Spacecraft potential control aboard Equator-S as a test for Cluster-II     

K. Torkar  W. Riedler  M. Fehringer  F. Rüdenauer  C. P. Escoubet  H. Arends  B. T. Narheim  K. Svenes  M. P. McCarthy  G. K. Parks  R. P. Lin  H. Rème 《Annales Geophysicae》1999,17(12):1582-1591

The payload of Equator-S was complemented by the potential control device (PCD) to stabilise the electric potential of the spacecraft with respect to the ambient plasma. Low potentials are essential for accurate measurements of the thermal plasma. The design of PCD is inherited from instruments for Geotail and Cluster and utilises liquid metal ion sources generating a beam of indium ions at several keV. The set-up of the instrument and its interaction with the plasma instruments on board is presented. When the instrument was switched on during commissioning, unexpectedly high ignition and operating voltages of some ion emitters were observed. An extensive investigation was initiated and the results, which lead to an improved design for Cluster-II, are summarised. The cause of the abnormal behaviour could be linked to surface contamination of some emitters, which will be monitored and cured by on-board procedures in future. The mission operations on Equator-S were not at all affected, because of the high redundancy built into the instrument so that a sufficient number of perfectly operating emitters were available and were turned on routinely throughout the mission. Observations of the effect of spacecraft potential control on the plasma remained limited to just one event on January 8, 1998, which is analysed in detail. It is concluded that the ion beam lead to the predicted improvement of the particle measurements even outside the low density regions of the magnetosphere where the effect of spacecraft potential control would have been much more pronounced, and that the similar instruments for the four Cluster-II spacecraft to be launched in 2000 will be very important to ensure accurate plasma data from this mission.  相似文献   

A probabilistic model for ghost delay time estimation based on recording geometry          下载免费PDF全文

James Rickett  Inês Cecílio 《Geophysical Prospecting》2018,66(5):964-974

In order to deconvolve the ghost response from marine seismic data, an estimate of the ghost operator is required. Typically, this estimate is made using a model of in‐plane propagation, i.e., the ray path at the receiver falls in the vertical plane defined by the source and receiver locations. Unfortunately, this model breaks down when the source is in a crossline position relative to the receiver spread. In this situation, in‐plane signals can only exist in a small region of the signal cone. In this paper, we use Bayes' theory to model the posterior probability distribution functions for the vertical component of the ray vector given the known source–receiver azimuth and the measured inline component of the ray vector. This provides a model for the ghost delay time based on the acquisition geometry and the dip of the wave in the plane of the streamer. The model is fairly robust with regard to the prior assumptions and controlled by a single parameter that is related to the likelihood of in‐plane propagation. The expected values of the resulting distributions are consistent with the deterministic in‐plane model when in‐plane likelihood is high but valid everywhere in the signal cone. Relaxing the in‐plane likelihood to a reasonable degree radically simplifies the shape of the expected‐value surface, lending itself for use in deghosting algorithms. The model can also be extended to other plane‐wave processing problems such as interpolation.  相似文献   

Estimating the provincial environmental Kuznets curve in China: a geographically weighted regression approach     

Yoomi?KimEmail authorView author&#;s OrcID profile  Katsuya?Tanaka  Chazhong?Ge 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(7):2147-2163

This study estimates the environmental Kuznets curve (EKC) relationship at the province level in China. We apply empirical methods to test three industrial pollutants—SO₂ emission, wastewater discharge, and solid waste production—in 29 Chinese provinces in 1994–2010. We use the geographically weighted regression (GWR) approach, wherein the model can be fitted at each spatial location in the data, weighting all observations by a function of distance from the regression point. Hence, considering spatial heterogeneity, the EKC relationship can be analyzed region-specifically through this approach, rather than describing the average relationship over the entire area examined. We also investigate the spatial stratified heterogeneity to verify and compare risk factors that affect regional pollution with statistical models. This study finds that the GWR model, aimed at considering spatial heterogeneity, outperforms the OLS model; it is more effective at explaining the relationships between environmental performance and economic growth in China. The results indicate a significant variation in the existence of the EKC relationship. Such spatial patterns suggest province-specific policymaking to achieve balanced growth in those provinces.  相似文献   

Decaying grid turbulence experiments in a stratified fluid: flow measurements and statistics     

S.?EspaEmail authorView author&#;s OrcID profile  G.?Avallone  A.?Cenedese 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(8):2325-2336

Laboratory experiments of decaying grid stratified turbulence were performed in a two-layer fluid and varying the stratification intensity. Turbulence was generated by towing an array of cylinders in a square vessel and the grid was moved at a constant velocity along the total vertical extent of the tank. In order to investigate the influence of the stratification intensity on the turbulence decay, both 2C-PIV and stereo PIV were used to provide time resolved velocity fields in the horizontal plane and the out-of-plane velocity. As expected, a faster decay of the turbulence level along the vertical axis and the collapse in a quasi-horizontal motion increased with the buoyancy frequency, N. In order to characterise the decay process we investigated the time evolution of the vortex statistics, the turbulence scales and the kinetic energy and enstrophy of the horizontal flow. The exponents recovered in the corresponding scaling laws were compared with the theoretical predictions and with reference values obtained in previous experimental studies. Both the spectral analysis and the evolution of characteristic length scales indicate that, in the examined range of N, the dynamics is substantially independent of the stratification intensity. The results obtained were explained in terms of the scaling analysis of decaying turbulence in strongly stratified fluids introduced by Brethouwer et al. (J Fluid Mech 585:343–368.  https://doi.org/10.1017/S0022112007006854, 2007).  相似文献   

Multisource hydrologic modeling uncertainty analysis using the IBUNE framework in a humid catchment     

Binquan?LiView author&#;s OrcID profile  Yingqing?He  Liliang?RenEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(1):37-50

Hydrologic cycle is a complex system associated with both certain and uncertain constituents. The propagation of confidence bounds from different uncertainty sources to model output is of great significance for hydrologic modeling. In this paper, we applied the integrated bayesian uncertainty estimator to quantify the effects of parameter, input and model structure uncertainty on hydrologic modeling progressively. Two hydrologic models (Xinanjiang model and TOPMODEL) were applied to a humid catchment under three scenarios. Case I: the shuffled complex evolution metropolis (SCEM-UA) algorithm was conducted to determine the posterior parameter distribution of hydrologic models and analyze the corresponding forecast uncertainty. Case II: input uncertainty was also considered by assuming rain depth bias follows a normal distribution, and integrated with SCEM-UA. Case III: Simulations from two models were combined by the Bayesian model averaging to fully quantify multisource uncertainty effects. Results suggested that, from Case I to II, the containing ratio (percentage of observed streamflow enveloped by 95% confidence interval) obviously increased by an average magnitude of 10% for the study period 2000–2006. Besides, it also found that the width of 95% confidence interval became wider and narrower for Xinanjiang model and TOPMODEL, respectively, from Case I to II. This may indicate that the uncertainty of TOPMODEL results was more remarkable than Xinanjiang model in Case I. By combining results from two models, model structure uncertainty was also considered in Case III. The accuracy of uncertainty bounds further improved with the containing ratio of 95% confidence interval >95%. In addition, the optimized deterministic results from the uncertainty analysis showed that the average Nash–Sutcliffe coefficient increased continually from Case I to II and III (0.82, 0.84 and 0.90, respectively) for the study period. The analysis demonstrated the improvement of modeling accuracy when extra uncertainty sources were also quantified, and this finding also proved the applicability of IBUNE framework in hydrologic modeling.  相似文献   

Relative model score: a scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling     

Ahmed?S.?Elshall  Ming?YeEmail authorView author&#;s OrcID profile  Yongzhen?Pei  Fan?Zhang  Guo-Yue?Niu  Greg?A.?Barron-Gafford 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(10):2809-2819

This paper defines a new scoring rule, namely relative model score (RMS), for evaluating ensemble simulations of environmental models. RMS implicitly incorporates the measures of ensemble mean accuracy, prediction interval precision, and prediction interval reliability for evaluating the overall model predictive performance. RMS is numerically evaluated from the probability density functions of ensemble simulations given by individual models or several models via model averaging. We demonstrate the advantages of using RMS through an example of soil respiration modeling. The example considers two alternative models with different fidelity, and for each model Bayesian inverse modeling is conducted using two different likelihood functions. This gives four single-model ensembles of model simulations. For each likelihood function, Bayesian model averaging is applied to the ensemble simulations of the two models, resulting in two multi-model prediction ensembles. Predictive performance for these ensembles is evaluated using various scoring rules. Results show that RMS outperforms the commonly used scoring rules of log-score, pseudo Bayes factor based on Bayesian model evidence (BME), and continuous ranked probability score (CRPS). RMS avoids the problem of rounding error specific to log-score. Being applicable to any likelihood functions, RMS has broader applicability than BME that is only applicable to the same likelihood function of multiple models. By directly considering the relative score of candidate models at each cross-validation datum, RMS results in more plausible model ranking than CRPS. Therefore, RMS is considered as a robust scoring rule for evaluating predictive performance of single-model and multi-model prediction ensembles.  相似文献   

Probabilistic analysis of risk and mitigation of deepwater well blowouts and oil spills     

Alessandro?Caia  Alberto?Giulio?Di?Lullo  Giambattista?De?Ghetto  Alberto?GuadagniniEmail authorView author&#;s OrcID profile 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(9):2647-2666

The development of robust risk assessment procedures for offshore oil and gas operations is a major element for the assessment of the potential feedback between planned activities and the environment. We illustrate a methodological and computational framework conducive to (1) a quantitative risk analysis of deepwater well barrier failures and subsequent hydrocarbon release to the environment and (2) the analysis of the value of the deployment of conventional and/or innovative mitigation measures. Our methodological framework is grounded on historical records and combines the use of Dynamic Event Trees and Decision Trees from which we estimate probability of occurrence and impact of post-blowout events. Each sequence of response actions, which are undertaken immediately after the event or in the subsequent days, is considered within the context of appropriately structured event paths. This approach is conducive to an estimate of the expected value of key decisions and underlying technologies, with an emphasis on their potential to reduce the oil spill volume, which can critically impact the environment. Our study yields an original comparative analysis of diverse intervention strategies, and forms a basis to guiding future efforts towards the development and deployment of technologies and operating procedures yielding maximum benefit in terms of safety of operations and environmental protection.  相似文献   

Analysis of the goodness of empirical approaches in predicting explosive detonation parameters     

Fernando?G.?BastanteEmail authorView author&#;s OrcID profile  Elena?Alonso  María?Araújo  Julio?García Menéndez 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(9):2605-2618

Goodness of empirical models for predicting explosive detonation velocity and pressure was analysed using 3 databases consisting of experimental velocity and pressure measurements for different explosives. The first database was used to estimate experimental errors for detonation velocity and pressure measurements. The second database was used to compare residuals obtained by the experimental models and by various thermochemical codes. Finally, the third database, consisting of some 600 data on 130 explosive substances, was used to estimate residual bias and dispersion resulting from the application of the experimental models. Also analysed was model coherence with the ideal detonation theory. Our main conclusion is that all the models introduce bias in their predictions depending on the density and oxygen balance values of the explosive. Of those analysed, the Xiong model was notable for its good results, with residual dispersion comparable to that obtained from application of the best thermochemical codes. Our results would indicate that the Xiong model is the only model that may be compatible with the ideal detonation theory. The pressure equation derived from the ideal detonation theory and calibrated with experimental data had excellent predictive capacity.  相似文献   

An integrated Bayesian approach to the probabilistic tsunami risk model for the location and magnitude of earthquakes: application to the eastern coast of the Korean Peninsula     

Kwan-Hyuck?Kim  Yong-Sik?Cho  Hyun-Han?KwonEmail authorView author&#;s OrcID profile 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(5):1243-1257

We explored the distributional changes in tsunami height along the eastern coast of the Korean Peninsula resulting from virtual and historical tsunami earthquakes. The results confirm significant distributional changes in tsunami height depending on the location and magnitude of earthquakes. We further developed a statistical model to jointly analyse tsunami heights from multiple events, considering the functional relationships; we estimated parameters conveying earthquake characteristics in a Weibull distribution, all within a Bayesian regression framework. We found the proposed model effective and informative for the estimation of tsunami hazard analysis from an earthquake of a given magnitude at a particular location. Specifically, several applications presented in this study showed that the proposed Bayesian approach has the advantage of conveying the uncertainty of the parameter estimates and its substantial effect on estimating tsunami risk.  相似文献   

Probabilistic spatial prediction of categorical data using elliptical copulas     

Xiang?HuangView author&#;s OrcID profile  Zhizhong?WangEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1631-1644

This study uses elliptical copulas and transition probabilities for uncertainty modeling of categorical spatial data. It begins by discussing the expressions of the cumulative distribution function and probability density function of two major elliptical copulas: Gaussian copula and t copula. The basic form of spatial copula discriminant function is then derived based on Bayes’ theorem, which consists of three parts: the prior probability, the conditional marginal densities, and the conditional copula density. Finally, three kinds of parameter estimation methods are discussed, including maximum likelihood estimation, inference functions for margins and canonical maximum likelihood (CML). To avoid making assumptions on the form of marginal distributions, the CML approach is adopted in the real-world case study. Results show that the occurrence probability maps generated by these two elliptical copulas are similar to each other. However, the prediction map interpolated by Gaussian copula has a relatively higher classification accuracy than t copula.  相似文献