The Impacts of Socioeconomic Development and Climate Change on Severe Weather Catastrophe Losses: Mid-Atlantic Region (MAR) and the U.S.

One strand of research relates the magnitude of severe weather disasters to climatic and human development factors; another highlights dramatic growth in catastrophe losses. However, there have been few attempts to put the two strands together. Here we use an explicit modeling framework to determine the contribution of climate variability relative to human factors in reported catastrophe losses. We then examine how future climate change can be expected to affect losses from natural disasters. Simultaneous regression models are constructed from three equations in which the dependent variables are U.S. flood loss, U.S. hurricane loss and U.S. catastrophe loss. Then two kinds of simulation under two climate change scenarios explore how climate change would affect losses. The climate change scenarios respectively project 13.5% and 21.5% increases in annual precipitation. The first simulation increases only the mean value of annual precipitation; the second simulation assumes that the mean and standard deviation of annual precipitation change in the same proportion. Results show that the growth in reported losses from weather-related natural disasters is due mainly to three socioeconomic factors: inflation, population growth and growth in per capita real wealth. However, weather variables such as precipitation and the number of hurricanes per period also clearly affect losses. The three stage least squares (3SLS) simultaneous equation model shows that a 1% increase in annual precipitation would enlarge catastrophe loss by as much as 2.8%. These findings are suggestive as planning signals to decision makers.     

Uncertainty analysis using the WRF maximum likelihood ensemble filter system and comparison with dropwindsonde observations in Typhoon Sinlaku (2008)

In this study, the maximum likelihood ensemble filter (MLEF) is applied to a tropical cyclone case to identify the uncertainty areas in the context of targeting observations, using the WRF model. Typhoon Sinlaku (2008), from which dropwindsonde data are collected through THORPEX Pacific Asian Regional Campaign (TPARC), is selected for the case study. For the uncertainty analysis, a measurement called the deep layer mean (DLM) wind variance is employed. With assimilation of conventional rawinsonde data, the MLEF-WRF system demonstrated stable data assimilation performance over multiple data assimilation cycles and produced high uncertainties mostly in data-void areas, for the given tropical cyclone case. Dropwindsonde deployment through T-PARC turned out to occur inside or near the weak uncertainty areas that are identified through the MLEF-WRF system. The uncertainty analysis using the MLEF method can provide a guide for identifying more effective targeting observation areas.     

Inverse relationship between the equatorial eastern Pacific annual-cycle and ENSO amplitudes in a coupled general circulation model

We propose a dynamical interpretation of the inverse relationship between the tropical eastern Pacific annual-cycle (AC) amplitude and the El Niño-Southern Oscillation (ENSO) amplitude, based on a pre-industrial simulation of Geophysical Fluid Dynamics Laboratory Couple climate model 2.0 with a fixed concentration of greenhouse gases spanning approximately 500 years. The slowly varying background conditions over more than a decade alternately provided favorable conditions for two opposite regimes, namely the ‘strong AC—weak ENSO regime’ and the ‘weak AC—strong ENSO regime’. For the weak AC—strong ENSO regime, the tropical eastern Pacific shows meridional-asymmetric surface warming with an emphasis on the southern part, leading to weakening of both the zonal trade wind and the cross equatorial southerly wind, as well as deepening of both the thermocline and mixed layer. The deeper mixed layer, weaker southerly wind, and reduced zonal gradient of the mean sea surface temperature due to tropical eastern Pacific warming all acts to reduce the AC. Conversely, the ENSO was intensified by the deeper mixed layer and deeper thermocline depth (thermocline feedback), but suppressed by the deeper thermocline depth (Ekman feedback) and the reduced zonal temperature gradient. We also computed the coupling strengths of the ENSO and AC, defined as the linear regression coefficients of the zonal and meridional wind stresses against the eastern Pacific SST, respectively. The coupling strengths of both the AC and ENSO are larger when they are intensified, and vice versa. All processes for the weak AC—strong ENSO regime operate in the opposite manner for the strong AC—weak ENSO regime.     

Probabilistic approach for active control based on structural energy

This paper presents an active control algorithm using the probability density function of structural energy. It is assumed that structural energy under excitation has a Rayleigh probability distribution. This assumption is based on the fact that the Rayleigh distribution satisfies the condition that the structural energy is always positive and the occurrence probability of minimum energy is zero. The magnitude of the control force is determined by the probability that the structural energy exceeds the specified target critical energy, and the sign of the control force is determined by the Lyapunov controller design method. The proposed control algorithm shows much reduction of peak responses under seismic excitation compared with the LQR controller, and it can consider the control force limit in the controller design. Also, the chattering problem which sometimes occurs in the Lyapunov controller can be avoided. Copyright © 2003 John Wiley & Sons, Ltd.     

Computation of Tsunamis in the East (Japan) Sea Using Dynamically Interfaced Nested Model

-- A study of 1983 and 1993 tsunami events in the East (Japan) Sea using multigrid dynamically-interfaced finite difference models was performed to produce detailed features of coastal inundations along the eastern coast of Korea. The computational domain is composed of several subregions with different grid sizes connected in parallel or inclined directions. The innermost subregion represents the coastal alignment reasonably well and has a grid size of about 30 meters. Numerical simulations have been performed in the framework of shallow-water equations (linear, as well as nonlinear) over the plane or spherical coordinate system, depending on the dimensions of the subregion. Results of simulations show the general agreements with the observed data of the runup height for both tsunamis. The evolution of the distribution function of tsunami heights is studied numerically and it shows a tendency to the log-normal curve for a long distance from the source.     

Geothermal gradient of the upper mantle beneath Jeju Island, Korea: Evidence from mantle xenoliths

Abstract Ultramafic xenoliths found in alkali basalts from Jeju Island, Korea are mostly spinel lherzolites accompanied by subordinate amount of spinel harzburgites and pyroxenites. The combination of results from a two-pyroxene geothermometer and Ca-in-olivine geobarometer yields temperature–pressure (T–P) estimates for spinel peridotites that fall in experimentally determined spinel lherzolite field in CaO-Fe-MgO-Al₂O₃-SiO₂-Cr₂O₃ (CFMASCr) system. These T–P data sets have been used to construct the Quaternary Jeju Island geotherm, which defines a locus from about 13 kbar at 880°C to 26 kbar at 1040°C. The geothermal gradient of Jeju Island is greater than that of the conventional conductive models, and may be as a result of a thermal perturbation by the heat input into the lithospheric mantle via the passage and emplacement of magma. Spinel–lherzolite is the main constituent rock-type of the lithospheric mantle beneath Jeju Island. Pyroxenites may be intercalated in peridotites at similar depth and temperature as re-equilibrated veins or lenses.     

The Collimated Propagation Causes of Astrophysical and Laboratory Jets

Astronomy Reports - The use of Z-pinch facilities makes it possible to carry out well-controlled and diagnosable laboratory experiments to study laboratory jets with scaling parameters close to...     

Application of multiple indicator Kriging for RMR value estimation in areas of new drift excavation during mine site redevelopment

Rock mass rating (RMR) values along additional drifts that are to be constructed during mine site redevelopment (Gagok mine, Korea) were estimated using multiple criteria indicator Kriging with borehole RMR and electrical resistivity tomography data. This study outlines two potential correction methods that supplement indicator Kriging and that can reduce error, allowing more accurate estimation of RMR values. The correction methods used a filtering of indirect data affected by drifts (FIED) method to reduce uncertainties and errors within electrical resistivity tomography data caused by changes in setup and the location of existing drifts. In addition, a correction indicating accurate representation of indirect data (CARI) method was used to resolve distortions in drilling log results. This meant that 73 % of the estimated RMR values were assigned to the correct RMR class, with only 1 % of these values being overestimated. The sensitivity of the FIED method was 4 %, with the linear CARI method having a sensitivity of 56–60 % and the logarithmic CARI method having a sensitivity of 61–65 %.