热带西太平洋暖池和副热带高压之间的关系

文中研究了热带西太平洋暖池和西太平洋副热带高压的季节性变化和年际变化关系。结果表明,西太平洋暖池面积和副热带高压面积指数季节变化趋势基本一致,暖池中心的纬向移动与副热带高压西伸脊点相反,而经向移动和５００ｈＰａ副热带高压脊平均位置的南北季节性变化非常一致。西太平洋副热带高压的年际变化落后暖池大约３个月左右,用暖池２８℃或２９℃面积指数可以很好地预测出当年６,７,８三个月西太平洋副热带高压的面积指数。     

南极长城站和中山站辐射特征的研究

对南极长城站和中山站1993～1994年辐射资料的分析表明:两站辐射分量的季节变化特征基本相似。但由于气候状况的差异,长城站到达地面的总辐射和吸收辐射分别为中山站的51%和42%。极昼期间（11～1月）中山站总辐射和紫外辐射总量均超过了青藏高原夏季（6～8月）的总量,两站净辐射夏半年为正,冬半年为负,显示出南极绿洲的辐射气候特点。     

登陆北上台风暴雨突发性增强的一种机制研究

采用一个三维混合模式对1992年8月30日至9月2日一次登陆北上台风暴雨过程进行了模拟。模式可以较准确地预报出与地面倒槽相一致的地面降水位置及降水量值。模拟的台风云系结构与卫星云图比较表明,外围云场与实例云况吻合很好,验证了本模式模拟卫星云图的能力,对卫星云图预报有实际意义;暴雨突然增幅的直接原因是高层冰云与低层供水云的突然北移重叠造成的。受地面倒槽附近强烈辐合抬升的动力作用,各相态云系的分布与垂直运动紧密相关;辐合线右侧的东南低空急流为降水的增幅及维持提供水汽来源;云的相变潜热非绝热加热作用对暴雨的增幅及维持具有正反馈作用,它对暴雨维持具有积极贡献。     

气候突变的聚类分析

气候数据是时间序列,是一类有序样品．本文给出了一种新的有序样品谱系聚类算法,先对数据进行平滑拟合,然后用聚类分析的方法分析了北半球的气候资料,证实了1920年为气候突变点．同时也找到了较低的各个层次上的突变点．     

海洋初始状态对预报2002/03年中太平洋型厄尔尼诺事件的作用

2002/03年厄尔尼诺事件,是暖海温中心出现在赤道中太平洋区域的一种新型厄尔尼诺,即中太平洋型厄尔尼诺。本文基于一个厄尔尼诺预测系统,利用三组回报试验来详细区分海洋表层和次表层初始状态对预报2002/03年中太平洋型厄尔尼诺事件的作用,并由此来探寻对预报厄尔尼诺演变过程最有利的初始条件。回报试验分为三组:(1)仅同化海表温度观测(sea surface temperature;简称SST)来优化海洋表层初始状态(Assim_SST);(2)仅同化海表高度观测(sea level;简称SL)来更新海洋次表层初始状态(Assim_SL);(3)同时同化SST和SL观测来一起更新海洋表层和次表层初始状态(Assim_SST+SL)。回报试验结果表明,三种不同的初始条件都可以使模式提前一年成功地预报2002/03年厄尔尼诺事件,并且"Assim_SST+SL"回报试验的效果最好。三组回报试验结果间的对比表明:海洋表层和次表层初始状态均对成功地预报该事件有重要作用,但其作用分别集中在事件发展的不同阶段。精确的海洋表层初始状态更容易激发模式预报出一次厄尔尼诺事件,而更合理的海洋次表层初始状态则能有效地提高厄尔尼诺事件预报的强度。     

Distribution and ecology of Nectocarcinus antarcticus and N. bennetti (Brachyura: Portunidae) in the New Zealand region

The distributions of two swimming crabs endemic to the New Zealand region are described, mostly from material obtained at 118 of 2544 New Zealand Oceanographic Institute benthic stations sampled.

Nectocarcinus antarcticus (Jacquinot) was found within the geographic limits 34°S‐51°S and 166° E‐176° W, with concentrations around Cook Strait, the Chatham Rise, Foveaux Strait, and the Auckland Is. N. bennetti (Takeda & Miyake) occurred between 44° S and 53° S, and 165° E and 180°, most frequently in the south and west, on the ‘highs’ of the Campbell Plateau. Although the distributions overlap between 44° S and 51° S, and this overlap zone produced most of the available material, only one joint occurrence of the two species was noted. This apparent separation was not satisfactorily explained by any of the ecological factors recorded. The depth ranges of both species were broadly similar (0–550 m for TV. antarcticus, 20–474 m for JV. bennetti); both were most frequently obtained at depths less than 200 m. Both occurred primarily on the coarser sediment grades, though N. antarcticus occupied a broader range of grades than N. bennetti.

The size ranges of the two species were similar; carapace lengths were 8.0–62.0 mm for N. antarcticus and 5.8–68.0 mm for N. bennetti. The larger specimens of both species were found towards the southern limits of distribution. Larger specimens of N. antarcticus were absent from depths greater than 120 m; smaller N. antarcticus and all N. bennetti occurred throughout their respective depth ranges. Ovigerous N. antarcticus (smallest, 8.8 mm carapace length) were obtained at depths of 17–263 m from May to October; ovigerous N. bennetti (smallest 36.1 mm) were from depths of 150–183 m in May only.     

虹鳟(Oncorhynchus mykiss)选育群体的血清类固醇激素周年变化

采用放射性免疫(RIA)和组织学切片技术,系统地研究了虹鳟(Oncorhynchus mykiss)选育群体的血清性类固醇激素周年变化与性腺发育特点的关系,以及血清中性类固醇激素雌二醇(E2)和睾酮(T)在雌雄亲本中的周年变化规律和生理作用。结果表明,虹鳟性腺发育可划分为6期。雌鱼血清中E2在10月(V期性腺)达到峰值,T浓度在11月达到峰值,而进入繁殖期后(11—12月)E2开始下降。雄鱼血清T浓度在11月达到最大值,E2在6月份达到峰值,在11月之后T开始下降。在各月份,雌鱼E2浓度水平远高于雄鱼,而雄鱼T浓度个别月份低于雌鱼。这些研究揭示出,测定血清性类固醇激素浓度水平可用于准确判断鱼类的生殖状态,且可为虹鳟家系选育出早熟亲本群体提供重要技术依据。     

On the recent warming of the southeastern Bering Sea shelf

During the last decade, the southeastern Bering Sea shelf has undergone a warming of 3 °C that is closely associated with a marked decrease of sea ice over the area. This shift in the physical environment of the shelf can be attributed to a combination of mechanisms, including the presence over the eastern Bering Sea shelf of a relatively mild air mass during the winter, especially from 2000 to 2005; a shorter ice season caused by a later fall transition and/or an earlier spring transition; increased flow through Unimak Pass during winter, which introduces warm Gulf of Alaska water onto the southeastern shelf; and the feedback mechanism whereby warmer ocean temperatures during the summer delay the southward advection of sea ice during winter. While the relative importance of these four mechanisms is difficult to quantify, it is evident that for sea ice to form, cold arctic winds must cool the water column. Sea ice is then formed in the polynyas during periods of cold north winds, and this ice is advected southward over the eastern shelf. The other three mechanisms can modify ice formation and melt, and hence its extent. In combination, these four mechanisms have served to temporally and spatially limit ice during the 5-year period (2001–2005). Warming of the eastern Bering Sea shelf could have profound influences on the ecosystem of the Bering Sea—from modification of the timing of the spring phytoplankton bloom to the northward advance of subarctic species and the northward retreat of arctic species.     

陶诗言先生在中国暴雨发生条件和机制研究中的贡献

作者在1998年庆贺陶诗言先生八十华诞的文集中曾专题阐述和评价了陶先生对中国暴雨研究的贡献。 至今十五年过去了,陶诗言先生虽已于2012年仙逝,但其深邃的科学思想依然闪烁着智慧的火花。他在中国暴雨研究中留下的宝贵遗产不但深刻影响过去和现代两代人的暴雨研究和业务发展,而且也将继续影响将来的中国暴雨研究。本文是对陶诗言先生在中国暴雨的研究中所作的贡献并结合现代研究的成果作进一步介绍和评价。主要集中在暴雨发生的动力和热力条件与机理方面。全文内容包括六个方面:（1）季节突变对中国梅雨爆发的影响;（2）暴雨发生的多尺度相互作用;（3）暖湿季风输送带对北方大暴雨的影响;（4）高空急流对暴雨的作用;（5）暴雨和强对流发生的物理条件;（6）地形对暴雨的作用     

西北太平洋海域风浪、涌浪、混合浪波浪能资源特征

用ECMWF的ERA-40海浪再分析资料,应用波浪能流密度计算方法,对西北太平洋海域的风浪能、涌浪能、混合浪能展开研究。结果表明:(1)波浪能流密度呈现出显著季节性差异。混合浪能流密度表现为冬高夏低;春、夏、秋季的涌浪能流密度明显大于风浪能流密度,冬季相反;(2)混合浪能流密度的大值区主要分布于阿留申群岛附近海域,高值中心可达60 kW/m以上;近海的大值区主要分布于琉球群岛—巴士海峡—传统的南海大风区一带,年平均值在4 kW/m以上,南海北部可达12 kW/m以上;(3)黄渤海的涌浪和混合浪能流密度峰值出现在8—9月,波谷出现在6月。风浪能流密度峰值出现在11月—次年3月,波谷出现在6—8月,均呈现双峰型月变化特征。东海、南海北部、南海中南部海域能流密度的月变化特征相似,都为双峰型,12月—次年4月的能流密度整体较高,波峰出现在12月,波谷出现在5—7月;(4)2 kW/m以上混合浪能流密度出现的频率较高,近海低于大洋;(5)0.5 m以上有效波高出现的频率都非常高,中国近海稍低于大洋;(6)涌浪能流密度的稳定性明显好于风浪能流密度;大洋的能流密度稳定性明显强于近岸。1月份能流密度的稳定性最好,4月和7月次之,10月的稳定性最差。