用Matlab中的Neural Network Toolbox仿真赤道东太平洋SST的预报模型

基于ＮＣＥＰ／ＮＣＡＲ再分析资料和ＣＯＡＤＳ海洋资料中的全球月平均海平面气压场、８５０hPa纬向风场及海洋温度场，利用Ｍatlab中的Ｎeural Network Toolbox仿真环境和ＢＰ模型改进算法比较准确地仿真和反演出了南方涛动指数、赤道纬向风指数和滞后的赤道东太平洋海温之间的动力结构和预报模型。该模型具有很好的拟合精度和可行的预报效果。可在一定时效内预测赤道东太平洋月平均海温的变化趋势。由于所建系统是具有直接因果关系的预报模型，因此不仅可直接用于预测，而且可有效避免类拟非线性微分方程组在积分过程中由于对初值敏感性而可能产生的对预报结果的不确定性。     

Heavy metals in marine sediments of Taranto Gulf (Ionian Sea, Southern Italy)

Al, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Ti and Zn concentrations have been determined in surface sediment samples collected in the Taranto Gulf (Ionian Sea, Southern Italy) in order to evaluate their levels and spatial distribution in this important area of the Mediterranean Sea. For various metals, the geoaccumulation index has been calculated as a criterion to assess if their concentrations represent contamination levels or can be considered as background levels. The results show that metals concentrations in sediments can be considered near the background levels found in the Mediterranean Sea.Analytical results have been elaborated by using a Geographical Information System (GIS) software to show metals accumulation areas. Using multivariate statistical analysis, we evaluate the possibility to distinguish the sampling stations, in relation to their geographical position. Results have showed metals distribution in the Taranto Gulf is principally influenced by industrial and urban wastes, located mostly in the northern coastal area of the Ionian Sea. Rivers in the Basilicata region and prevailing anticlockwise marine currents are further factors influencing metal accumulation in sediments.     

边坡整体稳定的可靠性分析方法

边坡整体滑动稳定性的可靠性分析是建立在土体具有的抗力大于荷载效应的概率基础上进行设计和校验的。在条分法的基础上推导出了进行边坡稳定可靠性分析的统一极限状态方程 ,将土的容重γ、内摩擦角φ、粘聚力 c作为随机变量 ,当其为非正态分布时 ,进行当量正态化 ,考虑变量相关的情况 ,用简化相关法对随机变量进行统计分析 ,并以 Bishop圆弧滑动法为例 ,用 JC法求解边坡的可靠性指标及失效概率 ,给出计算安全系数和可靠性指标的算法程序。并就影响可靠性指标的因素如抗剪强度指标、变量分布形式、土性参数的变异性等进行了讨论。     

盐度对双棘黄姑鱼仔鱼活力及仔稚鱼生长的影响

分别用不同盐度梯度海水对双棘黄姑鱼仔鱼进行饲养试验。结果表明：盐度为17．0．22．0、27．0．31．0～33．0的4个试验组仔鱼的不投饵存活系数分别为5．38、7.35、6.46、6．18；各盐度组仔稚鱼的生长速度没有显著差异（P〉0．05），各组仔鱼经25d的培养，其平均全长为18．8～19．2mm；盐度22．0及27．0的海水中仔稚鱼呈较高的存活率，各盐度组的平均存活率为36、0％、48．5％、46．7％和39．2％．     

琼州海峡岸礁潮间带生物

本文记录了2000年7月琼州海峡西口雷州半岛灯楼角珊瑚岸礁调查采集的25种造礁石珊瑚，以及栖息于湖间带的7类39科88种底栖生物，其大多数种类属于印度-西太平洋热带区系。优势类群是软体动物和节肢动物。珊瑚礁段底栖生物的平均生物量、栖息密度和多样性值分别为1173．30g／m^2，790．0个／m^2和5．69，由于造礁石珊瑚的存在为其他底栖生物提供了良好的生态环境，从而丰富了本区底栖生物的种类组成、数量、分布和群落结构。     

辽东湾北部海域营养状况与趋势评价

根据 1999-2006 年 6-8 月的调查数据,分析辽东湾北部海域的营养水平及变化趋势,以了解辽东湾北部海域营养水平的分布特点及污染状况.由 E 值和 CN/CP 值的总体评价结果来看,辽河口、双台子河口和大凌河口海域的富营养化程度较高,属于磷中等限制潜在性富营养区,而锦州湾海域污染相对较轻,属于中度营养区;在时空分布上,辽东湾北部海域 1999 年与 2006 年污染较为严重,中间年份污染相对较轻.针对辽东湾的具体环境用 CN/CP 值的评价模式更能揭示出营养盐限制对富营养化的影响.     

华北地区夏季降雨量与南海海温长期变化的关系

比较了华北地区7个站与17个站1951-1997年夏季（6，7，8月）降雨量与气候随时间的变化特征，并对其成因作了探讨。结果表明，用北京、天津、邢台、烟台、郑州、太原和济南等7个站可代表该地区夏季降雨量与气候的多尺度变化特征，过去47a该地区依次经历了湿凉、湿热、湿凉、干热、湿热几个时期，降雨量的长期变化与南海前冬（1-2月）海温成负相关。前冬南海海温偏高，意味着初夏南海地区大气对流低频振动偏弱，南海夏季风爆发较晚，西南季风较弱，夏季西太平洋副高位置偏南，华北地区大气低层北风加强，华北地区夏季少雨，前冬南海海温偏低时情况则相反，考虑冬季（1-2月）南海南温和7-8月西太平洋副高脊线位置（纬度）的影响用均生函数建模，试验结果与用子波变换重构方法考虑华北地区夏季降雨量的变化趋势比较，二者相吻合，预测试验结果与过去3a的实况基本一致。     

利用HOAPS资料研究南海海气界面热通量时空分布

基于第二版本HOAPS(Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data)潜热、感热和海表温度(SST)3个参量的15 a(1988~2002年)逐月平均资料,利用经验正交方法分解分析了这3个参量在南海的时空分布.结果表明,在夏季模态,潜热表现为南高北低,感热表现为中间低两边高,两者主要都是海洋向大气输送热量,但大气有时也向南海中部输送感热;在冬季模态,潜热和感热的高值区都在南海北部,东北部有一强中心,该中心主要是由风场引起的;夏季SST的变化导致全年SST呈准半年周期变化.冬季SST的变化滞后于潜热变化1个月;除夏季和冬季模态外,冬夏转换季节模态也十分明显;HOAPS与NCEP(National Center of Environment Prediction)资料相比,两者3个参量的时空分布大体一致,区别在于HOAPS资料能更好地反映参量的一些细微特征.     

Difference characteristics of sea surface temperature observed by GLI and AMSR aboard ADEOS-II

This study compares infrared and microwave measurements of sea surface temperature (SST) obtained by a single satellite. The simultaneous observation from the Global Imager (GLI: infrared) and the Advanced Microwave Scanning Radiometer (AMSR: microwave) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) provided an opportunity for the intercomparison. The GLI-and AMSR-derived SSTs from April to October 2003 are analyzed with other ancillary data including surface wind speed and water vapor retrieved by AMSR and SeaWinds on ADEOS-II. We found no measurable bias (defined as GLI minus AMSR), while the standard deviation of difference is less than 1°C. In low water vapor conditions, the GLI SST has a positive bias less than 0.2°C, and in high water vapor conditions, it has a negative (positive) bias during the daytime (nighttime). The low spatial resolution of AMSR is another factor underlying the geographical distribution of the differences. The cloud detection problem in the GLI algorithm also affects the difference. The large differences in high-latitude region during the nighttime might be due to the GLI cloud-detection algorithm. AMSR SST has a negative bias during the daytime with low wind speed (less than 7 ms⁻¹), which might be related to the correction for surface wind effects in the AMSR SST algorithm.     

Validity of sea surface temperature observed with the TRITON buoy under diurnal heating conditions

In order to investigate the validity of buoy-observed sea surface temperature (SST), we installed special instruments to measure near-surface ocean temperature on the TRITON buoy moored at 2.07°N, 138.06°E from 2 to 13 March 2004, in addition to a standard buoy sensor for the regular SST measurement at 1.5-m depth. Large diurnal SST variations were observed during this period, and the variations of the temperatures at about 0.3-m depth could be approximately simulated by a one-dimensional numerical model. However, there was a notable discrepancy between the buoy-observed 1.5-m-depth SST (SST_1.5m) and the corresponding model-simulated temperature only during the daytime when the diurnal rise was large. The evaluation of the heat balance in the sea surface layer showed that the diurnal rise of the SST_1.5m in these cases could not be accounted for by solar heating alone. We examined the depth of the SST_1.5m sensor and the near-surface temperature observed from a ship near the buoy, and came to the conclusion that the solar heating of the buoy hull and/or a disturbance in the temperature field around the buoy hull would contribute to the excessive diurnal rise of the SST_1.5m observed with the TRITON buoy. However, the temperature around the hull was not sufficiently homogenized, as suggested in a previous paper. For the diurnal rise of the SST_1.5m exceeding 0.5 K, the daytime buoy data became doubtful, through dynamics that remain to be clarified. A simple formula is proposed to correct the unexpected diurnal amplitude of the buoy SST_1.5m.