黑龙江省未来30、50年气候预测

通过CCCma、CCSR、CSIRO、Gfdl和Hadley气候模式对黑龙江省其中包括齐齐哈尔、佳木斯、哈尔滨、牡丹江等4区未来50年(2005～2050年)，在GG、GS情景下数值模拟。结果表明(采用GS结果)，未来2030、2050年气温均有较大增高。其中2030年年平均气温可增高1．94℃；春季提高2．06℃：；夏季提高1．29℃；秋季提高1．79℃；冬季提高2．66℃，2050年又继续增加．年平均气温将提高2．42℃；春季提高2．13℃；夏季提高1．68℃；秋季提高2．56℃；冬季提高3．21℃。冬季是四季中增幅最大的季节，其次秋季、春季和夏季。如果按GG情景下，未来气温还要高出1℃。增温中心在西部齐齐哈尔，增温较小为牡丹江。从哈尔滨年蒸发量来看，2030年可增加11％，2050年可增加13％。     

The phytoplankton of some saline lakes in Central Asia

The Aral Sea, Lake Balkhash, and Lake Kamyslybas are closed lakes in Central Asia. They range from oligosaline to metasaline. The salinity of the Aral Sea has increased by more than 30 g L⁻¹ since widespread irrigation began in its catchment area. Few studies of the phytoplankton have been conducted on these lakes since extensive irrigation started. The investigation reported here compares the flora of phytoplankton in these saline lakes. In the Small Aral Sea, phytoplankton density gradually decreased with increasing electrical conductivity (EC) (∼ salinity), but there was no such relation in Lake Balkhash and Lake Kamyslybas. In the Aral Sea, Dinophyceae and Bacillariophyceae were frequently observed in most areas of high EC value, and Cyanophyceae were most conspicuous in the area of medium and lower EC values. In Lake Balkhash, Cyanophyceae were most conspicuous, but Chlorophyceae were also noticeable. Most Cyanophyceae in Aral Sea formed filaments with heterocysts. The distinct characteristic of the phytoplankton of the Lake Balkhash was that all dominant species form colonies covered with a gelatinous film. Siliceousplankton diversity gradually decreased with increasing EC values in the Aral Sea and Lake Balkhash.     

利用步长模拟对青藏高原涡度方差测量法的质量评价

利用痕迹模拟方法对青藏高原两处地方涡度方差的测量数据进行了质量分析，揭示了其空间和时间结构。分析表明高达1/3的测量没有达到必要的数据正确假设。尽管这样对潜热、CO2、动量通量的测量基本通过测试，可以适用于基础研究，但是经常发现特定的风矢量违背基本假设条件。感热通量的测量允许使用不间断的连续测量法，然而由于局地地形的影响少量评估指数未能合理解释，但能够指示出组织结构及用于导出边界层中尺度流体模型假说。     

2005年震情述评

据我国地震台网测定，2005年全球共发生7级以上地震16次（表1），最大地震为3月29日印尼苏门答腊岛西北海域8．5级地震（图1）。与2004年相比全球地震频次和能量释放均有所降低。2005年全球7级以上地震活动有以下特点。     

����ο���ܵ�ʵ�ֺ�ά��

??ITRF??WGS84??ο?????????????ο???????????????????????????????????Щ?????????????? ????????,??????°汾ITRF2005??????????     

青藏高原黑碳气溶胶传输及沉降的季节特征模拟分析

根据全球气溶胶气候模式GEM-AQ/EC的1995~2004年模拟,分析了青藏高原大气黑碳气溶胶的来源、传输及沉降季节特征。研究表明:青藏高原黑碳气溶胶主要来自自由对流层和大气边界层的输送。相对于自由对流层的黑碳输送,紧邻青藏高原的南亚、东亚以及东南亚大气边界层的输送更有效,它形成了青藏高原由北向南、自西往东黑碳气溶胶浓度和沉降明显递增的基本分布形态。横跨欧亚大陆自由对流层的黑碳气溶胶由西向东向青藏高原的输送全年不变,夏季输送路径最北但强度最弱,冬季路径最南而强度最强。大气边界层黑碳气溶胶的输送受控于亚洲季风环流变化,来自南亚的黑碳气溶胶在春季越过孟加拉湾传输进入高原东南部,夏季则可翻越喜马拉雅山抵达青藏高原南部腹地;同时我国中部排放的黑碳气溶胶也在东亚夏季风向北扩展中驱动它从东向西往青藏高原东北部传输。从秋季到冬季,随着夏季风撤退,南亚黑碳源区向青藏高原传输衰退,东亚冬季风的反气旋性环流的南侧及西南侧的偏东风携带秋季我国东南部源区和冬季东南亚源区黑碳气溶胶向青藏高原东南部传输。受青藏高原明显的暖湿季和干冷季气候影响,干湿沉降分别主导了青藏高原冬季和夏季黑碳沉降,夏季青藏高原黑碳气溶胶沉降总量大多超过8~10 kg·km-2,在高原东北部的最高值超过40 kg·km-2。冬季青藏高原黑碳气溶胶沉降量最低,大部地区黑碳沉降低于5 kg·km-2。青藏高原黑碳沉降的冬夏季节相差约为2~8倍。     

利用地学空间数据管理与分析系统GeoExpl 2005对磁测(△T)资料进行处理

通过地学空间数据管理与分析系统GeoExpl 2005,对磁测(△T)资料进行分析处理,用其结果来确定板状磁性体上顶地表投影位置和倾向,对磁性体进行定位,以指导探矿工程的布置,达到找矿的目的.     

基于ITRF2005框架的南美板块运动及形变分析

本文通过利用ITRF2005框架速度场以及IGS参考站近两年观测数据解算所得速度场对南美板块的运动及形变特征进行分析。结果表明,南美板块整体以约12.4mm/a的速率向北西方向运动,其欧拉矢量参数与NNR-NULVEL1A模型基本一致。形变特征表现为中南部区域西缘因纳兹卡板块俯冲向东凹陷,东侧受大西洋中脊海底扩张推力向西运动,东西向的挤压使其约以22mm/a的速度收缩并阻碍其北向运动。板块南端则受南极洲板块挤压向北西运动。     

Two new pulsating hot subdwarf stars from the Edinburgh-Cape survey

We report the discovery of very rapid pulsations in two hot subdwarf stars from the Edinburgh-Cape blue object survey. The short periods, small amplitudes and multiperiodicity establish these stars as members of the class of rapidly-pulsating sdB stars. The spectrograms of both stars, however, show relatively strong He  ii 4686 and they are therefore more properly classified as sdOB. The light curve of EC 01541−1409 is dominated by two strong (∼1 per cent) variations with frequencies near 7114 and 7870 μHz (periods near 140.6 and 127.1 s), though at least five frequencies are present with amplitudes above about 0.002 mag. The light curve of EC 22221−3152 appears to be generated by at least 10 frequencies in the range 5670–11850 μHz (about 175–85 s) with amplitudes between about 0.01 and 0.001 mag, including the first overtone of the strongest variation. Somewhat surprisingly, this number of frequencies is detectable in observing runs as short as 3 h, probably due to the fact that the detected frequencies are well-separated.