New analytical and numerical approaches for geopotential modeling

 The standard analytical approach which is applied for constructing geopotential models OSU86 and earlier ones, is based on reducing the boundary value equation to a sphere enveloping the Earth and then solving it directly with respect to the potential coefficients _n,m . In an alternative procedure, developed by Jekeli and used for constructing the models OSU91 and EGM96, at first an ellipsoidal harmonic series is developed for the geopotential and then its coefficients _n,m ^e are transformed to the unknown _n,m . The second solution is more exact, but much more complicated. The standard procedure is modified and a new simple integral formula is derived for evaluating the potential coefficients. The efficiency of the standard and new procedures is studied numerically. In these solutions the same input data are used as for constructing high-degree parts of the EGM96 models. From two sets of _n,m (n≤360,|m|≤n), derived by the standard and new approaches, different spectral characteristics of the gravity anomaly and the geoid undulation are estimated and then compared with similar characteristics evaluated by Jekeli's approach (`etalon' solution). The new solution appears to be very close to Jekeli's, as opposed to the standard solution. The discrepancies between all the characteristics of the new and `etalon' solutions are smaller than the corresponding discrepancies between two versions of the final geopotential model EGM96, one of them (HDM190) constructed by the block-diagonal least squares (LS) adjustment and the other one (V068) by using Jekeli's approach. On the basis of the derived analytical solution a new simple mathematical model is developed to apply the LS technique for evaluating geopotential coefficients. Received: 12 December 2000 / Accepted: 21 June 2001     

Vertical distribution features of atmospheric water vapour in the Po valley area

Two sets of radiosounding measurements, taken at different hours from some stations in the Po Valley area, were examined in order to obtain the values of precipitable waterw and determine the shapes of the vertical distribution curves of absolute humidity. From these curves, we calculated the bestfit values of scale heightsH ₁ andH ₂ in the 0÷5 km and 5÷10 km altitude intervals, respectively. The analysis of the radiosounding data clearly shows that parametersw andH ₁ are closely related to the evolutionary features of the meteorological conditions on synoptic scale and are influenced, to a lesser extent, by the diurnal variations in the atmospheric ground layer. Seasonal average curves of temperature and absolute humidity, as functions of altitude, were also defined from the radiosounding measurements taken at various hours of the day. Moreover, interpolation methods in time (applied to a 12-hour range) and in space (range of about 300 km) were proposed for determining parametersw andH ₁ from the radiosounding measurements taken at different hours from the same station or from different stations at the same hour. Reliability tests, made by comparing the same station or from different stations at the same hour. Reliability tests, made by comparing the values given by the interpolation methods with those directly obtained from the radiosounding measurements, show that these evaluations ofw andH ₁ are affected by standard errors of estimate, which are comparable to the errors usually made in analyzing the radiosounding data.     

轴压下两体力学模型的转化条件及影响因素分析

接触界面的相互作用是影响工程稳定的重要因素,基于接触面两侧介质的实际受力状态,采用一体两介质力学模型与两体两介质力学模型加以描述。通过一体和两体模型试件的轴压破坏试验,分析了两种模型的力学响应的差异,并认为：一体两介质力学模型在符合一定条件情况下可以转变为两体两介质力学模型。此外,还对影响两种力学模型性能的参数进行了分析。提出对一体两介质力学模型力学性能产生影响的参量是低强度介质与高强度介质的静载极限强度比k以及两种介质之间的黏结力c;对两体两介质力学模型力学性能产生影响的主要参量除了k之外,尚有两种介质的断裂韧度比? 、体积比? 以及界面的粗糙程度     

Digital Archiving and On-line Publishing of Old Relief Models

Abstract

Although people rarely think of relief models when speaking about cartographic products, these artefacts are probably the most impressive way of visualizing landscapes. Unlike traditional maps or globes, most relief models are unique, vulnerable hand-made objects. Digital archiving is an important step in their preservation. There are special tools for this task, but these equipments are rather expensive, and libraries or other institutes that usually own these models cannot spend too much. The authors examined various on-line tools to create digital 3D representation of relief models using a set of photographs as source. These tools create point cloud and textured triangle mesh based on matching patterns on the photos. A workflow was developed which uses these web services and produces the digital 3D version of relief models. This paper introduces the method, discusses the details of successful photographing, the possible post-processing of the results. A new web site, using the X3DOM technology to show the digitized models to the general public, is also introduced.     

关于固结度计算的一点看法

通过探寻渗透系数、压缩系数(或体积压缩系数)与孔隙比在固结过程中的变化规律来确定固结系数与固结时间的关系并将其用于固结度计算是无益的,原因在于固结度计算公式只在固结系数为常数时才成立。     

Mini-inflation prior to the cosmic confinement transition?

The onset of the confinement transition in the early universe is studied within the Friedmann model. Exploiting a bag model equation of state for the deconfined matter, which is generalized to include also metastable states, the possibility of a mini-inflationary epoch is demonstrated. A criterion of metastability is derived to estimate parameters of this mini-inflation.     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.     

Forecasting ocean wave energy: The ECMWF wave model and time series methods

Recently, the technology has been developed to make wave farms commercially viable. Since electricity is perishable, utilities will be interested in forecasting ocean wave energy. The horizons involved in short-term management of power grids range from as little as a few hours to as long as several days. In selecting a method, the forecaster has a choice between physics-based models and statistical techniques. A further idea is to combine both types of models. This paper analyzes the forecasting properties of a well-known physics-based model, the European Center for Medium-Range Weather Forecasts (ECMWF) Wave Model, and two statistical techniques, time-varying parameter regressions and neural networks. Thirteen data sets at locations in the Atlantic and Pacific Oceans and the Gulf of Mexico are tested. The quantities to be predicted are the significant wave height, the wave period, and the wave energy flux. In the initial tests, the ECMWF model and the statistical models are compared directly. The statistical models do better at short horizons, producing more accurate forecasts in the 1-5 h range. The ECMWF model is superior at longer horizons. The convergence point, at which the two methods achieve comparable degrees of accuracy, is in the area of 6 h. By implication, the physics-based model captures the underlying signals at lower frequencies, while the statistical models capture relationships over shorter intervals. Further tests are run in which the forecasts from the ECMWF model are used as inputs in regressions and neural networks. The combined models yield more accurate forecasts than either one individually.