An integrated web-based air pollution decision support system – a prototype

To efficiently and effectively monitor and mitigate air pollution in the urban environment, it is of paramount importance to integrate into a unified whole air pollutant concentration databases coming from different sources including the ground-based stations, mobile sensors, remote sensing, atmospheric-chemical-transport models and social media for the analysis and unraveling of the complex air pollution processes in space and time. This study constructs and implements for the first time a prototype of the fully integrated air pollution decision support system (APDSS) that put together in an integrated manner all relevant multi-scale, multi-type and multi-source data for decision-making on urban air pollution. The prototype contains the main system that handles the multi-source, multi-type and multi-scale databases, queries, visualization and data mining algorithms and the integrated modules that individually and holistically capitalize on the power of the ground-based stations, ground and aerial mobile sensors, satellite-borne remote-sensing technologies, atmospheric-chemical-transport models and social media. It renders a solid scientific foundation and system development methodology for the study of the spatiotemporal air pollution profiles crucial to the mitigation of urban air pollution. Real-life applications of the prototype are employed to illustrate the functionality of the APDSS.     

Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.     

Towfish orientation and position estimation

The towfish location and orientation problems that arise in using side-scan sonar to detect objects on the sea bottom are treated separately. Data which locate the towfish relative to the ship are usually deteriorated by multipath receptions and other effects. In order to overcome this serious degradation in the location measurements, a modified Kalman filter is proposed. An estimate of the state transition matrix for this filter is derived, and a means of switching between two Kalman gains is suggested. The feasibility of the proposed filter is justified by a case study. Improved estimates of towfish pitch and heading measurements are obtained by a separate system employing model identification and subsequent Kalman filtering. Application of these methods to data from similar towed side-scan sonar systems should yield significant gains in object location accuracy     

Numerical solutions for flow in porous media

A numerical approach is proposed to model the flow in porous media using homogenization theory. The proposed concept involves the analyses of micro‐true flow at pore‐level and macro‐seepage flow at macro‐level. Macro‐seepage and microscopic characteristic flow equations are first derived from the Navier–Stokes equation at low Reynolds number through a two‐scale homogenization method. This homogenization method adopts an asymptotic expansion of velocity and pressure through the micro‐structures of porous media. A slightly compressible condition is introduced to express the characteristic flow through only characteristic velocity. This characteristic flow is then numerically solved using a penalty FEM scheme. Reduced integration technique is introduced for the volumetric term to avoid mesh locking. Finally, the numerical model is examined using two sets of permeability test data on clay and one set of permeability test data on sand. The numerical predictions agree well with the experimental data if constraint water film is considered for clay and two‐dimensional cross‐connection effect is included for sand. Copyright © 2003 John Wiley & Sons, Ltd.     

Amplitude ratios of several groups of variable stars

The observed positions of classical cepheids, RR Lyrae stars, Scuti stars and dwarf cepheids in the logg-logT _e plane form a continuous sequence, thereby defining the location of maximum instability. The amplitude ratio (the ratio of radial velocity amplitude to light amplitude) is small for variables at the upper end of the instability strip and increases almost linearly towards the lower end of the strip. The theory of radial pulsation predicts the trend of this correlation.     

基于尺度空间的分层聚类方法及其在遥感影像分类中的应用

基于尺度空间的分层聚类方法（ＳＳＨＣ）是一种以热力学非线性动力机制为理论基础的新型聚类算法,是视觉松驰化过程的模拟。与传统基于统计方法的聚类算法相比较,ＳＳＨＣ具有样本空间可服从自由分布、通过规则可获取最优聚类中心点及类别、可在聚类过程中融合后验知识等优点。本文从聚类和热力学运动机制和视觉模拟过程出发,对ＳＳＨＣ聚类算法进行综合分析,并对如何生成聚类树的过程进行详细描述邮通过融合点的部分自由能进行     

Field investigation of deformation characteristics and stress mobilisation of a soil slope

Stress mobilisation and deformation of a slope are important for engineers to carry out reliable design of retaining systems. However, most case histories reported mainly on the response of pore water pressure (PWP), whereas knowledge about the stress deformation characteristics of slope is limited. In this study, a saprolitic soil slope was instrumented to monitor not only the responses of PWP but also horizontal stress and horizontal displacement. To assist in the interpretation of field data, a series of laboratory tests was conducted to characterise volume change behaviour of the soil taken from the site, under the effects of both net stress and suction. During a rainstorm event when positive PWP built up, a remarkably large displacement of 20 mm was recorded between 5.5- and 6-m depths, and the top 5 m of the slope exhibited translational downslope movement. This caused an increase in Bishop’s effective horizontal stress by 350 %, which reached a peak value close to 40 % of a Bishop’s effective passive stress. During the subsequent dry season when suction was recovered, an upslope rebound of 10 mm was recorded. Comparison of field and laboratory data reveals that the rebound was attributed to suction-induced soil shrinkage. This rebound led to a decrease in the Bishop’s effective horizontal stress previously built up during the storm event.     

Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.