厄尔尼诺和台风共同影响下的7月份黄、东海海温变化

基于历史海温数据和台风路径数据,研究了厄尔尼诺/拉尼娜（El Niño/La Niña）背景下7月份中国近海海温变化特征。结果表明:7月黄、东海海温异常与El Niño/La Niña有显著相关关系,OISST和GODAS海温数据与Niño3指数同步相关系数分别为-0.32和-0.45。El Niño年7月,黄、东海海表温度异常低于-0.5℃的概率超过60%;La Niña年7月,黄海海温异常高于0.5℃的概率约有60%;正常年7月,海温异常的空间分布与El Niño年相反,但量值偏低。El Niño年7月,中国近海及邻近区域大气异常能够给局地带来更多降水;同时,受El Niño背景场的影响,入侵黄、东海的台风强度更强、影响时间更长。大尺度的降水和台风活动的影响是导致黄、东海海温异常降低的重要原因。因此,分析和预测7月份中国近海海温异常,在充分考虑El Niño/La Niña背景场的基础上,需要结合局地的大尺度降水和台风的影响同时分析,这为特定背景下结合不同时间尺度上的因素共同分析中国近海海温变化提供了一种思路。     

热带太平洋第二类El Nio事件及其对中国气候的影响

基于热带太平洋次表层海温资料,分析了热带太平洋第二类El Nio事件海温异常的分布特征及其形成机制,讨论了与经典El Nio事件、El Nio Modoki、WP(西太平洋暖池)及CT(冷舌)El Nio事件之间的关系,揭示了第二类El Nio事件对中国降水的影响,得到以下结论。(1)第二类El Nio事件表征为热带太平洋次表层海温异常第三模态,占总方差贡献的4.7%。在海洋表面层,第二类El Nio事件暖期赤道东太平洋为沿赤道西伸的冷舌,热带中西太平洋为环绕冷舌的马蹄型大范围暖区。该型具11a和30~40a年代际振荡及3~4a年际变率,峰值多出现在春季。第二类El Nio事件是热带太平洋异常海面风应力场和赤道两侧的风应力旋度共同作用的结果,在赤道东印度洋-中西太平洋与赤道东太平洋-南美洲上空出现以反号垂直运动为特征的异常Walker环流。(2)El Nio Modoki与第二类El Nio事件有密切关系,它实质上是第二类El Nio事件次表层海温与近海面大气相互作用的结果,捕捉了第二类El Nio事件的主要信息。(3)第二类El Nio事件对中国春季及夏初降水有一定影响。在事件暖期,东海地区存在一个显著的异常反气旋性环流,其南侧的中国南方地区盛行异常东北气流,水汽来源减少,导致该地区少雨,其西侧的异常偏南气流北上直达华北地区,异常多水汽向北输送,并与北方的偏北流场相遇,导致该地区降水偏多。在第二类El Nio事件冷期相反。本文结果还指出,WP与CT El Nio事件是由经典El Nio事件第一模态与El Nio Modoki事件组合而成,它们不是独立的El Nio类型。此外,还讨论了夏半年El Nio事件对大气环流影响的物理过程。     

ENSO对华东地区春季降水影响的不对称性

利用1958—2019年的观测和再分析数据集,对冷、暖两类厄尔尼诺-南方涛动（El Niño-Southern Oscillation,ENSO）事件与后期华东地区春季降水之间的关系进行了分析。结果表明：（1）在暖ENSO事件中,华东春季降水量与前冬季ENSO海面温度异常存在较强的正相关关系。在冷ENSO事件中,这种强正相关向内陆地区西移,主要集中在江西和湖南。（2）暖ENSO事件通常会导致浙江、江苏和福建等沿海省份春季降水量过剩,而冷ENSO事件往往导致江西和湖南降水偏少。这归因于ENSO对大气环流的非线性影响。（3）与暖ENSO事件相比,冷ENSO事件引起的海面温度异常中心明显西移,造成异常低层大气环流的西移,最终导致华东降水的西移效应。（4）通过分析和发现,强调了华东春季降水对ENSO的非线性响应,这对华东地区的季节性气候预测具有重要意义。     

Manifestation of the Arctic Oscillation and El Niño-Southern Oscillation in the tropical stratosphere

Characteristics of the Arctic Oscillation and El Niño-Southern Oscillation effects manifested on interannual scales in the equatorial stratosphere are determined. Wavelet analysis of local phase shifts, coherence, and correlation is used to obtain correlation portraits of the largest factors of climate variability against the background of coherent variations in the equatorial stratospheric wind speed at the 50- and 15-hPa pressure levels. It is shown that the Arctic Oscillation and El Niño-Southern Oscillation signals may reach the tropical stratosphere. The signals are easily identified in a wide range of scales, including quasi-biennial, 3-to 5-year, and 10-to 11-year periods. The results obtained reflect a coherent pattern of the manifestation of these signals at the selected stratospheric levels. It is found that the El Niño-Southern Oscillation effect at periods close to 10–11 years reaches the stratospheric level rather rapidly, in the same or next month, while the effects of the Arctic Oscillation index are delayed by nine months. The estimates obtained show that a phase shift of almost 180° in the Arctic Oscillation index relative to the equatorial stratospheric wind occurred in almost all of the range of interannual periods in 1978 and 1992. For the El Niño-Southern Oscillation, an increase in local correlations on a scale of 3-to 5-year variations was observed in 1980–1990, a 180° phase shift occurred in 1992, and the correlation with stratospheric wind increased in 1992–2004. The estimates obtained are indicative of a change in the atmospheric circulation pattern that took place in the Northern Hemisphere in 1978–1991.     

Antarctic sea ice and ENSO event

The characteristic low-frequency oscillation of the sea surface temperature anomaly (SSTA) of ENSO related regions, Nino 1 + 2, Nino 3, Nino 4 and Nino West, and the Southern Oscillation index (SOI) is analyzed with the method of maximum entropy spectrum. Antarctic sea ice is divided into 4 regions, i. e. East Antarctic is Region Ⅰ (0°-120° E), the region dominated by Ross Sea ice is Region Ⅱ (120° E-120° W), the region dominated by Ross Sea ice is Region Ⅲ (120° W-0°), and the whole Antarctic sea ice area is Region Ⅳ. Also, the month-to-month correlation series of the sea ice with ENSO from contemporary to 5-years lag is calculated. The optimum correlation period is selected from the series. The characteristics and the rules obtained are as follows.1. There are a common 4-years main period of the SSTA of Ninos 1 + 2,3 and 4, a rather strong 4-years secondary period and a quasi-8-years main period of that of Nino West. There are also 1. 5 and 2 to 3-years secondary periods of that of all 4 Nin     

西北太平洋柔鱼冬春生群体栖息地的变化研究

柔鱼（Ommastrephes bartramii）是短生命周期鱼种,其适宜栖息地范围受海洋水温条件的显著影响。本文根据2006-2015年7-11月中国鱿钓技术组提供的西北太平洋柔鱼冬生群体的捕捞数据以及海表温度（SST）数据,利用捕捞努力量与SST的频率分布关系,估算柔鱼各月适宜温度范围（PFSST）,对1985-2015年柔鱼PFSST进行估算,同时分析柔鱼PFSST的年代际变化规律,并评估不同强度厄尔尼诺和拉尼娜事件对柔鱼栖息地的影响。研究表明,2006-2015年柔鱼各月适宜的SST具有明显变化,7-11月对应适宜的SST范围分别为16~19℃、17~21℃、15~19℃、14~16℃和12~13℃。单位捕捞努力量渔获量大小随PFSST变动而发生相应变化,两者具有显著正相关关系,这说明了柔鱼渔场范围内适宜温度面积增加,对应柔鱼资源丰度上升。1985-2015年柔鱼PFSST呈现显著的月间和年际变化,7-11月PFSST具有先增加后递减的变化规律,且7-9月PFSST年际波动相似,10和11月PFSST年际变化相似。同时,柔鱼PFSST与渔场内SST具有显著正相关关系。柔鱼渔场内PFSST受厄尔尼诺和拉尼娜事件调控,其面积随气候事件的强度发生变化,具体表现为:弱拉尼娜事件和正常气候条件下,柔鱼渔场范围内水温最高,适宜栖息面积显著增长;中等强度和高强度拉尼娜条件下,柔鱼渔场内平均水温较高,但适宜栖息面积较前两者显著减小;弱强度、中等强度和超高强度厄尔尼诺条件下,柔鱼渔场内水温均较低,但弱强度和超高强度厄尔尼诺条件下柔鱼适宜栖息面积均大于中等强度厄尔尼诺条件。     

Influence of Asian monsoon and ENSO events on particle fluxes in the western subtropical Pacific

A time-series sediment trap was deployed from October 2007 to May 2011 in the western subtropical Pacific with the aim of understanding the seasonal and inter-annual variability on particle flux in response to El Niño-Southern Oscillation (ENSO) events. Total mass fluxes varied from 3.04 mg m⁻² day⁻¹ to 31.1 mg m⁻² day⁻¹, with high fluxes during February–April and low fluxes during other months. This seasonal variation was also characterized by a distinct change in the CaCO₃ flux between the two periods. The marked increase in particle flux during February–April may be attributed to enhanced biological productivity in surface waters caused by strong wind-driven mixing in response to the western North Pacific monsoon system. The 2009/10 strong El Niño was accompanied by a significant reduction in particle flux, whereas the La Niña had no recognizable effect on particle flux in the subtropical Pacific. In particular, in the mature phase of the 2009/10 strong El Niño, the fluxes of organic carbon and biogenic silica decreased by 70–80% compared with those during the normal period, implying that the El Niño acted to suppress biological productivity in surface waters. The suppression of biological productivity during the 2009/10 strong El Niño is attributed to the decrease in precipitation due to the shift in the western Pacific warm pool. This finding is opposite that of other studies of the western equatorial Pacific, where El Niño events were observed to result in an increase in biological productivity and particle flux. The difference in particle flux between the western equatorial and subtropical Pacific is attributed to the regional differences in oceanic and atmospheric circulation systems generated by the strong El Niño.     

ENSO indices from sea surface salinity observed by Aquarius and Argo

Analysis of the first 26 months of data from the Aquarius satellite confirms the existence of a sharp sea surface salinity (SSS) front along the equator in the western equatorial Pacific. Following several earlier studies, we use the longitudinal location of the 34.8-psu isohaline as an index, termed Niño-S34.8, to measure the zonal displacement of the SSS front and consequently the eastern edge of the western Pacific warm pool. The on-going collection of the Array for Real-time Geostrophic Oceanography (ARGO) program data shows high correlations between Niño-S34.8 and the existing indices of El Niño, suggesting its potential important role in ENSO evolution. Further analysis of the ARGO data reveals that SSS variability in the southeastern tropical Pacific is crucial to identify the type of El Niño. A new SSS index, termed the southeastern Pacific SSS index (SEPSI), is defined based on the SSS variability in the region (0°–10°S, 150°–90°W). The SEPSI is highly correlated with the El Niño Modoki index, as well as the Trans-Niño index, introduced by previous studies. It has large positive anomalies during central Pacific El Niño or El Niño Modoki events, as a result of enhanced zonal sea surface temperature gradients between the central and eastern tropical Pacific, and can be used to characterize the type of El Niño. The processes that possibly control these SSS indices are also discussed.     

Spatio-temporal variability of chlorophyll a and its responses to sea surface temperature, winds and height anomaly in the western South China Sea

To understand the response of marine ecosystem to environmental factors, the oceanographic (physical and biochemical) data are analyzed to examine the spatio-temporal distributions of chlorophyll a (Chl a) associated with surface temperature, winds and height anomaly for long periods (1997-2008) in the western South China Sea (SCS). The results indicate that seasonal and spatial distributions of Chl a are primarily influenced by monsoon winds and hydrography. A preliminary Empirical Orthogonal Function (EOF) analysis of remotely sensed data is used to assess basic characteristics of the response process of Chl a to physical changes, which reveals interannual variability of anomalous low Chl a values corresponding to strong El Ni o (1997-1998), high values corresponding to strong La Ni a (1999-2000), low Chl a corresponding to moderate El Ni o (2001-2003), upward Chl a after warm event in 2005 off the east coast of Vietnam. The variability of Chl a in nearshore and the Mekong River Estuary (MER) waters also suggests its response to these warm or cold processes. Considering the evidence for covariabilities between Chl a and sea surface temperature, winds, height anomaly (upwelling or downwelling), cold waters input and strong winds mixing may play important roles in the spatial and temporal variability of high Chl a. Such research activities could be very important to gain a mechanistic understanding of ecosystem responses to the climate change in the SCS.     

Impact of the central Pacific zonal wind divergence and convergence on the central Pacific El Nio event

The central Pacific(CP) zonal wind divergence and convergence indices are defined, and the forming mechanism of CP El Nio(La Nia) events is discussed preliminarily. The results show that the divergence and convergence of the zonal wind anomaly(ZWA) are the key process in the forming of CP El Nio(La Nia) events. A correlation analysis between the central Pacific zonal wind divergence and convergence indices and central Pacific El Nio indices indicates that there is a remarkable lag correlation between them. The central Pacific zonal wind divergence and convergence indices can be used to predict the CP events. Based on these results, a linear regression equation is obtained to predict the CP El Nio(La Nia) events 5 months ahead.     

Effect of Sea Level Variability on the Estimation of Mean Sea Surface Gradients

It is demonstrated that an along-track mean sea surface (MSS) model estimated with TOPEX altimeter data, including the large 1997-1998 El Niño event, is slightly less accurate than a MSS model calculated from less data where El Niño signals are small. The manner in which true sea level variability corrupts the estimation of MSS gradients is discussed. A model is proposed to reduce the error, based on scaling climate indices such as the Southern Oscillation Index, while accounting for phase shifts using a Hilbert transform. After modeling and removing the seasonal and interannual sea level variations, parameters to a plane MSS model are estimated using TOPEX altimeter data from January 1993 to June 2000. Results indicate an overall improvement over the earlier model based on four years of data, and no apparent degradation due to aliasing of sea level variability.     

The frontal system at the boundary of the East China Sea: Its variability and response to large-scale atmospheric forcing

High-resolution satellite sea surface temperature measurements (PATHFINDER dataset) indicate that the fronts at the boundary of the East China Sea (Taiwan front, Kuroshio frontal zone, and South Korean coastal front) appear as a unified dominating frontal structure when climatological averaging is applied. This structure is about 1200 km in length, spreads over the continental shelf from Taiwan to the Tsushima Islands, and separates productive seawaters from the oligotrophic oceanic waters. The Kuroshio frontal zone, incorporated into this structure, reveals interannual variability with periods consistent with El Niño–Southern Oscillation (4–5 years).     

137°经向断面温、盐度的年际变异

系统地分析了137°E断面温、盐度的多年变化,主要结果为:(1)137°E断面100m层温度,在低纬度海域于某些年份出现异常低温,此现象可能与厄尔尼诺事件有关;指出棉兰老冷涡的存在是造成该断面于6°～8°N附近出现低温的主要原因。(2)厄尔尼诺期间,冬季137°E断面上28℃等温线所在纬度小于其多年平均值。(3)冬季137°E断面上次表层高盐水可划分为强型、次强型、中等型和弱型4种类型。     

Variations of eddy kinetic energy in the South China Sea

Fifteen years of merged altimetric data were used to acquire the seasonal to interanual variations of eddy kinetic energy (EKE) in the South China Sea (SCS). The results show that climatological mean EKE in the SCS ranges from 50 cm²/s² to 1,400 cm²/s², with high values in the regions southeast of Vietnam and southwest of Taiwan Island. The amplitude of the annual harmonic of the EKE is characterized by high values to the southeast of Vietnam where the maximum exceeds 800 cm²/s². The EKE in the northern SCS reaches its maximum in August-February, while it peaks in September–December in the southern SCS. Besides the seasonal variation, the EKE also shows strong interannual variation, which has a negative (positive) anomaly in boreal winter during El Niño (La Niña) events. The interannual variation of local wind stress curl associated with El Niño-Southern Oscillation events may be the cause of the interannual variation of the EKE in the SCS.     

Trends of sea surface temperature and sea surface temperature fronts in the South China Sea during 2003–2017

The trends of the sea surface temperature(SST) and SST fronts in the South China Sea(SCS) are analyzed during2003–2017 using high-resolution satellite data. The linear trend of the basin averaged SST is 0.31°C per decade,with the strongest warming identified in southeastern Vietnam. Although the rate of warming is comparable in summer and winter for the entire basin, the corresponding spatial patterns of the linear trend are substantially different between them. The SST trend to the west of the Luzon Strait is characterized by rapid warming in summer, exceeding approximately 0.6°C per decade, but the trend is insignificant in winter. The strongest warming trend occurs in the southeast of Vietnam in winter, with much less pronounced warming in summer. A positive trend of SST fronts is identified for the coast of China and is associated with increasing wind stress. The increasing trend of SST fronts is also found in the east of Vietnam. Large-scale circulation, such as El Ni?o, can influence the trends of the SST and SST fronts. A significant correlation is found between the SST anomaly and Ni?o3.4 index, and the ENSO signal leads by eight months. The basin averaged SST linear trends increase after the El Ni?o event(2009–2010), which is, at least, due to the rapid warming rate causing by the enhanced northeasterly wind. Peaks of positive anomalous SST and negatively anomalous SST fronts are found to co-occur with the strong El Ni?o events.     

Cause chain of an El Niño event in the eastern equatorial pacific and feedback and decrease-increase effects

Physical factors affecting El Niño events are subdivided into two categories. The first category includes those physical factors that have been demonstrated by modern science to have an effect on El Niño events. The second category comprises those physical factors that are only a hypothesis based on correlations that have yet to be corroborated to have affected El Niño events. This paper proposes the concept of a cause chain for an El Niño, pointing out that physical factors are linked and interdependent. The feedback effect and decrease-increase effect upon physical factors within the cause chain provide results superior to any single theory. We can only further explore the feedback effect and decrease-increase effect together with comprehensive analysis on the contributive ratio of these physical factors so as to improve the forecast accuracy of El Niño events. This represents a new way of thinking in the explanation of the cause of El Niño events.     

气候模式FIO-ESM对2015/16年厄尔尼诺的预测

Recently atmospheric and oceanic observations indicate the tropical Pacific is at the El Ni?o condition. However,it's not clear whether this El Ni?o event of this year is comparable to the very strong one of 1997/98 which brought huge influence on the whole world. In this study, based on the Ensemble Adjusted Kalman Filter(EAKF)assimilation scheme and First Institute of Oceanography-Earth System Model(FIO-ESM), the assimilation system is setup, which can provide reasonable initial conditions for prediction. And the hindcast results suggest the skill of El Ni?o-Southern Oscillation(ENSO) prediction is comparable to other dynamical coupled models. Then the prediction for 2015/16 El Ni?o by using FIO-ESM is started from 1 November 2015. The ensemble results indicate that the 2015/16 El Ni?o will continue to be strong. By the end of 2015, the strongest strength is very like more than 2.0°C and the ensemble mean strength is 2.34°C, which indicates 2015/16 El Ni?o event will be very strong but slightly less than that of 1997/98 El Ni?o event(2.40°C) calculated relative a climatology based on the years1992–2014. The prediction results also suggest 2015/16 El Ni?o event will be a transition to ENSO-neutral level in the early spring(FMA) 2016, and then may transfer to La Ni?a in summer 2016.     

西风爆发、次表层暖水东移与厄尔尼诺现象

利用最近20 a的大气海洋资料,分析了厄尔尼诺事件与赤道太平洋西风异常以及赤道太平洋次表层海温之间的关系.结果表明,赤道西太平洋(5°S～5°N,120°～160°E)和赤道中东太平洋(5°S～5°N,160°E～160°W)西风异常都存在着与厄尔尼诺周期一致的年际变化,但前者还包含有显著的2～3个月季节内振荡.赤道西太平洋次表层冷暖水东移也呈现年和年际时间尺度的振荡周期.在厄尔尼诺发生前,赤道西太平洋次表层海水出现持续性增暖,赤道西太平洋西风异常频率加快,强度增强.随后赤道中太平洋(160°E～160°W)出现持续性(3个月以上)强西风异常(即西风爆发),并进一步向东扩展,同时次表层暖水沿着赤道波导东移到赤道东太平洋混合层,导致赤道东太平洋海表大面积异常增暖,形成一次厄尔尼诺现象.最后,模式模拟了1980～1984年赤道太平洋海温的变化,进一步证实了赤道纬向西风异常对暖水东移起着重要的作用.     

Wave climate variability of Taiwan waters

Global sea surface wind field data derived from NCEP reanalysis were used in driving a SWAN wave model to reconstruct historical wave records from 1948 to 2008. The reconstructed wave data were compared and verified by the observation of the data buoys of the Central Weather Bureau and the Water Resources Agency, Taiwan, and the National Data Buoy Center/National Oceanic and Atmospheric Administration, United States. Over the past six decades, the wave climate in Taiwan waters has undergone considerable changes. The annual mean significant wave heights have reduced an average of 0.31 cm/year. Winter wave heights have gradually dropped 0.86 cm/year, which are related to the weakening of winter monsoons. Regarding the inter-annual wave climate variation, the influence of El Niño/southern oscillation was substantial; the wave heights increased in La Niña years and decreased in El Niño years. In the past 60 years, extreme wave events have been concentrated in two periods: 1967–1974 and 2000–2008. More severe extreme wave events occurred in the latter compared with the former, and all were induced by typhoons. A clear trend, in which the summer (winter) extreme wave events have increased (decreased) gradually, has been identified. The 1980s was the transition period. After the transition period, the annual occurrence of extreme wave events caused by typhoons exceeded those caused by an intense outbreak of winter cold surges, although the total number of the annual extreme wave events has not changed substantially.     

中西太平洋金枪鱼围网渔场聚类及其原因分析

本文根据1995-2010年我国中西太平洋金枪鱼围网生产统计数据,按年和月不同时间空间分辨率对金枪鱼围网渔场进行聚类分析,划定不同渔场类型;同时结合海表温度（SST）及Niño3.4区指数,探讨其渔场类型形成的原因。研究表明,在月为时间尺度下气候异常事件（El Niño和La Niña事件）发生频次与渔场聚类结果类别相关联,在1-12月发生气候异常事件频数分布可划分为以下几个阶段:1-3月、4-6、7-9月、10-12月,与月时间尺度下金枪鱼围网中心渔场4种聚类结果的时间范围具有一致性。通过渔场重心聚类结果和El Niño和La Niña事件分类统计对比发现,在年时间尺度下,气候异常事件的类型与聚类结果相关联,聚类结果同一类别包含的年份发生的气候异常事件具有一致性,即在同一类别下1995年、1997年为强El Niño年;1998年、2007、年、2009年为正常年份;2010年为强La Niña年;1999年、2000年、2001年为La Niña年;1996年、2008年为La Niña年;2002年、2004年为El Niño年。研究认为,中心渔场的年际聚类变化与El Niño、La Niña事件的发生分布具有很强的相关性,因此可以利用El Niño、La Niña指标来预测渔场的年间和月份间的变化。