准四年周期的北半球夏季遥相关与东亚夏季风环流的相互关系

利用ＮＭＣ的２００ｈＰａ和８５０ｈＰａ风场资料研究了北半球夏季遥相关和东亚夏季风异常环流在准４年时间尺度上的相互关系。研究发现当北半球夏季出现积雪强迫型遥相关时,东亚－西太平洋地区既存在异常纬向环流,也存在异常经向环流;而当出现东亚太平洋型遥相关时,东亚－西太平洋地区以异常纬向环流为主。分析还发现源于北太平洋的异常涡旋在向南传播的过程中,先取西南路径,在到达菲律宾东部以后折向东南。     

小麦出苗至抽穗期土壤湿度预报及喷灌量计算

以黑龙江省８５０农场的资料进行分析,５至６月份小麦出苗、拔节至抽穗阶段,经常出现干旱,是需水关键期,对产量影响极大。所以利用麦田土壤湿度资料,建立经验公式,对土壤墒情进行预测预报,从而获得最佳喷灌时间及喷灌量,为节约用水、计划用水提供了可靠依据。     

石英颗粒表面“V”形撞击坑与化学溶蚀坑的鉴别

石英颗粒表面特征主要是从形态上来加以区分,它是一种形貌分析法。很多特征在不同的搬运和沉积过程中都存在,因此不能用单一的特征来分析其搬运介质、搬运方式和沉积史。要综合分析全部特征,去伪存真,同时对这些特征要有正确的鉴定,这是分析的基础。     

Time-Domain Simulation for Coupled Motions of Three Barges Moored Side-by-Side in Floatover Operation

Simulating the coupled motions of multiple bodies in the time domain is a complex problem because of the strong hydrodynamic interactions and coupled effect of various mechanical connectors. In this study, we investigate the hydrodynamic responses of three barges moored side-by-side in a floatover operation in the frequency and time domains. In the frequency domain, the damping lid method is adopted to improve the overestimated hydrodynamic coefficients calculated from conventional potential flow theory. A time-domain computing program based on potential flow theory and impulse theory is compiled for analyses that consider multibody hydrodynamic interactions and mechanical effects from lines and fenders. Correspondingly, an experiment is carried out for comparison with the numerical results. All statistics, time series, and power density spectra from decay and irregular wave tests are in a fairly good agreement.     

Correlations among color,morphology, and luminosity for the luminous red galaxy (LRG) sample of the SDSS data release 5

We have investigated the correlations among color, morphology and luminosity for all LRGs, cut I LRGs, cut II LRGs, and Main galaxies that are also classified as LRGs. It is found that the morphology of LRGs is tightly correlated with luminosity. The rest-frame u-g color of cut I LRGs and cut II LRGs is nearly independent of luminosity, but the color of Main galaxies is correlated with luminosity. For cut I LRGs and Main galaxies, the early type proportion apparently changes with color: at the rest-frame u-g < 1.3 it increases strongly with increasing color, while at the rest-frame u-g > 1.3 it decreases with increasing color. We also notice that the morphology of cut II LRGs is only a weak function of color. Published in Astrofizika, Vol. 50, No. 3, pp. 335–345 (August 2007).     

强震孕育与断层形变异常形态及时空分布特征

分析了华北北部20世纪70年代初以来的断层形变资料。结果表明：震前断层活动存在明显的阶段性特征；短临阶段断层形变异常主要形态有两种：一种是在α、β相后的γ相短临异常，这种异常一般在近源区出现；另一种是较大幅度的突跳型短临异常，这种异常一般在远源区出现，这些都是断层形变前兆由中期过渡到短期的明显标志；断层形变短临异常有从外围向震中迁移的特征；唐山地震前出现γ相短临异常的比例高于大同和张北地震，主要表现为在中期趋势积累背景上的反向；3次强震前α、β、γ相异常场地的分布具构造控制特征；强震前场地断层异常活动存在象限性分布特征，且与震源机制解的结果基本一致。     

Estimation of the chord length and relative height of tracking stations from single pass satellite ranging data

We describe here a technique of determining the chord length and the relative height between two laser tracking stations using single-pass satellite ranging data over very short arcs. Numerical examples show that this technique can supplement the conventional technique which requires data over much longer arcs by providing a capability for checking the accuracy of the geodetic network of laser tracking stations.     

A comparative study of extensive machine learning models for predicting long-term monthly rainfall with an ensemble of climatic and meteorological predictors

Rainfall prediction is of vital importance in water resources management. Accurate long-term rainfall prediction remains an open and challenging problem. Machine learning techniques, as an increasingly popular approach, provide an attractive alternative to traditional methods. The main objective of this study was to improve the prediction accuracy of machine learning-based methods for monthly rainfall, and to improve the understanding of the role of large-scale climatic variables and local meteorological variables in rainfall prediction. One regression model autoregressive integrated moving average model (ARIMA) and five state-of-the-art machine learning algorithms, including artificial neural networks, support vector machine, random forest (RF), gradient boosting regression, and dual-stage attention-based recurrent neural network, were implemented for monthly rainfall prediction over 25 stations in the East China region. The results showed that the ML models outperformed ARIMA model, and RF relatively outperformed other models. Local meteorological variables, humidity, and sunshine duration, were the most important predictors in improving prediction accuracy. 4-month lagged Western North Pacific Monsoon had higher importance than other large-scale climatic variables. The overall output of rainfall prediction was scalable and could be readily generalized to other regions.     

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