THE RELATIONSHIP BETWEEN SCS SUMMER MONSOON INTENSITY AND OCEANIC THERMODYNAMIC VARIABLES AT DIFFERENT TIME SCALE

The oscillation characteristics of 1948 - 2003 South China Sea (SCS) summer monsoon intensity (SCSSMI) is analyzed by wavelet transform and the relationship between SCSSMI filtered by Lanczos filter at different time scale and oceanic thermal conditions is studied. The results show that SCSSMI exhibits dominant interannual (about 4 a), decadal (about 9 a) and interdecadal (about 38 a) oscillation periods. The interannual variation is the strongest and the interdecadal variation the weakest. The region of significant correlation between SCS summer monsoon intensity and oceanic thermodynamic variables at different time scale is greatly different. Significant correlation area of interannual variation of SCSSMI is concentrated in near equatorial region. Corresponding correlation displays quasi-biannual variability. If positive anomalies of SST and the depth of thermocline happen in eastern equatorial Indian Ocean and western equatorial Pacific, and negative anomalies of SST and the depth of thermocline happen in western equatorial Indian Ocean and eastern equatorial Pacific in previous autumn and winter, the interannual variation of SCSSMI will enhance. If the condition is contrary, interannual variation of SCSSMI will weaken. The interannual variation of SCSSMI will influence SST. The region surrounding SCS and east of Australia shows significantly negative correlation in autumn, and significantly positive correlation exhibits in west equatorial Indian Ocean, eastern equatorial Pacific and equatorial Atlantic in winter. The decadal variation of SCSSMI is modulated by PDO. Interdecadal variation of SCSSMI is relevant to the global warming and PDO.     

Spectrophotometric Variability of Mira

Data from the Pulkovo spectrophotometric data base on the absolute quasimonochromatic fluxes from oCet in the 320–1080 nm range are used to determine the physical parameters of this star in different phases of its light curve. The continuum emission layer is found to expand between the phases of the cycle corresponding to the rising and falling branches of the light curve. The average expansion velocity is 32 km/s. By the time the star’s brightness has fallen by roughly three magnitudes, its radius has increased by almost a factor of three. Over this same time the temperature of the layer has fallen from 3000 K to 2200 K. For this expansion velocity, the calculated mass rate loss is ⊙ M /year.__________Translated from Astrofizika, Vol. 48, No. 2, pp. 175–189 (May 2005).     

Metallicity of clusters from RRab pulsators: results of an automatic analysis

The stability of massive stars is re-examined with respect to an adiabatic dynamical instability discovered by Stothers & Chin. An adiabatic stability analysis is performed, its validity for the objects being considered is discussed, and the relation between the mean adiabatic index and adiabatic stability is commented on. As the results of Stothers & Chin could not be confirmed, we suspect that luminous blue variable instability is due to non-adiabatic effects.     

Efficiency of kriging estimation for square, triangular, and hexagonal grids

Although several researchers have pointed out some advantages and disadvantages of various soil sampling designs in the presence of spatial autocorrelation, a more detailed study is presented herein which examines the geometrical relationship of three sampling designs, namely the square, the equilateral triangle, and the regular hexagon. Both advantages and disadvantages exist in the use of these designs with respect to estimation of the semivariogram and their effect on the mean square error or variance of error. This research could be used to design optimal sampling strategies; it is based on the theory of regionalized variables, in which the intrinsic hypothesis is satisfied. Among alternative designs, an equilateral triangle design gives the most reliable estimate of the semivariogram. It also gives the minimum maximum mean square error of point estimation of the concentration over the other two designs for the same number of measurements when the nugget effect is small relative to the variance. If the nugget effect is large (.90 ² or more), and the linear sampling density is >0.85r where r is the range, the hexagonal design is best. This study computes and compares the maximum mean square error for each of these designs.     

扩展水凝物控制变量的雷达资料同化对台风“天鸽”数值模拟的影响

利用WRF(Weather Research and Forecast)模式及WRFDA(WRF model data assimilation system)系统,针对2017年台风“天鸽”个例通过同化雷达径向速度(Vr)和反射率因子(RF),研究水凝物控制变量的雷达资料同化对台风分析预报的影响。研究表明：雷达径向速度的直接同化有效地改进了模式初始场中台风涡旋区的中小尺度信息,分析场中产生了气旋性的风场增量,对模式背景场中的台风有显著增强作用。通过在传统控制变量中扩展针对水凝物的控制变量可有效地同化雷达反射率因子资料,对初始场的水物质进行调整,并对随后确定性预报的台风路径和强度都有一定的正效果。此外,相比没有水凝物控制变量的雷达同化试验,加入了水凝物控制变量的雷达资料同化试验降水预报效果更好。这为将我国近海的地基多普勒天气雷达用于台风初始化分析和预报提供了一定的技术支撑和保障。     

Variation in upwelling intensity along the NorthWest Iberian Peninsula (Galicia)

Thermohaline variables were simultaneously measured, July 17, 2000, at four Galician rias under favourable upwelling conditions to analyse upwelling intensity. The intensity of coastal upwelling is shown to be strongly dependent on the wind pattern. The maximum amplitudes of wind stress were observed at the western coast (0.30 Nm^-2) with southward direction (favourable to upwelling) and these are shown to be related to low temperature (12°C) and high salinity (35.8) in the estuaries mouth. From Cape Finisterre to Cape Estaca de Bares the wind stress showed a lower magnitude (0.05-0.10 Nm^-2) with a direction oblique to the coast. The temperature showed an increase (14°C) and the salinity a decrease (35.4) because the lower upwelling intensity at this part of the coast. The observed decrease in upwelling from south to north is not an isolated event, since the measured wind conditions are persistent during summer months, at least in the period with available QuikSCAT data (1999-2004).     

正倒垂法变形监测的原理与数据分析

大坝变形监测是一项精度非常高的工作,正倒垂作为一种十分常用的监测方法,在大坝的变形监测中发挥着巨大的作用。首先介绍了正倒垂法变形监测的原理与方法,通过采集隔河岩大坝四个测点的正倒垂观测数据,重点探讨和分析了大坝水平位移与环境量之间的关系及其变化规律,并由此得出一些相关结论,最后提出了正倒垂的一些改进措施。     

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise.In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical–empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections.The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.