CLIMATOLOGICAL CHARACTERISTICS FOR THE ONSET OF ASIAN SUMMER MONSOON AS REVEALED BY HIRS-Tb12 AND DROUGHT AND FLOODS IN EASTERN CHINA

As shown in comparison and study of the HIRS-Tb12 data and conventional data, temperature, humidity and vertical motion are structured differently in the Southern and Northern Hemispheres, which are well depicted with the HIRS-Tb12 data. When high pressures rapidly decrease over the regions of South China Sea and Arabian Sea with the HIRS-Tb12 less than 200 W/m2, monsoons will set off in the South China Sea, Arabian Sea and Bay of Bengal, respectively. From a year of significant drought to one of significant floods, the trend of evolution is significantly different in the downdraft areas of the subtropical highs between the two hemispheres.     

用翁氏模型图版设计早期油气田(藏)开发方案

由于缺乏早期资料，设计早期油气田（藏）开发方案是非常困难的。在制作翁氏模型的Qctm/No-ER图版和ER-ctR图版过程提出根据探明储量No、经济极限产量Qc、假定达到峰值产量的时间tm、最终采收率ER，由翁氏模型的Qctm/No-ER图版求取增长指数b，由翁氏模型ER-ctR图版求取ctR，再求出其他参数及所有的油气田（藏）开发指标，完成早期油气田（藏）开发方案设计。     

Evaluation of the Reduction in Uncertainty Obtained by Conditioning a 3D Stochastic Channel to Multiwell Pressure Data

A stochastic channel embedded in a background facies is conditioned to data observed at wells. The background facies is a fixed rectangular box. The model parameters consist of geometric parameters that describe the shape, size, and location of the channel, and permeability and porosity in the channel and nonchannel facies. We extend methodology previously developed to condition a stochastic channel to well-test pressure data, and well observations of the channel thickness and the depth of the top of the channel. The main objective of this work is to characterize the reduction in uncertainty in channel model parameters and predicted reservoir performance that can be achieved by conditioning to well-test pressure data at one or more wells. Multiple conditional realizations of the geometric parameters and rock properties are generated to evaluate the uncertainty in model parameters. The ensemble of predictions of reservoir performance generated from the suite of realizations provides a Monte Carlo estimate of the uncertainty in future performance predictions. In addition, we provide some insight on how prior variances, data measurement errors, and sensitivity coefficients interact to determine the reduction in model parameters obtained by conditioning to pressure data and examine the value of active and observation well data in resolving model parameters.     

Combination of Dependent Realizations Within the Gradual Deformation Method

Gradual deformation is a parameterization method that reduces considerably the unknown parameter space of stochastic models. This method can be used in an iterative optimization procedure for constraining stochastic simulations to data that are complex, nonanalytical functions of the simulated variables. This method is based on the fact that linear combinations of multi-Gaussian random functions remain multi-Gaussian random functions. During the past few years, we developed the gradual deformation method by combining independent realizations. This paper investigates another alternative: the combination of dependent realizations. One of our motivations for combining dependent realizations was to improve the numerical stability of the gradual deformation method. Because of limitations both in the size of simulation grids and in the precision of simulation algorithms, numerical realizations of a stochastic model are never perfectly independent. It was shown that the accumulation of very small dependence between realizations might result in significant structural drift from the initial stochastic model. From the combination of random functions whose covariance and cross-covariance are proportional to each other, we derived a new formulation of the gradual deformation method that can explicitly take into account the numerical dependence between realizations. This new formulation allows us to reduce the structural deterioration during the iterative optimization. The problem of combining dependent realizations also arises when deforming conditional realizations of a stochastic model. As opposed to the combination of independent realizations, combining conditional realizations avoids the additional conditioning step during the optimization process. However, this procedure is limited to global deformations with fixed structural parameters.     

Probability Density Functions as Botanical-Climatological Transfer Functions for Climate Reconstruction

We present a new procedure, the pdf method (pdf=probability density function), for reconstructing Quaternary climate utilizing botanical data. The procedure includes the advantages of the indicator species method by considering the fossil and modern presence and absence of taxa rather than their frequencies, thus avoiding the need for modern analog plant communities. Overcoming the problematic use of absolute limits to describe climate response ranges is the main progress of the pdf method in comparison to the indicator species method. This advantage results from estimating probability density functions (pdfs) for monthly mean January and July temperature conditional on the present day occurrence of single taxa. Gaussian distributions sufficiently approximate pdfs of many, although not all, studied taxa. On the assumption of statistical independence, the procedure calculates a joint pdf as the product of the pdfs of the individual taxa. This algorithm weights each taxon according to the extent of its climate response range expressed by its covariance structure. We interpret the maximum of the resulting pdf as the most likely climate and its confidence interval as the uncertainty range. To avoid an artificial reduction of uncertainty arising from the use of numerous similar pdfs, a preselection method is proposed based on the Mahalanobis distance between pdfs. The pdf method was applied to the Carpinus phase of a profile from Gröbern, Germany, that spans the last interglaciation (Eemian). The reconstructed most probable January and July temperatures of about 0.0°C and 18.4°C barely differ from the modern values of −0.5°C and 18.3°C.     

Drought in Bulgaria and atmospheric synoptic conditions over Europe

Drought in Bulgaria is analyzed from the multiple viewpoints of statistical occurrence, spatial patterns, and synoptic conditions. A new index of drought, the SD (spatial-dryness) index, characterizes drought by both intensity and spatial extent. The occurrence of the SD index is analyzed using global gridded data sets. Examination of transitional probabilities of multiple months and years with drought occurrence suggests persistence is sufficiently frequent to be important for climate-related environmental planning. Finally, it is shown that specific seasonal synoptic patterns are associated with wet and dry conditions in Bulgaria. This revised version was published online in July 2006 with corrections to the Cover Date.     

山西夏县台热水井水氡异常特征与地震的关系初探

为弄清山西夏县中心地震台水氡震前异常的原因 ,对山西夏县中心地震台热水井水氡 1984年以来的观测资料用概率论的数据处理方法进行了处理 ,以负异常的发震原理进行了分析 ,结果表明震前负异常的发震概率为 70 %。     

应力释放模型的改进及其在研究台湾地区地震预测问题中的应用.

应力释放模型过去主要用于研究大范围历史大地震活动规律．本文对应力释放模型进行了改进，对其能否运用于区域更小、时段更短、震级更低的情况进行了探讨；以台湾地区近百年6级以上地震为例的研究结果表明，应力释放模型仍然适用．在回溯性的地震预测检验中，用改进的应力释放模型计算出台湾地区地震发生的条件概率强度，并用其预测6级以上地震的发震时刻．结果表明，其预测精度优于泊松模型．      

Application of Dangerous Probability Function in Risk Estimation of Surface Rupture Earthquake：Taking the Lingwu Fault in Ningxi1 Region as on Example

Based on the fitting on paleoearthquake data of intra-plate regions in the northern part of Chi-na and giving a statistical model of time interdependence,the potential damage earthquakes in a definite future period and characteristics of present shocks along the Lingwu fault have been analyzed by using dangerous probability function and some new data concerned.We have in-ferred that the fault has entered a period that earthquakes will probably occur.There exists a potential danger that a strong earthquake with Ms7.0-7.5 will occur in 10-100a.     

河流水质风险评价的灰色-随机风险率方法

提出了量化影响河流水质的随机不确定性与灰色不确定性的水质超标灰色－随机风险率概念，建立了水质超标灰色－随机风险率评价模型。在水质单项参数评价模型中，将河流污染物浓度变量的分布处理成灰色概率分布，将污染物浓度超过水质类别标准值的风险率处理成灰色概率，即水质超标灰色－随机风险率。在水质综合评价模型中，河流水环境系统被考虑为担任某一使用可能的可靠性系统，而任意一种水质参数超标意味着河流水体使用功能不能得到应有的保证，也即表明水体综合评价超标，最后借鉴系统可靠性分析的理论和方法计算水质综合超标率。该方法应用于黄河花园口断面重金属污染风险评价。