediction skill in the northwestern and central parts of southern Africa is higher than that in northeastern South Africa. El Niño/Southern Oscillation (ENSO) provides the major source of predictability, but the relationship with ENSO is too strong in the model. The Benguela Niño, the basin mode in the tropical Indian Ocean, the subtropical dipole modes in the South Atlantic and the southern Indian Oceans and ENSO Modoki may provide additional sources of predictability. Within the wet season from October to the following April, the precipitation anomalies in December-February are the most predictable. This study presents promising results for seasonal prediction of precipitation anomaly in the extratropics, where seasonal prediction has been considered a difficult task.     

Response of the tropical Indian Ocean SST to decay phase of La Niña and associated processes

Delayed impact of El Niño on Tropical Indian Ocean (TIO) Sea Surface Temperature (SST) variations and associated physical mechanisms are well documented by several studies. However, TIO SST evolution during the decay phase of La Niña and related processes are not adequately addressed before. Strong cooling associated with La Niña decay over the TIO could influence climate over the Indian Oceanic rim including Indian summer monsoon circulation and remotely northwest Pacific circulation. Thus understanding the TIO basin-wide cooling and related physical mechanisms during decaying La Niña years is important. Composite analyses revealed that negative SST anomalies allied to La Niña gradually dissipate from its mature phase (winter) till subsequent summer in central and eastern Pacific. In contrast, magnitude of negative SST anomalies in TIO, induced by La Niña, starts increasing from winter and attains their peak values in early summer. It is found that variations in heat flux play an important role in SST cooling over the central and eastern equatorial Indian Ocean, Bay of Bengal and part of Arabian Sea from late winter to early summer during the decay phase of La Niña. Ocean dynamical processes are mainly responsible for the evolution of southern TIO SST cooling. Strong signals of westward propagating upwelling Rossby waves between 10°S to 20°S are noted throughout (the decaying phase of La Niña) spring and summer. Anomalous cyclonic wind stress curl to the south of the equator is responsible for triggering upwelling Rossby waves over the southeastern TIO. Further, upwelling Rossby waves are also apparent in the Arabian Sea from spring to summer and partly contributing to the SST cooling. Heat budget analysis reveals that negative SST/MLT (mixed layer temperature) anomalies over the Arabian Sea are mostly controlled by heat flux from winter to spring and vertical advection plays an important role during early summer. Vertical and horizontal advection terms primarily contribute to the SST cooling anomalies over southern TIO and the Bay of Bengal cooling is primarily dominated by heat flux. Further we have discussed influence of TIO cooling on local rainfall variations.