伴随法在潮汐和海温数值计算中的应用研究

变分数据同化中的伴随法可实现数值模型与观测数据的拟合。随着物理海洋数值计算和数值预报业务的不断发展，其具有广阔的应用前景。本文主要研究关于伴随数据同化的有关理论及其在物理海洋数值模型中的应用。本文介绍了变分伴随数据同化的基本原理，从模型方程的连续和离散形式出发讨论采用两种不同的方法推导伴随方程，一是拉格朗日乘子（Lagrange multiplier）法；二是基于泛函的Gateaux微分概念的方法，这里简称Gateaux微分法。文中讨论了导出离散伴随模型方程和目标函数梯度的两种不同途径，其中一种途径是由连续的正模型得到连续的伴随模型及连续的目标函数梯度表达式，然后再对伴随模型和目标函数梯度进行差分离散（简称“伴随的差分”）；另外一种途径是由离散的正模型直接导出离散的伴随模型及梯度表达式（简称“差分的伴随”）。目前尽管人们比较一致的看法是应该采用后一种途径，即建立伴随模型系统应该采用“差分的伴随”，但对由这两种途径建立的伴随系统的相互关系，人们探讨的并不多。本文利用了简单的模型对该问题进行了研究。另外，对有关初始猜测和伴随优化系统的多解性问题进行了探讨。本文着重研究并实现了利用伴随法优化非线性潮汐模型的开边界条件。其中采用的二维非线性浅水模型既考虑非线性底磨擦和侧向粘性涡动混合，又包括非线性平流项；离散伴随模型的建立是基于ADI格式（不受CFL条件限制），改善了变分伴随数据同化过程中计算量和计算存储问题，使之减小若干倍（约5～7倍），从而使得模式适于业务化的需求，具有实用价值；同化过程中使用的观测数据既包括常规验潮站水位观测资料，又包括TOPEX/POSEIDON卫星测高数据。实测数据同化数值试验表明，开边界条件的最优控制对数值计算结果有一定程度的改进。本文还探讨了将伴随法应用于海表面温度（SST）的数值预报中。其中采用的SST数值预报模型是基于国家“七五”期间科技攻关项目《中国近海海表面温度短期数值预报模式》。文中利用船舶报SST观测数据进行伴随数据同化试验，以优化初始场，其结果是比较满意的，表明变分数据同化对改进SST数值预报的效果是比较明显的，将伴随法引入中国海域SST数值预报业务化中是可行的。本文最后讨论了伴随数据同化中尚待深入研究的问题，着重指出了在物理海洋学领域开展二阶伴随模式应用研究的内容和必要性。

中国以礼草属新分类群

本文报道了禾本科以礼草属二新种及二新变种，即稀穗以礼草Kengyilia laxistachya L.B.Cai et D. F. Cui，和静以礼草Kengyilia hejingensis L.B.Cai et D. F. Cui，显芒以礼草Kengyilia hirsute var. obviaristata L. B. Cai和毛鞘以礼草Kengyilia rigiadula var. trichocolea L. B. Cai.

西藏高原草原化嵩草草甸生态系统呼吸及碳平衡

The soil respiration and net ecosystem productivity of Kobresia littledalei meadow ecosystem was investigated at Dangxiong grassland station, one grassland field station of Lhasa Plateau Ecosystem Research Station. Soil respiration and soil heterotrophic respiration were measured at the same time by using Li6400-09 chamber in growing season of year 2004. The response of soil respiration and its components, i.e. microbial heterotrophic respiration and root respiration to biotic and abiotic factors were addressed. We studied the daily and seasonal variation on Net Ecosystem carbon Exchange (NEE) measured by eddy covariance equipments and then the regression models between the NEE and the soil temperature. Based on the researches, we analyzed the seasonal variation in grass biomass and estimated NEE combined the Net Ecosystem Productivity with heterogeneous respiration and then assessed the whether the area is carbon source or carbon sink. 1.Above-ground biomass was accumulated since the grass growth started from May; On early September the biomass reached maximum and then decreased. The aboveground net primary production (ANPP) was 150.88 g m~" in 2004. The under-ground biomass reached maximum when the aboveground start to die back. Over 80% of the grass root distributed at the soil depth from 0 to 20cm. The underground NPP was 1235.04 g m"2.. Therefore annual NPP wasl.385X103kg ha"1, i.e.6236.6 kg C ha"1. 2. The daily variation of soil respiration showed single peak curve with maximum mostly at noon and minimum 4:00-6:00 am. Daily variations were greater in June, July and August than those in September and October. Soil respiration had strong correlation with soil temperature at 5cm depth while had weaker correlation with soil moisture, air temperature, surface soil temperature, and so on. But since early September the soil respiration had a obviously correlation with soil moisture at 5cm depth. Biomass had a obviously linearity correlation with soil respiration at 30th June, 20th August, and the daytime of 27th September except at 23lh October and at nighttime of 27th September. We established the soil respiration responding to the soil temperature and to estimate the respiration variation during monsoon season (from June through August) and dry season (May, September and October). The regression between soil respiration and 5cm soil temperature were: monsoon season (June through August), Y=0.592expfl()932\ By estimating , the soil daily respiration in monsoon season is 7.798gCO2m"2 and total soil respiration is 717.44 gCC^m" , and the value of Cho is 2.54; dry season (May, September and October), Y=0.34exp°'085\ the soil daily respiration is 3.355gCO2m~2 and total soil respiration is 308.61 gCC^m", and the value of Cho is 2.34. So the total soil respiration in the grown season (From May to October) is 1026.1 g CO2IT1"2. 3. Soil heterogeneous respiration had a strong correlation with soil temperature especially with soil temperature at 5cm depth. The variation range in soil heterogeneous respiration was widely. The regression between soil heterogeneous respiration and 5cm soil temperature is: monsoon season, Y=0.106exp ' 3x; dry season, Y=0.18exp°"0833x.By estimating total soil heterotrophic respiration in monsoon season is 219.6 gCC^m"2, and the value of Cho is 3.78; While total soil heterogeneous respiration in dry season is 286.2 gCCbm"2, and the value of Cho is 2.3. The total soil heterotrophic respiration of the year is 1379.4kg C ha"1. 4. We estimated the root respiration through the balance between soil respiration and the soil heterotrophic respiration. The contribution of root respiration to total respiration was different during different period: re-greening period 48%; growing period 69%; die-back period 48%. 5. The Ecosystem respiration was relatively strong from May to October, and of which the proportion in total was 97.4%.The total respiration of Ecosystem was 369.6 g CO2 m" .we got the model of grass respiration respond to the soil temperature at 5cm depth and then estimated the daytime grass respiration, plus the nighttime NEE and daytime soil respiration. But when we estimated the grass respiration, we found the result was negative, so the estimating value in this way was not close. 6. The estimating of carbon pool or carbon sink. The NPP minus the soil heterogeneous respiration was the NEE, and it was 4857.3kg C o ha"1, which indicated that the area was the carbon sink.

Charles Dickens

Pykett, L. (2002). Charles Dickens. Critical Issues. New York: Palgrave Macmillan. RAE2008

An heroic bishop : the life-story of French of Lahore

http://www.archive.org/details/anheroicbishopli00stocuoft

Support vector machines for regression and applications to software quality prediction

Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.

Mapping the Governance Reform of Welfare to Work in Britain under New Labour

This article draws on Newman's (2001, 2007) typology of the modernization of governance under New Labor, to examine the development of British welfare to work administration. Concentrating on the delivery of active labor market policy, the article suggests network forms of governance occupy a marginal role in welfare to work delivery. Managerialist and hierarchical forms of governance dominate administration of activation policy. In accordance with UK tradition, a national centralized, top down system exercises control of social security and employment services administration, but increasingly seeks to realize its goals through a market system of delivery.