New Methodology to Characterize Shear Behavior of Joints by Combination of Direct Shear Box Testing and Numerical Simulations

A new procedure is presented, which combines big shear box tests on rocks and corresponding numerical simulations with explicit consideration of joint roughness to get deeper insight into the shear behavior of rock joints. The procedure consists of three parts: (1) constant normal load- or CNS-shear box tests with registration of shear- and normal-components of stress and displacements and deduction of basis rock mechanical parameters; (2) high resolution 3D-scanning of joint surface to deduce joint topography; and (3) set-up, run and evaluation of 3-dimensional numerical model with explicit duplication of joint roughness as back-analysis of shear box tests. The numerical back-analysis provides deeper insight into the joint behavior at the micro-scale. Several parameters can be deduced, like micro-slope angle distribution, aperture size distribution, local normal stress distribution and detailed analysis of dilation in relation to shear direction. The potential of the new procedure is illustrated exemplary by shear box tests on slate.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

Probabilistic Seismic Hazard Assessment Along the Southeastern Coast of Vietnam

On the basis of the analysis of geological, tectonic characteristics and earthquake manifestation features, a causative relation between geodynamic regime and seismicity has been established for the southeastern coastal zone and continental shelf of Vietnam. The probabilistic methods have been used to evaluate ground shaking effects at Nha Trang city aswell as for the entire study area. Short, intermediate and long term predictions of ground shaking (in the form of peak ground accelerationmaps) show high risks in the coastal zone of central Vietnam and in the southeastern continental shelf of the country.     

Fine-resolution regional climate model simulations of the impact of climate change on tropical cyclones near Australia

Fine-resolution regional climate simulations of tropical cyclones (TCs) are performed over the eastern Australian region. The horizontal resolution (30 km) is fine enough that a good climatological simulation of observed tropical cyclone formation is obtained using the observed tropical cyclone lower wind speed threshold (17 m s^–1). This simulation is performed without the insertion of artificial vortices (bogussing). The simulated occurrence of cyclones, measured in numbers of days of cyclone activity, is slightly greater than observed. While the model-simulated distribution of central pressures resembles that observed, simulated wind speeds are generally rather lower, due to weaker than observed pressure gradients close to the centres of the simulated storms. Simulations of the effect of climate change are performed. Under enhanced greenhouse conditions, simulated numbers of TCs do not change very much compared with those simulated for the current climate, nor do regions of occurrence. There is a 56% increase in the number of simulated storms with maximum winds greater than 30 m s^–1 (alternatively, a 26% increase in the number of storms with central pressures less than 970 hPa). In addition, there is an increase in the number of intense storms simulated south of 30°S. This increase in simulated maximum storm intensity is consistent with previous studies of the impact of climate change on tropical cyclone wind speeds.     

Seasonal variations of atmospheric sulfur dioxide and dimethylsulfide concentrations at Amsterdam Island in the southern Indian Ocean

Daily measurements of atmospheric sulfur dioxide (SO₂) concentrations were performed from March 1989 to January 1991 at Amsterdam Island (37°50 S–77°30 E), a remote site located in the southern Indian Ocean. Long-range transport of continental air masses was studied using Radon (²²²Rn) as continental tracer. Average monthly SO₂ concentrations range from less than 0.2 to 3.9 nmol m^-3 (annual average = 0.7 nmol m^-3) and present a seasonal cycle with a minimum in winter and a maximum in summer, similar to that described for atmospheric DMS concentrations measured during the same period. Clear diel correlation between atmospheric DMS and SO₂ concentrations is also observed during summer. A photochemical box model using measured atmospheric DMS concentrations as input data reproduces the seasonal variations in the measured atmospheric SO₂ concentrations within ±30%. Comparing between computed and measured SO₂ concentrations allowed us to estimate a yield of SO₂ from DMS oxidation of about 70%.     

Covariations in oceanic dimethyl sulfide,its oxidation products and rain acidity at Amsterdam Island in the Southern Indian Ocean

Simultaneous measurements of rain acidity and dimethyl sulfide (DMS) at the ocean surface and in the atmosphere were performed at Amsterdam Island over a 4 year period. During the last 2 years, measurements of sulfur dioxide (SO₂) in the atmosphere and of methane sulfonic acid (MSA) and non-sea-salt-sulfate (nss-SO₄ ^2-) in rainwater were also performed. Covariations are observed between the oceanic and atmospheric DMS concentrations, atmospheric SO₂ concentrations, wet deposition of MSA, nss-SO₄ ^2-, and rain acidity. A comparable summer to winter ratio of DMS and SO₂ in the atmosphere and MSA in precipitation were also observed. From the chemical composition of precipitation we estimate that DMS oxidation products contribute approximately 40% of the rain acidity. If we consider the acidity in excess, then DMS oxidation products contribute about 55%.     

Estimating the error in vertically interpolated forecast‐observation differences: U‐ and v‐wind components

Abstract

Data assimilation in numerical weather forecasting corrects current forecast values by subtracting a portion of interpolated forecast‐minus‐observation differences at the points of a three‐dimensional grid. Deviations used in updating a forecast data field are forecast errors obtained or derived from observations available at update time. When observations are missing at mandatory levels, construction of full vertical soundings by interpolation introduces extraneous errors. The present paper is concerned with determination of the error in vertical extrapolations of surface winds, and of aircraft and satellite cloud‐tracked winds. In addition it examines the effect on accuracy of using location‐specific statistics compared to averaged statistics as the basis for the interpolation weighting scheme and compares errors of one‐ and two‐variable interpolations.

Interpolation accuracy tests demonstrate the influence of the interpolation scheme on the quality of interpolated information used in forecast updating. The results show that the level of accuracy exceeds the benchmark provided by monthly mean forecast error values only with bivariate interpolation of wind components from off‐level data sources.     

Seasonal variation of atmospheric dimethylsulfide at Amsterdam Island in the southern Indian Ocean

Daily measurements of atmospheric concentrations of dimethylsulfide (DMS) were carried out for two years in a marine site at remote area: the Amsterdam Island (37°50S–77°31E) located in the southern Indian Ocean. DMS concentrations were also measured in seawater. A seasonal variation is observed for both DMS in the atmosphere and in the sea-surface. The monthly averages of DMS concentrations in the surface coastal seawater and in the atmosphere ranged, respectively, from 0.3 to 2.0 nmol l^-1 and from 1.4 to 11.3 nmol m^-3 (34 to 274 pptv), with the highest values in summer. The monthly variation of sea-to-air flux of DMS from the southern Indian Ocean ranges from 0.7 to 4.4 mol m^-2 d^-1. A factor of 2.3 is observed between summer and winter with mean DMS fluxes of 3.0 and 1.3 mol m^-2 d^-1, respectively.     

Annual variation of atmospheric carbonyl sulfide in the marine atmosphere in the Southern Indian Ocean

Measurements of the concentrations of carbonyl sulfide (COS) in the marine atmosphere were made over a period of two years in the southern Indian Ocean (Amsterdam Island, 37°50 S–77°31 E; March 1987–February 1988 and April 1989–February 1990). The mean atmospheric COS concentration for the whole period was 475±48 pptv (n=544). Atmospheric COS concentrations show no significant seasonal variation with a summer to winter ratio of 1.05. Taking into account the observed variability of the atmospheric COS concentration (10%), a value of 1.4 yr is estimated as a lower limit for the atmospheric COS lifetime. A comparison of the COS data at Amsterdam Island with those obtained in the Southern Hemisphere in the past 12 yr does not reveal any significant trend in the tropospheric background COS mixing ratio.     

Changes in heat wave characteristics over Extremadura (SW Spain)

Theoretical and Applied Climatology - Heat wave (HW) events are becoming more frequent, and they have important consequences because of the negative effects they can have not only on the human...