华北地区地震短临异常综合标志及预报指标的研究

本文对华北16次中强以上地震前多种前兆短临异常进行了分析,归纳出短临异常的综合变化特征。依据短临异常的综合特征,提出在中期异常背景上孕震过程由中期向短期过渡的两个定量化综合标志。研究了孕震后期在观测到较多数量短临异常情况下,能否发布5级以上地震预报意见的预报指标。作为本文结果的检验,计算了8次地震前的综合标志和预报指标。本研究工作在短临预报中具有一定的实用价值。

云南地区2011年雨季结束期(10—11月)降水延伸期预报试验

1引言延伸期天气预报指10～30d期间的天气过程预报[1-3],介于中期天气预报(10d以下)和长期天气预报(月以上)之间,能有效衔接天气预报和气候预测之间的"缝隙"。近年来关于延伸期天气预报的研究大多是基于季节内振荡(ISO)理论。

Experiment study of optimization on prediction index gases of coal spontaneous combustion

The coal of Anyuan Mine has the characteristic of easy spontaneous combustion. Conventional method is difficult to predict it. Coal samples from this mine were tested in laboratory. The data obtained from laboratory determination were initialized for the value which was defined as "K". The ratio of each index gas and value of "K", and the ratio of combination index gases and value of "K", were analyzed simultaneously. The research results show that for this coal mine, if there is carbon monoxide in the gas sample, the phenomenon of oxidation and temperature rising for coal exists in this mine; if there is C_2H_4 in the gas sample, the temperature of coal perhaps exceeds 130 °C. If the coal temperature is between 35 °C and 130 °C, prediction and forecast for coal spontaneous combustion depend on the value of Φ(CO)/K mainly; if the temperature of coal is between 130 °C and 300 °C, prediction and forecast for coal spontaneous combustion depend on the value of Φ(C_2H_6)/Φ(C_2H_2) and Φ(C_2H_6)/K. The research results provide experimental basis for the prediction of coal spontaneous combustion in Anyuan coal mine, and have better guidance on safe production of this coal mine.

巴彦淖尔市2012-07-20典型极端暴雨过程特征分析

文章使用MICAPS常规气象资料及多普勒雷达资料对2021-07-20/21巴彦淖尔市东南部地区的大到暴雨过程进行特征及成因分析。文章介绍了天气实况与环流背景,分析了影响系统与演变特征、雷达资料和探空资料,同时进行了Ec数值预报模式检验并给出了预报指标量值。所得结论以期为今后预报预警业务的开展提供参考。

Application of uncertainty reasoning based on cloud model in time series prediction

Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.

Estimating Field Source Parameters of Gravity Change in North China Based on the Euler Deconvolution Method

Based on the absolute and relative gravity observations in North China from 2009 to 2014,spatial dynamic variations of the regional gravity field are obtained. We employed the Euler deconvolution method and the theoretical model to get the best estimates of parameters. Gravity field change caused by the depth and distribution in North China is calculated by back analysis. The results show the structural index that equals 1 is suitable for inversion of the gravity variation data. The inversion results indicate that the depths of anomaly field sources are spread over the Hetao fault. The research method of this paper can be used in the quantitative study on the field source and may shed new light on the interpretations of gravity change, and also provide quantitative basis for earthquake prediction index criterions based on the gravity change.

Melt Index Prediction by Neural Soft-Sensor Based on Multi-Scale Analysis and Principal Component Analysis

Prediction of melt index （MI）, the most important parameter in determining the product＇s grade and quality control of polypropylene produced in practical industrial processes, is studied. A novel soft-sensor model with principal component analysis （PCA）, radial basis function （RBF） networks, and multi-scale analysis （MSA） is proposed to infer the MI of manufactured products from real process variables, where PCA is carried out to select the most relevant process features and to eliminate the correlations of the input variables, MSA is introduced to a^quire much more information and to reduce the uncertainty of the system, and RBF networks are used to characterize the nonlinearity of the process. The research results show that the proposed method provides promising prediction reliability and accuracy, and supposed to have extensive application prospects in propylene polymerization processes.

Prediction of the P-leaching potential of arable soils in areas with high livestock densities

Due to long-term positive P-balances many surface soils in areas with high livestock density in Germany are over-supplied with available P, creating a potential for vertical P losses by leaching. In extensive studies to characterize the endangering of ground water to P pollution by chemical soil parameters it is shown that the available P content and the P concentration of the soil solution in the deeper soil layers, as indicators of the P-leaching potential, cannot be satisfactorily predicted from the available P content of the topsoils. The P equilibrium concentration in the soil solution directly above ground water table or the pipe drainage system highly depends on the relative saturation of the P-sorption capacity in this layer. A saturation index of <20% normally corresponds with P equilibrium concentrations of <0.2 mg P/L. Phytoremediation may reduce the P leaching potential of P-enriched soils only over a very long period.

REDEFINING ENSO EPISODES BASED ON CHANGED CLIMATE REFERENCES

Through studying changes in ENSO indices relative to change of climate reference from 1961~1990 to 1971~2000, the study generated new standards to define ENSO episodes and their intensities. Then according to the new climate references and new index standards, ENSO episodes and their intensities for the period 1951 -2003 have been classified. Finally, an analysis has been performed comparing the new characteristics with the old ones for ENSO period, peak values and intensities.

Quantifying local predictability of the Lorenz system using the nonlinear local Lyapunov exponent

The nonlinear local Lyapunov exponent（NLLE） can be used as a quantification of the local predictability limit of chaotic systems. In this study, the phase-spatial structure of the local predictability limit over the Lorenz-63 system is investigated. It is found that the inner and outer rims of each regime of the attractor have a high probability of a longer than average local predictability limit, while the center part is the opposite. However, the distribution of the local predictability limit is nonuniformly organized, with adjacent points sometimes showing quite distinct error growth.The source of local predictability is linked to the local dynamics, which is related to the region in the phase space and the duration on the current regime.

Managerial Ability and Forecast Accuracy

We examine the relation between managerial ability and management forecast accuracy. We base our analysis on S＆P 500 Composite Index constituents for the period of 2006-2012. Data were collected from Thomson Reuteurs, Compustat and Demerjian, Lev, and McVay （2012）. We find that forecast accuracy is positively associated with managerial ability in the case of sales forecasts. Specifically, more able managers are associated with lower magnitude＇s forecast errors in the case of sales forecasts. Additional analysis finds that managerial ability is immaterial to EPS figures＇ forecast accuracy, i.e., EPS forecasts appear not to be affected by manager＇s superiority. Regarding sales forecasts, the results are consistent with the assertion that managers impact the quality of the delivered management forecasts. Regarding EPS forecasts, the results are in alignment with Demerjian, Lev, Lewis, and McVay （2013） who highlighted that managerial ability is an ability score related to the entire management team.

New European Union＇s Requirements and IFRS Practice Statement ＂Management Commentary＂： Does MD＆A Disclosure Quality Affect Analysts＇ Forecasts？

The Management Discussion and Analysis （MD＆A） is a mandatory document under the European Union＇s （EU） law. In 2003, the EU issued Directive 2003/51/EC, which broadened the information that firms have to provide in their MD＆A, and in 2010 the International Accounting Standards Board （IASB） issued the International Financial Reporting Standards （IFRS） Practice Statement ＂Management Commentary＂, a non-binding guidance for the presentation of this document. The aim of this paper is to examine the relationship between MD＆A disclosure quality and properties of analysts＇ forecasts. In fact, although most studies found that financial analysts mainly refer to financial statement data in forecasting earnings, there are few researches highlighting the importance of MD＆A disclosures for financial analysts. On this basis, Ramnath, Rock, and Shane （2008） called for researches in order to better understand the relationship between the information really used by analysts and their forecasts. To assess the quality of MD＆A disclosures, we developed a multidimensional measure on the basis of the EU requirements and the IFRS Practice Statement, and then we regressed this variable on both forecast accuracy and dispersion. The findings show that our measure of MD＆A disclosure quality is significantly and positively related to forecast accuracy. We conducted other analyses in order to better understand the previous relationship and we found that, if we analyze the different information contained in the MD＆A statement, financial analysts consider useful accounting and financial data in forecasting earnings. These results enhance our understanding of the role of MD＆A disclosures in the wide set of information that firms provide to financial statement users.