室外大池马氏珠母贝育苗试验

本试验利用一个室外露天水容量为187立方米的水泥池进行马氏珠母贝人工育苗,一次育出贝苗5065万只,平均每立方米水体收贝苗27.08万只。室外大池育苗具有耗饵量少,节约人力,培育的幼虫和贝苗生长快和产苗量大等优点,能够迅速提高贝苗总产量,解决目前存在的贝苗(?)足的困难,值得提倡推广。     

Zircon U-Pb geochronology of Early Jurassic-Late cretaceous volcanic rocks in North Yellow Sea BasinEI北大核心CSCD

The X-drilling cores of the North Yellow Sea basin reveal two sets of Mesozoic clastic rocks, which are the dark rocks in lower part and the red rocks in upper part, respectively. There are two layers of volcanic rocks at the bottom and the upper part of the dark rock unit. The volcanic rocks at the bottom part are trachytic dacite while rocks at the upper part are clastic dacite. The zircon grains from the upper and lower units of volcanic rocks are euhedral-subhedral columnar crystals and show oscillatory zoning on cathodoluminescence images. 22 tests of zircons in the trachytic dacite from the bottom part yield an age of 141-151 Ma, with weighted mean 206Pb/238U age of 145±2 Ma. Whereas 18 tests of zircons from the sample at the upper part give 206Pb/238U ages around 139-149 Ma with weighted mean 206Pb/238U age of 141±2 Ma, which implies that the X well volcanic rocks belong to Late Jurassic-Early Cretaceous. Comparing with the age and geochemical characteristics of the Mesozoic igneous rocks in Shandong peninsula, we suggest that the igneous rocks from both the North Yellow Sea basin and Jiaolai basin were formed under same dynamic setting, i.e., the subduction related volcano arc and back-arc extension. ©, 2015, Science Press. All right reserved.     

基于不同权重的栖息地指数模型预报阿根廷滑柔鱼中心渔场

本文根据2003-2009年1-5月和2011年1-5月西南大西洋海域阿根廷滑柔鱼(Illex argentinus)的生产数据,结合遥感获得的海表面温度(SST)和海表面高度(SSH)数据,利用不同权重的栖息地指数模型来预报阿根廷滑柔鱼的中心渔场。采用外包络法,利用作业次数与SST、SSH建立适应性指数(SI)模型,依据作业次数比重和产量比重来比较不同权重的算术加权模型(AWM),从而筛选出最佳模型,并对最佳模型进行验证。结果显示,确定AWM(a=0.3,SST权重为0.3,SSH的权重为0.7)为最佳模型,当栖息地适应性指数(HSI)大于0.6时,作业次数的比重为93.23%,产量比重为89.28%,当HSI小于0.4时,作业次数的比重为2.12%,产量比重为3.35%。利用2011年1-5月的生产数据和环境数据对AWM(a=0.3)进行验证,结果显示,在HSI大于0.6的海域,各月作业次数比重均在91%以上,产量比重均在95%以上。研究表明,在阿根廷滑柔鱼渔场形成中SSH比SST更为重要,基于SST和SSH的AWM(a=0.3)能够较好地预测西南大西洋阿根廷滑柔鱼的中心渔场。     

一种改进的病态问题截断奇异值方法

截断奇异值分解方法是通过删除较小的奇异值及对应的特征向量获得病态模型的稳定解.文中首先将线性病态模型表示成近似的秩亏模型,证明秩亏模型的最小范数最小二乘解与截断奇异值解的等价性;然后,根据模型参数间的先验信息,以参数的线性函数的二次范数最小为目标,在残差范数最小条件下给出改进的最小范数最小二乘解,其实质是截断奇异值解的修正.截断参数的选取采用L曲线法.计算实例表明,修正的截断奇异值算法稳定有效,比正则化解和截断奇异值解具有更小的均方误差.     

太平洋潜热通量及其与黄淮夏季降水的关系

研究了1979—2010年太平洋潜热通量的变化特征及其与中国黄淮夏季降水的关系。结果表明,潜热通量的气候场和方差场均存在着明显的季节变化,且各季节气候场的极值中心也是变化幅度较大的区域。黄淮地区降水与前期春季的潜热场相关性最好。定义了黄淮夏季降水指数来研究影响降水的潜热场关键区,发现春季潜热关键区为10°~20°N之间的中东太平洋和热带东太平洋沿岸海区。春季当上述两个海区净潜热通量增多时,后期夏季500hPa和850hPa位势高度异常场中,在太平洋西海岸-阿拉斯加南部一线上均表现为"正—负—正"的分布型,黄淮降水偏多。     

丽水市旅游气候舒适度分析

采用人体舒适度气象指数（BCMI）、寒冷指数（CI）、温湿指数（THI）和度假气候指数（HCI）等4个综合性的气候指标,对丽水市的旅游气候舒适度进行了分析评价,并着重对比分析了BCMI和HCI对旅游气候适宜性的表征能力。结果表明：丽水市全年有8个月BCMI处在4～6级之间,属一类气候适宜区;冬季CI值较低,无严寒现象,夏季低海拔地区THI值偏高,但海拔600 m以上地区（约占市域面积6成）THI值较低,适宜“避暑纳凉”;HCI比传统的BCMI表现的更客观、更全面,它不仅考虑了气候的热舒适性影响,还考虑了降水和云量对旅游出行及观光的影响,且就时间尺度而言,HCI更适合旅游舒适度逐日预报的开展。     

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.