不确定性类型对概率表达和概率判断的影响

The present research firstly reviewed the experimental literature on probability expression and probability judgment, hypothesizing that individuals’ preference of probability expressions (verbal probability vs. numerical probability) and tendency for overextremity in probability judgment might differ with respect to different types of uncertainty. Five studies were conducted to test this hypothesis. In Study 1, questionnaires were used to explore the communication preference among Chinese-speaking people. Study 2 adapted the View of Uncertainty Questionnaire to explore the difference of verbal answers to three kinds of uncertainty. Study 3 and Study 4 used methods of the paper-and-pencil questionnaire and the laboratory experiment, respectively, to test the effects of uncertainty types on the preference of probability expressions and on the tendency for over-extreme probability judgment. Finally, Study 5 focused on individuals’ preference of probability expressions under various kinds of scenarios. The results were as follows: 1. The Communication Model Preference paradox phenomenon appears to be even more pronounced in the Chinese culture than in American English cultural settings. 2. The Chinese prefer more verbal probability expressions when communicating uncertainty in a weather-forecasting context than in a general context. 3. Sample groups with lower level of westernization tend to give more extreme answers and less probabilistic answers. 4. Types of uncertainty did have effects on individuals’ tendency for over-extreme probability judgment: under a traditional probability judgment task, people tend to be more over-extreme on internal uncertainty events than on external uncertainty events; however, this result is reversed under a gambling task. 5. Individuals’ preference for verbal probability expressions is more salient on internal uncertain events than on external uncertain events.

Forecasting Daily Chlorophyll a Concentration during the Spring Phytoplankton Bloom Period in Xiangxi Bay of the Three-Gorges Reservoir by Means of a Recurrent Artificial Neural Network

A recurrent artificial neural network was used for 0-and 7-days-ahead forecasting of daily spring phytoplankton bloom dynamics in Xiangxi Bay of Three-Gorges Reservoir with meteorological, hydrological, and limnological parameters as input variables. Daily data from the depth of 0.5 m was used to train the model, and data from the depth of 2.0 m was used to validate the calibrated model. The trained model achieved reasonable accuracy in predicting the daily dynamics of chlorophyll a both in 0-and 7-days-ahead forecasting. In 0-day-ahead forecasting, the R-2 values of observed and predicted data were 0.85 for training and 0.89 for validating. In 7-days-ahead forecasting, the R-2 values of training and validating were 0.68 and 0.66, respectively. Sensitivity analysis indicated that most ecological relationships between chlorophyll a and input environmental variables in 0-and 7-days-ahead models were reasonable. In the 0-day model, Secchi depth, water temperature, and dissolved silicate were the most important factors influencing the daily dynamics of chlorophyll a. And in 7-days-ahead predicting model, chlorophyll a was sensitive to most environmental variables except water level, DO, and NH3N.

Differing estrogen activities in the organic phase of air particulate matter collected during sunny and foggy weather in a Chinese city detected by a recombinant yeast bioassay

Total air suspended particles (PM 100) collected from an urban location near a traffic line in Wuhan, China, were examined for estrogen using a recombinant yeast bioassay. Wuhan, located at the central part of China, is the fourth biggest city in China with 7 million populations. Today, Wuhan has developed into the biggest city and the largest traveling center of central China, becoming one of the important bases of industry, education and research. Wuhan is right at the confluent point of Yangzi River, the third longest river in the world, and its largest distributary Hanjiang, with mountains and more than 100 takes in downtown area. Therefore, by its unique landscape, Wuhan has formed clear four seasons with relatively long winter and summer and short spring and autumn. Foggy weather usually happen in early spring. The yeast line used in this assay stably expresses human estrogen receptor-alpha. Weak but clear estrogenic activities were detected in the organic phase of crude extracts of air particle materials (APM) in both sunny and foggy weather by 0.19-0.79 mug E2/gPM(100) which were statistically significantly elevated relative to the blank control responding from 20% to 50% of the maximum E2 response, and the estrogenic activity was much higher in foggy weather than in sunny weather. The estrogenic activities in the sub-fractions from chromatographic separation of APM sampled in foggy days were also determined. The results indicated that the responses of the fractions were obviously higher than the crude extracts. Since there is no other large pollution source nearby, the estrogenic material was most likely from vehicle emissions, house heating sources and oil fumes of house cooking. The GC/MS analysis of the PM100 collected under foggy weather showed that there were many phenol derivatives, oxy-PAHs and resin acids which have been reported as environmental estrogens. These results of the analysis of estrogenic potency in sunny and foggy weather in a subtropical city of China indicate that further studies are required to investigate the actual risks for the associated health and atmospheric system. (C) 2004 Elsevier Ltd. All rights reserved.

A non-linear perturbation model considering catchment wetness and its application in river flow forecasting

A non-linear perturbation model for river flow forecasting is developed, based on consideration of catchment wetness using an antecedent precipitation index (API). Catchment seasonality, of the form accounted for in the linear perturbation model (the LPM), and non-linear behaviour both in the runoff generation mechanism and in the flow routing processes are represented by a constrained nan-linear model, the NLPM-API. A total of ten catchments, across a range of climatic conditions and catchment area magnitudes, located in China and in other countries, were selected for testing daily rainfall-runoff forecasting with this model. It was found that the NLPM-API model was significantly more efficient than the original linear perturbation model (the LPM). However, restric tion of explicit nan-linearity to the runoff generation process, in the simpler LPM-API form of the model, did not produce a significantly lower value of the efficiency in flood forecasting, in terms of the model efficiency index R-2. (C) 1997 Elsevier Science B.V.

Dust weather records in Beijing during 1860-1898 AD based on the Diary of Tonghe Weng

IEECAS SKLLQG

Deformation Monitoring and Forecasting Model Study Based on Grey System Theory

The grey system theory studies the uncertainty of small sample size problems. This paper using grey system theory in the deformation monitoring field, based on analysis of present grey forecast models, developed the spatial multi-point model. By using residual modification, the spatial multi-point residual model eras developed in further study. Then, combined with the sedimentation data of Xiaolangdi Multipurpose Dam, the results are compared and analyzed, the conclusion has been made and the advantages of the residual spatial multi-point model has been proved.

Application of forecasting structural cracks technique of 3D move in Chengdao buried hill

3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.

空间电流体系地磁反演及理论研究

The space currents definitely take effects on electromagnetic environment and also are scientific highlight in the space research. Space currents as a momentum and energy provider to Geospace Storm, disturb the varied part of geomagnetic field, distort magnetospheric configuration and furthermore take control of the coupling between magnetosphere and ionosphere. Due to both academic and commercial objectives above, we carry on geomagnetic inverse and theoretical studies about the space currents by using geomagnetic data from INTERMAGNET. At first, we apply a method of Natural Orthogonal Components (NOC) to decomposition the solar daily variation, especially for (solar quiet variation). NOC is just one of eign mode analysis, the most advantage of this method is that the basic functions (BFs) were not previously designated, but naturally came from the original data so that there are several BFs usually corresponding to the process really happened and have more physical meaning than the traditional spectrum analysis with the fixed BFs like Fourier trigonometric functions. The first two eign modes are corresponding to the and daily variation and their amplitudes both have the seasonal and day-to-day trend, that will be useful for evaluating geomagnetic activity indices. Because of the too strict constraints of orthogonality, we try to extend orthogonal contraints to the non-orthogonal ones in order to give more suitable and appropriate decomposition of the real processes when the most components did not satisfy orthogonality. We introduce a mapping matrix which can transform the real physical space to a new mathematical space, after that process, the modified components which associated with the physical processes have satisfied the orthogonality in the new mathematical space, furthermore, we can continue to use the NOC decomposition in the new mathematical space, and then all the components inversely transform back to original physical space, so that we would have finished the non-orthogonal decomposition which more generally in the real world. Secondly, geomagnetic inverse of the ring current’s topology is conducted. Configurational changes of the ring current in the magnetosphere lead to different patterns of disturbed ground field, so that the global configuration of ring current can be inferred from its geomagnetic perturbations. We took advantages of worldwide geomagnetic observatories network to investigate the disturbed geomagnetic field which produced by ring current. It was found that the ring current was not always centered at geomagnetic equator, and significantly deviated off the equator during several intense magnetic storms. The deviation owing to the tilting and latitudinal shifting of the ring current with respect to the earth’s dipole can be estimated from global geomagnetic survey. Furthermore those two configurational factors which gave a quantitative description of the ring current configuration, will be helpful to improve the Dst calibration and understand the dependence of ring current’s configuration on the plasma sheet location relative to the equator when magnetotail field warped. Thirdly, the energization and physical acceleration process of ring current during magnetic storm has been proposed. When IMF Bz component increase, the enhanced convection electric field drive the plasma injection into the inner magnetosphere. During the transport process, a dynamic heating is happened which make the particles more ‘hot’ when the injection is more deeply inward. The energy gradient along the injection path is equivalent to a kind of force, which resist the plasma more earthward injection, as a diamagnetic effect of the magnetosphere anti and repellent action to the exotically injected plasma. The acceleration efficiency has a power law form. We use analytical way to quantitatively describe the dynamical process by introducing a physical parameter: energization index, which will be useful to understand how the particle is heated. At the end, we give a scheme of how to get the from storm time geomagnetic data. During intense magnetic storms, the lognormal trend of geomagnetic Dst decreases depend on the heating dynamic of magnetosphere controlling ring current. The descending pattern of main phase is governed by the magnetospheric configuration, which can be describled by the energization index. The amplitude of Dst correlated with convection electric field or south component of the solar wind. Finally, the Dst index is predicted by upstream solar wind parameter. As we known space weather have posed many chanllenges and impacts on techinal system, the geomagnetic index for evaluating the activity space weather. We review the most popular Dst prediction method and repeat the Dst forecasting model works. A concise and convnient Key Points model of the polar region is also introduced to space weather. In summary, this paper contains some new quantitative and physical description of the space currents with special focus on the ring current. Whatever we do is just to gain a better understanding of the natural world, particularly the space environment around Earth through analytical deduction, algorithm designing and physical analysis, to quantitative interpretation. Applications of theoretical physics in conjunction with data analysis help us to understand the basic physical process govering the universe.

中低纬电离层暴的统计分析与经验建模

As a key issue of ionospheric weather study, systemic studies on ionospheric storms can not only further improve our understanding of the response of the ionosphere to solar and geomagnetic disturbances, but also help us to reveal the chemical, dynamic and electro-dynamic mechanisms during storms. Empirical modelling for regional ionospheric storm is also very useful, because it can provide us with tools and references for the forecasting and further practical application of ionospheric activity. In this thesis, we focus on describing and forecasting of ionospheric storms at middle and low latitudes. The main points of my investigations are listed as follows. (1) By using magnetic storms during the period over 50 years, the dependence of the type, onset time and time delay of the ionospheric storms on magnetic latitude, season and local time at middle and low latitudes in the East-Asian sector are studied. The results show that the occurrences of the types of ionospheric disturbances differ in latitude and season. The onset of the ionospheric storms depends on local time. At middle latitudes, most negative phase onsets are within the local time interval from night to early morning, and they rarely occurred in the local noon and afternoon sectors. At low latitudes, positive phases commence most frequently in the daytime sector as well as pre-midnight sector. The average time delays for both the positive and negative ionospheric storms increase with descending latitudes. The time delay has significant dependence on the local time of main phase onset (MPO). The time delay of positive response is shorter for daytime MPO and longer for night-time MPO, whereas the opposite applies for negative response. (2) Based on some previous researches, a primary empirical model for mid-latitude ionospheric disturbance is set up. By fitting to the observed data, we get a high accuracy with a mean RMSE of only 12-14% in summer and equinox. The model output has been compared with the output of STORM model, and the results show that, our model is much better than STORM in summer and a little better for some mid-latitude stations at equinox. Especially, for the type of two-step geomagnetic storm, our model can present twice descending of foF2 very well. In addition, our model can forecast positive ionospheric storms.