Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

The seasonal prediction skill of the Asian summer monsoon is assessed using retrospective predictions (1982–2009) from the ECMWF System 4 (SYS4) and NCEP CFS version 2 (CFSv2) seasonal prediction systems. In both SYS4 and CFSv2, a cold bias of sea-surface temperature (SST) is found over the equatorial Pacific, North Atlantic, Indian Oceans and over a broad region in the Southern Hemisphere relative to observations. In contrast, a warm bias is found over the northern part of North Pacific and North Atlantic. Excessive precipitation is found along the ITCZ, equatorial Atlantic, equatorial Indian Ocean and the maritime continent. The southwest monsoon flow and the Somali Jet are stronger in SYS4, while the south-easterly trade winds over the tropical Indian Ocean, the Somali Jet and the subtropical northwestern Pacific high are weaker in CFSv2 relative to the reanalysis. In both systems, the prediction of SST, precipitation and low-level zonal wind has greatest skill in the tropical belt, especially over the central and eastern Pacific where the influence of El Nino-Southern Oscillation (ENSO) is dominant. Both modeling systems capture the global monsoon and the large-scale monsoon wind variability well, while at the same time performing poorly in simulating monsoon precipitation. The Asian monsoon prediction skill increases with the ENSO amplitude, although the models simulate an overly strong impact of ENSO on the monsoon. Overall, the monsoon predictive skill is lower than the ENSO skill in both modeling systems but both systems show greater predictive skill compared to persistence.     

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

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

Prediction skill of monthly SST in the North Atlantic Ocean in NCEP Climate Forecast System version 2

This work evaluates the skill of retrospective predictions of the second version of the NCEP Climate Forecast System (CFSv2) for the North Atlantic sea surface temperature (SST) and investigates the influence of El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) on the prediction skill over this region. It is shown that the CFSv2 prediction skill with 0–8 month lead displays a “tripole”-like pattern with areas of higher skills in the high latitude and tropical North Atlantic, surrounding the area of lower skills in the mid-latitude western North Atlantic. This “tripole”-like prediction skill pattern is mainly due to the persistency of SST anomalies (SSTAs), which is related to the influence of ENSO and NAO over the North Atlantic. The influences of ENSO and NAO, and their seasonality, result in the prediction skill in the tropical North Atlantic the highest in spring and the lowest in summer. In CFSv2, the ENSO influence over the North Atlantic is overestimated but the impact of NAO over the North Atlantic is not well simulated. However, compared with CFSv1, the overall skills of CFSv2 are slightly higher over the whole North Atlantic, particularly in the high latitudes and the northwest North Atlantic. The model prediction skill beyond the persistency initially presents in the mid-latitudes of the North Atlantic and extends to the low latitudes with time. That might suggest that the model captures the associated air-sea interaction in the North Atlantic. The CFSv2 prediction is less skillful than that of SSTA persistency in the high latitudes, implying that over this region the persistency is even better than CFSv2 predictions. Also, both persistent and CFSv2 predictions have relatively low skills along the Gulf Stream.     

Variability of the Indian Ocean SST and its possible impact on summer western North Pacific anticyclone in the NCEP Climate Forecast System

The NCEP Climate Forecast System version 2 (CFSv2) provides important source of information about the seasonal prediction of climate over the Indo-Pacific oceans. In this study, the authors provide a comprehensive assessment of the prediction of sea surface temperature (SST) in the tropical Indian Ocean (IO). They also investigate the impact of tropical IO SST on the summer anomalous anticyclonic circulation over the western North Pacific (WNPAC), focusing on the relative contributions of local SST and remote forcing of tropical IO SST to WNPAC variations. The CFSv2 captures the two most dominant modes of summer tropical IO SST: the IO basin warming (IOBW) mode and the IO dipole (IOD) mode, as well as their relationship with El Niño-Southern Oscillation (ENSO). However, it produces a cold SST bias in IO, which may be attributed to deeper-than-observed mixed layer and smaller-than-observed total downward heat flux in the tropical IO. It also overestimates the correlations of ENSO with IOBW and IOD, but underestimates the magnitude of IOD and summer IOBW. The CFSv2 captures the climate anomalies related to IOBW but not those related to IOD. It depicts the impact of summer IOBW on WNPAC via the equatorial Kelvin wave, which contributes to the maintenance of WNPAC in July and August. The WNPAC in June is mostly forced by local cold SST, which is better predicted by the CFSv2 compared to July and August. The mechanism for WNPAC maintenance may vary with lead time in the CFSv2.     

Southern Hemisphere extra-tropical forcing: a new paradigm for El Ni?o-Southern Oscillation

The main goal of this paper is to shed additional light on the reciprocal dynamical linkages between mid-latitude Southern Hemisphere climate and the El Ni?o-Southern Oscillation (ENSO) signal. While our analysis confirms that ENSO is a dominant source of interannual variability in the Southern Hemisphere, it is also suggested here that subtropical dipole variability in both the Southern Indian and Atlantic Oceans triggered by Southern Hemisphere mid-latitude variability may also provide a controlling influence on ENSO in the equatorial Pacific. This subtropical forcing operates through various coupled air?Csea feedbacks involving the propagation of subtropical sea surface temperature (SST) anomalies into the deep tropics of the Atlantic and Indian Oceans from boreal winter to boreal spring and a subsequent dynamical atmospheric response to these SST anomalies linking the three tropical basins at the beginning of the boreal spring. This atmospheric response is characterized by a significant weakening of the equatorial Atlantic and Indian Inter-Tropical Convergence Zone (ITCZ). This weakened ITCZ forces an equatorial ??cold Kelvin wave?? response in the middle to upper troposphere that extends eastward from the heat sink regions into the western Pacific. By modulating the vertical temperature gradient and the stability of the atmosphere over the equatorial western Pacific Ocean, this Kelvin wave response promotes persistent zonal wind and convective anomalies over the western equatorial Pacific, which may trigger El Ni?o onset at the end of the boreal winter. These different processes explain why South Atlantic and Indian subtropical dipole time series indices are highly significant precursors of the Ni?o34 SST index several months in advance before the El Ni?o onset in the equatorial Pacific. This study illustrates that the atmospheric internal variability in the mid-latitudes of the Southern Hemisphere may significantly influence ENSO variability. However, this surprising relationship is observed only during recent decades, after the so-called 1976/1977 climate regime shift, suggesting a possible linkage with global warming or decadal fluctuations of the climate system.     

How predictable is the northern hemisphere summer upper-tropospheric circulation?

The retrospective forecast skill of three coupled climate models (NCEP CFS, GFDL CM2.1, and CAWCR POAMA 1.5) and their multi-model ensemble (MME) is evaluated, focusing on the Northern Hemisphere (NH) summer upper-tropospheric circulation along with surface temperature and precipitation for the 25-year period of 1981–2005. The seasonal prediction skill for the NH 200-hPa geopotential height basically comes from the coupled models’ ability in predicting the first two empirical orthogonal function (EOF) modes of interannual variability, because the models cannot replicate the residual higher modes. The first two leading EOF modes of the summer 200-hPa circulation account for about 84% (35.4%) of the total variability over the NH tropics (extratropics) and offer a hint of realizable potential predictability. The MME is able to predict both spatial and temporal characteristics of the first EOF mode (EOF1) even at a 5-month lead (January initial condition) with a pattern correlation coefficient (PCC) skill of 0.96 and a temporal correlation coefficient (TCC) skill of 0.62. This long-lead predictability of the EOF1 comes mainly from the prolonged impacts of El Niño-Southern Oscillation (ENSO) as the EOF1 tends to occur during the summer after the mature phase of ENSO. The second EOF mode (EOF2), on the other hand, is related to the developing ENSO and also the interdecadal variability of the sea surface temperature over the North Pacific and North Atlantic Ocean. The MME also captures the EOF2 at a 5-month lead with a PCC skill of 0.87 and a TCC skill of 0.67, but these skills are mainly obtained from the zonally symmetric component of the EOF2, not the prominent wavelike structure, the so-called circumglobal teleconnection (CGT) pattern. In both observation and the 1-month lead MME prediction, the first two leading modes are accompanied by significant rainfall and surface air temperature anomalies in the continental regions of the NH extratropics. The MME’s success in predicting the EOF1 (EOF2) is likely to lead to a better prediction of JJA precipitation anomalies over East Asia and the North Pacific (central and southern Europe and western North America).     

两类ENSO对中国北方冬季平均气温和极端低温的不同影响

利用1961-2012年观测、再分析资料以及全球大气环流模式数值试验,探讨了中国北方冬季平均气温对于不同类型（即东部型和中部型）ENSO事件的气候响应,并分析了不同类型ENSO对极端低温事件的可能影响,重点关注了北大西洋涛动（NAO）在其中的桥梁作用。结果表明,ENSO信号能通过调制北大西洋地区的大气环流改变欧亚中高纬度地区的纬向温度平流输送和西伯利亚高压的强度,进而影响中国北方冬季气温,由于不同类型ENSO事件海温分布的差异,这种影响具有明显的非线性特征。在两类厄尔尼诺和东部型拉尼娜事件冬季,北大西洋涛动均呈现负位相,不利于北大西洋的暖湿空气向欧亚大陆输送,西伯利亚高压偏强,因而中国北方地区较气候态偏冷。中部型厄尔尼诺和东部型拉尼娜事件冬季气温负异常的显著区域分别位于东北大范围地区、内蒙古河套附近;东部型厄尔尼诺事件冬季显著的冷异常信号仅局限于黑龙江北部与大兴安岭地区;而中部型拉尼娜事件冬季虽伴随北大西洋涛动正位相,但其空间结构向西偏移,对下游中国北方地区气温的直接影响并不显著,可能受局地信号干扰较大。数值试验再现了北大西洋涛动以及中国北方冬季气温对不同类型ENSO的响应,进一步佐证了上述结论。此外,两类厄尔尼诺事件冬季中国东北地区日平均气温容易偏低,极端低温事件的发生频次增多;而两类拉尼娜事件对极端低温的影响较弱。      

The seasonal footprinting mechanism in CFSv2: simulation and impact on ENSO prediction

The seasonal footprinting mechanism (SFM) is thought to be a pre-cursor to the El Nino Southern Oscillation (ENSO). Fluctuations in the North Pacific Oscillation (NPO) impact the ocean via surface heat fluxes during winter, leaving a sea-surface temperature (SST) “footprint” in the subtropics. This footprint persists through the spring, impacting the tropical Pacific atmosphere–ocean circulation throughout the following year. The simulation of the SFM in the National Centers for Environmental Prediction (NCEP)/Climate Forecast System, version 2 (CFSv2) is likely to have an impact on operational predictions of ENSO and potentially seasonal predictions in the United States associated with ENSO teleconnection patterns. The ability of the CFSv2 to simulate the SFM and the relationship between the SFM and ENSO prediction skill in the NCEP/CFSv2 are investigated. Results indicate that the CFSv2 is able to simulate the basic characteristics of the SFM and its relationship with ENSO, including extratropical sea level pressure anomalies associated with the NPO in the winter, corresponding wind and SST anomalies that impact the tropics, and the development of ENSO-related SST anomalies the following winter. Although the model is able to predict the correct sign of ENSO associated with the SFM in a composite sense, probabilistic predictions of ENSO following a positive or negative NPO event are generally less reliable than when the NPO is not active.     

Seasonal Prediction for May Rainfall over Southern China Based on the NCEP CFSv2

In this study, we assess the prediction for May rainfall over southern China (SC) by using the NCEP CFSv2 outputs. Results show that the CFSv2 is able to depict the climatology of May rainfall and associated circulations. However, the model has a poor skill in predicting interannual variation due to its poor performance in capturing related anomalous circulations. In observation, the above-normal SC rainfall is associated with two anomalous anticyclones over the western tropical Pacific and northeastern China, respectively, with a low-pressure convergence in between. In the CFSv2, however, the anomalous circulations exhibit the patterns in response to the El Ni?o-Southern Oscillation (ENSO), demonstrating that the model overestimates the relationship between May SC rainfall and the ENSO. Because of the onset of the South China Sea monsoon, the atmospheric circulation in May over SC is more complex, so the prediction for May SC rainfall is more challenging. In this study, we establish a dynamic-statistical forecast model for May SC rainfall based on the relationship between the interannual variation of rainfall and large-scale ocean-atmosphere variables in the CFSv2. The sea surface temperature anomalies (SSTAs) in the northeastern Pacific and the central-eastern equatorial Pacific, and the 500-hPa geopotential height anomalies over western Siberia in previous April, which exert great influence on the SC rainfall in May, are chosen as predictors. Furthermore, multiple linear regression is employed between the predictors obtained from the CFSv2 and observed May SC rainfall. Both cross validation and independent test show that the hybrid model significantly improve the model''s skill in predicting the interannual variation of May SC rainfall by two months in advance.     

A brief introduction to the issue of climate and marine fisheries

Climatic variability has profound effects on the distribution, abundance and catch of oceanic fish species around the world. The major modes of this climate variability include the El Niño-Southern Oscillation (ENSO) events, the Pacific Decadal Oscillation (PDO) also referred to as the Interdecadal Pacific Oscillation (IPO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM) and the North Atlantic Oscillation (NAO). Other modes of climate variability include the North Pacific Gyre Oscillation (NPGO), the Atlantic Multidecadal Oscillation (AMO) and the Arctic Oscillation (AO). ENSO events are the principle source of interannual global climate variability, centred in the ocean–atmosphere circulations of the tropical Pacific Ocean and operating on seasonal to interannual time scales. ENSO and the strength of its climate teleconnections are modulated on decadal timescales by the IPO. The time scale of the IOD is seasonal to interannual. The SAM in the mid to high latitudes of the Southern Hemisphere operates in the range of 50–60 days. A prominent teleconnection pattern throughout the year in the Northern Hemisphere is the North Atlantic Oscillation (NAO) which modulates the strength of the westerlies across the North Atlantic in winter, has an impact on the catches of marine fisheries. ENSO events affect the distribution of tuna species in the equatorial Pacific, especially skipjack tuna as well as the abundance and distribution of fish along the western coasts of the Americas. The IOD modulates the distribution of tuna populations and catches in the Indian Ocean, whilst the NAO affects cod stocks heavily exploited in the Atlantic Ocean. The SAM, and its effects on sea surface temperatures influence krill biomass and fisheries catches in the Southern Ocean. The response of oceanic fish stocks to these sources of climatic variability can be used as a guide to the likely effects of climate change on these valuable resources.     

Development of statistical prediction models for Changma precipitation: An ensemble approach

An ensemble statistical forecast scheme with a one-month lead is developed to predict year-to-year variations of Changma rainfall over the Korean peninsula. Spring sea surface temperature (SST) anomalies over the North Atlantic, the North Pacific and the tropical Pacific Ocean have been proposed as useful predictors in a previous study. Through a forward-stepwise regression method, four additional springtime predictors are selected: the northern Indian Ocean (NIO) SST, the North Atlantic SST change (NAC), the snow cover anomaly over the Eurasian continent (EUSC), and the western North Pacific outgoing longwave radiation anomaly (WNP (OLR)). Using these, three new prediction models are developed. A simple arithmetic ensemble mean produces much improved forecast skills compared to the original prediction model of Lee and Seo (2013). Skill scores measured by temporal correlation and MSSS (mean square error skill score) are improved by about 9% and 17%, respectively. The GMSS (Gerrity skill score) and hit rate based on a tercile prediction validation scheme are also enhanced by about 19% and 13%, respectively. The reversed NIO, reversed WNP (OLR), and reversed NAC are all related to the enhancement of a cyclonic circulation anomaly to the south or southwest of the Korean peninsula, which induces southeasterly moisture flux into the peninsula and increasing Changma precipitation. The EUSC predictor induces an enhancement of the Okhotsk Sea high downstream and thus strengthening of Changma front.     

BCC大气环流模式对亚澳季风年际变率主导模态的模拟

利用观测海温驱动下的北京气候中心大气环流模式(BCC-AGCM)1979-2000年的模拟数据,从亚澳季风(A-AM)年际变率的角度,对该模式的性能进行了分析.通过季节依赖的EOF分析方法(SEOF)得到观测第1模态,与ENSO从暖位相向冷位相的转变相联系,并伴随东南印度洋和西北太平洋的降水异常随季节变化.该模态具有准2a和4-6a周期的谱峰.分析结果显示,BCC模式可以很好地模拟出第1模态的时间变化特征,及其与ENSO位相的同步关系.但是,模式模拟的降水空间型与观测存在偏差,这主要是由于模式对环流场模拟的偏差造成的,具体表现在西北太平洋(WNP)反气旋和南印度洋(SIO)反气旋的季节锁相模拟偏差.前者与模式模拟的环流场整体偏东有关,后者是由于SIO反气旋的发展和衰亡过程受印度洋局地海气相瓦作用影响,而单独大气模式则无法合理地反映这一过程.另外,模式模拟的第一模态降水空间型在夏季效果较差,原因在于模式模拟的夏季平均降水量存在偏差,尤其是东南印度洋的降水量模拟偏少.进一步分析表明,这可能与对流参数化方案的选择有关.     

ENSO及其组合模态对中国东部各季节降水的影响

近期的研究发现,热带太平洋低层大气存在两种主要模态,即经向对称ENSO模态和ENSO与海表温度(SST)年循环相互作用产生的经向反对称组合模态。主要探讨了这两种不同ENSO模态对中国东部各季节降水的影响。结果表明,厄尔尼诺年秋季,中国西南、长江及华南大部分区域呈现显著正降水异常;冬季,正降水异常范围扩大,覆盖华南、华东及华北东南部地区。这两个季节的异常降水都主要受ENSO模态的影响。与ENSO模态相关的正异常海温局地强迫导致120°E以西出现反气旋性环流,其西北侧增强的西南暖湿气流使得中国东部地区降水增多。次年春季,从中国华南延伸到东北出现正的异常降水,主要是ENSO组合模态的贡献。因为次年春季热带太平洋地区ENSO模态信号只局限于赤道地区,并没有对中国东部降水有显著的影响,而ENSO与海温年循环相互作用的组合模态使得与ENSO相关的赤道大气异常可以扩展到赤道以外地区。ENSO组合模态对中国降水异常有重要影响,在今后的研究和短期预测中需引起重视。      

SEASONAL PREDICTIONS FOR SPRING AND AUTUMN SURFACE AIR TEMPERATURES OVER SOUTHERN CHINA BY THE NCEP CFSV2

In this study, we investigate the variations of spring and autumn air temperatures in southern China (SC) and associated atmospheric circulation patterns. During the boreal spring, the SC air temperature is mainly influenced by tropical sea surface temperature anomalies (SSTAs). On the one hand, the El Ni?o SSTA pattern may induce a stronger-than-normal western Pacific subtropical high, which leads to warming in SC. On the other hand, the warm SSTAs in the tropical Indian Ocean may trigger anomalous Rossby wave trains, which propagate northeastward and result in anomalously high temperature in SC. During the boreal autumn, however, the SC temperature is more likely affected by mid-latitude atmospheric circulation, such as the wave trains forced by the North Atlantic SSTAs. The NCEP Climate Forecast System version 2 (CFSv2) is able to capture the climatology of SC air temperatures during both spring and autumn. For interannual variation, the CFSv2 shows a good skill for predicting the SC temperature in spring, due to the model’s good performance in capturing the associated atmospheric circulation anomalies as responses to tropical SSTAs, in spite of the overestimated relationship with the El Ni?o–Southern Oscillation (ENSO). However, the model has a poor skill for predicting the SC temperature in autumn, primarily due to the unrealistic prediction of its relationship with the ENSO.     

奇异值分解和奇异交叉谱分析方法在华北夏季降水诊断中的应用

利用1965~2000年华北5省市及相邻省73个地面观测站逐月平均降水场及北半球500 hPa高度场、北太平洋海温场资料, 采用奇异值分解 (SVD)、奇异交叉谱 (SCSA) 分析方法, 将华北夏季降水场分别与1月北半球500 hPa高度场、冬季北太平洋海温场进行了诊断分析, 得出奇异向量分布型及相互作用的耦合周期信号。在对前4对奇异向量的分析中发现, 华北夏季降水全区域为正距平时与1月北半球500 hPa高度场PNA遥相关型关系非常密切。ENSO对华北夏季降水的影响确实存在, 但华北夏季降水全区域为正距平时与冬季北太平洋ENSO关系并不明显。同时还找出了华北降水与北半球500 hPa高度、北太平洋海温场相互作用的关键区。在华北各型降水与高度场、海温场关键区相互作用的耦合周期中, 前者以准2~7年振荡为主; 后者则周期较长, 最短周期仍为准2年振荡, 最长周期为准10~11年振荡。以上结论为进一步研究华北夏季降水短期气候预测方法, 提供了参考依据。     

Predictions of Nino3.4 SST in CFSv1 and CFSv2: a diagnostic comparison

Diagnostic evaluations of the relative performances of CFSv1 and CFSv2 in prediction of monthly anomalies of the ENSO-related Nino3.4 SST index are conducted using the common hindcast period of 1982–2009 for lead times of up to 9 months. CFSv2 outperforms CFSv1 in temporal correlation skill for predictions at moderate to long lead times that traverse the northern spring ENSO predictability barrier (e.g., a forecast for July made in February). However, for predictions during less challenging times of the year (e.g., a forecast for January made in August), CFSv1 has higher correlations than CFSv2. This seeming retrogression is caused by a cold bias in CFSv2 predictions for Nino3.4 SST during 1982–1998, and a warm bias during 1999–2009. Work by others has related this time-conditional bias to changes in the observing system in late 1998 that affected the ocean reanalysis serving as initial conditions for CFSv2. A posteriori correction of these differing biases, and of a similar (but lesser) situation affecting CFSv1, allows for a more realistic evaluation of the relative performances of the two CFS versions. After the dual bias corrections, CFSv2 has slightly better correlation skill than CFSv1 for most months and lead times, with approximately equal skills for forecasts not traversing the ENSO predictability barrier and better skills for most (particularly long-lead) predictions traversing the barrier. The overall difference in correlation skill is not statistically field significant. However, CFSv2 has statistically significantly improved amplitude bias, and visibly better probabilistic reliability, and lacks target month slippage as compared with CFSv1. Together, all of the above improvements result in a highly significantly reduced overall RMSE—the metric most indicative of final accuracy.     

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。     

Sub-seasonal Prediction of the South China Sea Summer Monsoon Onset in the NCEP Climate Forecast System Version 2

This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset (SCSSMO) and investigates the associated oceanic and atmospheric processes, utilizing the hindcasts of the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Typically, the SCSSMO is accompanied by an eastward retreat of the western North Pacific subtropical high (WNPSH), development of the cross-equatorial flow, and an increase in the east-west sea surface temperature (SST) gradient. These features are favorable for the onset of westerlies and strengthening of convection and precipitation over the South China Sea (SCS). A more vigorous SCSSMO process shows a higher predictability, and vice versa. The NCEP CFSv2 can successfully predict the onset date and evolution of the monsoon about 4 pentads (20 days) in advance (within 1–2 pentads) for more forceful (less vigorous) SCSSMO processes. On the other hand, the climatological SCSSMO that occurs around the 27th pentad can be accurately predicted in one pentad, and the predicted SCSSMO occurs 1–2 pentads earlier than the observed with a weaker intensity at longer leadtimes. Warm SST biases appear over the western equatorial Pacific preceding the SCSSMO. These biases induce a weaker-than-observed WNPSH as a Gill-type response, leading to weakened low-level easterlies over the SCS and hence an earlier and less vigorous SCSSMO. In addition, after the SCSSMO, remarkable warm biases over the eastern Indian Ocean and the SCS and cold biases over the WNP induce weaker-than-observed westerlies over the SCS, thus also contributing to the less vigorous SCSSMO.     

Interdecadal Modulation of AMO on the Winter North Pacific Oscillation-Following Winter ENSO Relationship

It is known that the wintertime North Pacific Oscillation (NPO) is an important extratropical forcing for the occurrence of an El Ni?o?Southern Oscillation (ENSO) event in the subsequent winter via the “seasonal footprinting mechanism” (SFM). This study reveals that the Atlantic Multidecadal Oscillation (AMO) can notably modulate the relationship between the winter NPO and the following winter ENSO. During the negative AMO phase, the winter NPO has significant impacts on the following winter ENSO via the SFM. In contrast, the influence of the winter NPO on ENSO is not robust at all during the positive AMO phase. Winter NPO-generated westerly wind anomalies over the equatorial western Pacific during the following spring are much stronger during negative than positive AMO phases. It is suggested that the AMO impacts the winter NPO-induced equatorial westerly winds over the western Pacific via modulating the precipitation climatology over the tropical central Pacific and via modulating the connection of the winter NPO with spring sea surface temperature in the tropical North Atlantic.