携着环保之梦创业 怀着祖国之心献力——专访WWB株式会社社长龙润生

全球变暖、臭氧层破坏、酸雨、淡水资源危机、能源短缺、森林资源锐减、土地荒漠化、物种加速灭绝、垃圾成灾、有毒化学品污染等环境问题正在威胁着地球和人类,环境治理与保护已经成为全球共识,并且迫在眉睫。看似离我们生活十分遥远的北极,也受到了环境问题的波及。如果环境得不到合理治理和保护,短短不到百年时间,北极圈的海冰就会消逝。

Web服务在工程技术领域中的应用

Web服务相对原有的组件技术而言有其自身的特点和优势 ,是一种新型的分布式组件技术 ,但有关的核心技术和协议还有待进一步发展和标准化。对Web服务的概念及其体系结构、Web服务的适用场合作了阐述。以滚动轴承的刚度计算为研究实例 ,详细介绍了Web服务在工程技术领域中的应用过程。

西风爆发事件对暖池厄尔尼诺和冷舌厄尔尼诺的作用——一个概念模型得到的结果

本文通过1个概念模型讨论了西风爆发事件对暖池厄尔尼诺与冷舌厄尔尼诺两种事件的作用,并讨论了它们对应的物理机制。结果表明,由西风爆发所诱导的纬向平流异常和海洋波动对厄尔尼诺的多样性有着至关重要的作用。由于模型包含了最基本的海-洋与大气物理变量及其相互作用机制,本结果可为解释西风爆发事件对厄尔尼诺多样性影响研究提供最基本的框架。

NCEP/CFSR再分析耦合资料中MJO对ENSO的影响研究

基于1979—2008年NCEP/CFSR再分析耦合数据集,研究了冬季MJO对ENSO事件的影响。结果表明,在年际时间尺度以及长期的年代际时间尺度上,热带印度洋MJO活动的强弱性都可以影响热带中东太平洋ENSO事件的发生和发展。在年际时间尺度上,ENSO发生前期征兆的赤道中东太平洋的西风爆发事件(Westerly Wind Burst,WWB),作为MJO影响ENSO的主要途径,存在着显著的次季节时间尺度的变化。相对于气候平均的赤道太平洋西部暖池区上升而东部下沉的Walker环流,MJO正位相东传后的西风异常,减弱了低层东风和赤道东太平洋海水上翻。这一上升海流的减弱导致了中东赤道太平洋的海温升高,从而有利于ENSO暖海温事件的发生。而在年代际时间尺度上,MJO范围和强度在1998年前后出现了明显的转变,1998年之前MJO的东移范围更东,强度更强,从而导致了西太平洋西风爆发区的次季节西风异常事件更加显著,在Bjeknes正反馈机制下对应了年代际时间尺度下的强尼诺事件出现,1998年之后则与之相反。冬季MJO对ENSO影响的这一年代际特征主要体现在晚冬季节,而在早冬伴随着印度洋的增暖,MJO强度一直在逐年增加。

西风爆发在CMIP5中的模拟评价

赤道西风爆发现象(西风爆发)是指赤道表面西风突然增大的现象,已有研究表明赤道太平洋西风爆发与ENSO (El Ni?o-Southern Oscillation)有密切的关系。本文就西风爆发现象在CMIP5中的模拟情况进行了相关评价,并将其与观测结果进行对比;同时对西风爆发与ENSO的关系、西风爆发与MJO的关系进行了细致的分析与评价。研究结果表明,模式可以很好地再现西风爆发随厄尔尼诺事件发生而向东移动的现象,这主要是由于赤道太平洋西风爆发与赤道太平洋海表温度有很好的对应关系。在大部分模式中,西风爆发领先于厄尔尼诺的发生,并对厄尔尼诺的发展有着相应的影响。与前人的研究结果不同,利用蒙特卡洛验证法证明MJO不能显著地增加西风爆发发生的概率,这一点也在大部分CMIP5模式中有所体现。

A Statistical Comparison of the Westerly Wind Bursts between the Positive and Negative Phases of the PDO

To understand the diversity of the El Ni?o–Southern Oscillation(ENSO)under the background of Pacific decadal oscillation(PDO)during recent decades,characteristics of westerly wind bursts(WWBs)during positive and negative phases of the PDO were analyzed.It is shown that,during the ENSO developing period,the El Ni?o evolution may be affected by stronger or more frequent WWBs in the positive PDO phase than in the negative PDO phase.The sustained effects of atmospheric dynamics on the equatorial ocean can be indicated by the accumulated WWB strength,which contains most WWB characteristics,including the accumulated days,occurrence frequency,strength,and spatial range of WWBs.The synoptic/climate systems that are directly related to WWBs show a wider spatial distribution in the positive PDO phase than in the negative PDO phase.

Genesis of the 2014–2016 El Nio events

The 2015/2016 El Nio was one of the strongest El Nio events in history, and this strong event was preceded by a weak El Nio in 2014. This study systematically analyzed the dynamical processes responsible for the genesis of these events. It was found that the weak 2014 El Nio had two warming phases, the spring-summer warming was produced by zonal advection and downwelling Kelvin waves driven by westerly wind bursts(WWBs), and the autumn-winter warming was produced by meridional advection, surface heating as well as downwelling Kelvin waves. The 2015/2016 extreme El Nio, on the other hand, was primarily a result of sustained zonal advection and downwelling Kelvin waves driven by a series of WWBs, with enhancement from the Bjerknes positive feedback. The vast difference between these two El Nio events mainly came from the different amount of WWBs in 2014 and 2015. As compared to the 1982/1983 and 1997/1998 extreme El Nio events, the 2015/2016 El Nio exhibited some distinctive characteristics in its genesis and spatial pattern. We need to include the effects of WWBs to the theoretical framework of El Nio to explain these characteristics, and to improve our understanding and prediction of El Nio.

A New Equatorial Oscillation Index for Better Describing ENSO and Westerly Wind Bursts

An Equatorial Oscillation Index(EOI) is defined, based on the zonal gradient of sea surface pressure between the western Pacific and eastern Pacific along the equator, to describe the distribution of wind and pressure within the equatorial Pacific. The EOI has a stronger correlation with the Ni?o3.4 sea surface temperature anomaly(SSTA), as well as with westerly/easterly wind bursts(WWBs/EWBs), showing a superiority over the Southern Oscillation Index(SOI). In general, the EOI is consistent with the SOI, both of which reflect large-scale sea level pressure oscillations. However, when there are inconsistent SSTAs between the equator and subtropical regions, the SOI may contrast with the EOI due to the reverse changes in sea level pressure in the subtropical regions. As a result, the SOI fails to match the pattern of El Ni?o, while the EOI can still match it well. Hence, the EOI can better describe the variability of the Ni?o3.4 SSTA and WWBs/EWBs. The correlation between the SOI and Ni?o3.4 SSTA falls to its minimum in May, due to the large one-month changes of sea level pressure from April to May in the subtropical southern Pacific, which may be related to the spring predictability barrier(SPB). The newly defined EOI may be helpful for monitoring El Ni?o–Southern Oscillation(ENSO) and predicting ENSO.