2010—2016年江西省暖季短时强降水特征分析

利用江西省2010—2016年5—9月1597个观测站逐小时降水资料对江西省短时强降水进行统计分析。采用REOF将降水场划分为5个区域：赣北南部（Ⅰ区）,抚州市及赣州中部（Ⅱ区）,赣北北部（Ⅲ区）,赣南南部、北部（Ⅳ区）以及赣中西部（Ⅴ区）。短时强降水高频区主要分布在山地及河谷附近,分别为湘赣交界罗霄山脉东侧、武夷山西侧、信江河谷、乐安河谷和昌江河谷。河谷附近短时强降水频次以昌江河谷最高（16.9次/a）,山地附近最高在罗霄山脉东侧（12.6次/a）,极端短时强降水分别位于上饶市东北部山区（3.7次/a）及九岭山南侧的锦江河谷（3.3次/a）。短时强降水主要发生在5月第3候,6、7月第3~4候以及8月第2~3候。Ⅳ、Ⅴ区具有单峰型的日变化特征;Ⅰ、Ⅱ、Ⅲ区具有双峰型的日变化特征。主峰基本集中在下午17时;次峰在上午08—10时。短时强降水对暴雨贡献率基本在40%以上,Ⅰ、Ⅱ区的暴雨天气过程将近一半是由短时强降水贡献的。信江河谷是暴雨雨量中心,但并不是短时强降水雨量中心;昌江河谷与武夷山西麓既是暴雨中心也是短时强降水中心。     

利用风廓线雷达研究郑州机场低空急流特征及其对飞行的影响

利用2016、2017年郑州机场高分辨率边界层风廓线雷达半小时平均观测资料, 对机场上空低空急流时空分布特征进行统计研究, 结果表明:夏末、秋季低空急流出现次数相对较少, 春季、夏初是高发时期, 冬季易出现较强的超低空急流, 只有春季风速从低层到高层呈现先增大后减小、再增大的变化过程, 8月末可能是急流的时空转换期; 夜间和凌晨是高发时段, 白天降低30%~40%, 一般情况下, 00—12时(世界时, 下同)急流较弱, 12时后明显增强向上发展, 19时开始减弱, 持续至21时; 急流中心最大风速一半以上在12~18 m/s, 高度集中在60~180 m和300~900 m, 超低空急流占大部分, 夜间出现最大风速的概率远高于白天; 低空急流发生高度大部分在飞机起飞或着陆的范围内, 使飞机复飞概率增加, 对夜间航班影响更大。      

A study of variability of annual river flow of the southern African region

Abstract

Variability of river flow is investigated in 502 river flow gauging stations in nine countries of the southern African region with a view to document the spatial variability of the river flow regimes. Those regions where there is strong evidence of declining or increasing trend in annual runoff have been identified. The study has shown that runoff in the region ranges from over 320 mm year^?1 in the Lower Zambezi and the highlands of Tanzania to less than 10 mm year^?1 in the deserts of Namibia and the Kalahari. There is also evidence of declining runoff in parts of Zambia, Angola, Mozambique and the High Veld in South Africa. The recent decline seems to have started from around 1975.     

A generalized conditional intensity measure approach and holistic ground‐motion selection

A generalized conditional intensity measure (GCIM) approach is proposed for use in the holistic selection of ground motions for any form of seismic response analysis. The essence of the method is the construction of the multivariate distribution of any set of ground‐motion intensity measures conditioned on the occurrence of a specific ground‐motion intensity measure (commonly obtained from probabilistic seismic hazard analysis). The approach therefore allows any number of ground‐motion intensity measures identified as important in a particular seismic response problem to be considered. A holistic method of ground‐motion selection is also proposed based on the statistical comparison, for each intensity measure, of the empirical distribution of the ground‐motion suite with the ‘target’ GCIM distribution. A simple procedure to estimate the magnitude of potential bias in the results of seismic response analyses when the ground‐motion suite does not conform to the GCIM distribution is also demonstrated. The combination of these three features of the approach make it entirely holistic in that: any level of complexity in ground‐motion selection for any seismic response analysis can be exercised; users explicitly understand the simplifications made in the selected suite of ground motions; and an approximate estimate of any bias associated with such simplifications is obtained. Copyright © 2010 John Wiley & Sons, Ltd.     

Discrete wavelet‐based trend identification in hydrologic time series

Trend identification is a substantial issue in hydrologic series analysis, but it is also a difficult task in practice due to the confusing concept of trend and disadvantages of methods. In this article, an improved definition of trend was given as follows: ‘a trend is the deterministic component in the analysed data and corresponds to the biggest temporal scale on the condition of giving the concerned temporal scale’. It emphasizes the intrinsic and deterministic properties of trend, can clearly distinguish trend from periodicities and points out the prerequisite of the concerned temporal scale only by giving which the trend has its specific meaning. Correspondingly, the discrete wavelet‐based method for trend identification was improved. Differing from those methods used presently, the improved method is to identify trend by comparing the energy difference between hydrologic data and noise, and it can simultaneously separate periodicities and noise. Furthermore, the improved method can quantitatively estimate the statistical significance of the identified trend by using proper confidence interval. Analyses of both synthetic and observed series indicated the identical power of the improved method as the Mann–Kendall test in assessing the statistical significance of the trend in hydrologic data, and by using the former, the identified trend can adaptively reflect the nonlinear and nonstationary variability of hydrologic data. Besides, the results also showed the influences of three key factors (wavelet choice, decomposition level choice and noise content) on discrete wavelet‐based trend identification; hence, they should be carefully considered in practice. Copyright © 2012 John Wiley & Sons, Ltd.     

Daily rainfall projections from general circulation models with a downscaling nonhomogeneous hidden Markov model (NHMM) for south‐eastern Australia

An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south‐eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046–2065 and 2081–2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two‐thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray–Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd.     

Computational methods for fitting statistical distribution models of multi-site binding equilibria

Statistical distribution models of multi-site binding equilibria have potential applicability in the study of acid-base and metal complexation chemistry of humic substances in soils, sediments, and natural waters. A mathematical derivation is presented for the general continuous model for the case of proton binding; computational methods are described for fitting numerically the parameters in such models. Among models considered are those based on nontruncated, truncated, and bimodal (mixed) distributions. Specific emphasis is placed on Gaussian distribution models.     

Modeling long term lake variations by physically based stochastic dynamic models

Several physically based stochastic dynamic models (SDM) are described including year-to-year variations of water volume in terminal and non-terminal lakes, streamflow of lake-fed rivers, and salinity of an inland sea (the Sea of Azov). All of these models are based upon the SDM of water volume of terminal lakes developed by Kritzky and Menkel in 1946 in co-operation with Kolomogorov. Explicit formulae are derived for second order statistical moments of the output processes, including variance, correlation function, spectra, etc., under the assumption that the forcing functions from stationary random sequences. The least-squares prediction problem is solved for both stationary and non-stationary cases. Some of the processes are shown to possess high statistical predictability. Actual predictions are compared with independent observations. Problems for further study are stated.     

岩体结构面粗糙度系数JRC的定向统计研究

本文回顾了岩体结构面粗糙度系数ＪＲＣ的研究成果，分析了各种ＪＲＣ研究方法的应用范围。在野外实际结构面形态的详细调查和深入研究的基础上，发展了Ｂａｒｔｏｎ直边法，并提出按岩性定向统计研究结构面粗糙度系数ＪＲＣ的科学思想。     

多元素与大骨节病关系的稳定性研究

对内蒙古三个典型大骨节病区<15岁人群发中21个元素和病情进行了三年连续定期观察,统计分析结果表明:(1)病区食物对人体元素含量的影响可以分为二种情况,一是元素在食物链中含量过低,食物的变化虽可使机体该元素发生变化,但变幅甚小,致使其代谢处于缺乏状态;另一类是机体内这些元素的含量因食物的改变而发生较大变化,显示这些元素与病情无内在联系.(2)对发中硒等2l个元素与病情分别作单相关和多元逐步回归分析,结果证明,硒缺乏是导致大骨节病早期病变的基本因素,而其它元素与病情的关系具有不确定性.