Prediction of the number of equivalent cycles for earthquake motion

This paper addresses new prediction models for computing the number of equivalent cycles in liquefaction analyses. Three models are presented for the Italian seismicity as a function of synthetic ground motion parameters that are often available from earthquake data web-sites immediately after events. In particular, it is observed that the number of earthquake cycles can be best estimated from the five following parameters: peak ground acceleration; epicentral distance; Arias Intensity; the mean period; and, the frequency of zero crossings. However, strong estimations can be obtained from the first three parameters only. We use statistical indicators to determine the goodness of the models and the usefulness of the selected independent variables, and we present a comparative analysis to validate our predictive equations. Moreover, this paper describes the existing correlation between magnitude and cycle numbers. The study is primarily based on Italian acceleration records, even if the database is also expanded to recorded European, Japanese and American events to amplify the magnitude values range. These simplified models are useful in addressing practical earthquake engineering problems which require the knowledge of number of equivalent cycles.     

A regional climate model for the western United States

A numerical approach to modeling climate on a regional scale is developed whereby large-scale weather systems are simulated with a global climate model (GCM) and the GCM output is used to provide the boundary conditions needed for high-resolution mesoscale model simulations over the region of interest. In our example, we use the National Center for Atmospheric Research (NCAR) community climate model (CCM1) and the Pennsylvania State University (PSU)/NCAR Mesoscale Model version 4 (MM4) to apply this approach over the western United States (U.S.). The topography, as resolved by the 500-km mesh of the CCM1, is necessarily highly distorted, but with the 60-km mesh of the MM4 the major mountain ranges are distinguished. To obtain adequate and consistent representations of surface climate, we use the same radiation and land surface treatments in both models, the latter being the recently developed Biosphere-Atmosphere Transfer Scheme (BATS). Our analysis emphasizes the simulation at four CCM1 points surrounding Yucca Mountain, NV, because of the need to determine its climatology prior to certification as a high-level nuclear waste repository.We simulate global climate for three years with CCM1/BATS and describe the resulting January surface climatology over the western U.S. The details of the precipitation patterns are unrealistic because of the smooth topography. Selecting five January CCM1 storms that occur over the western U.S. with a total duration of 20 days for simulation with the MM4, we demonstrate that the mesoscale model provides much improved wintertime precipitation patterns. The storms in MM4 are individually much more realistic than those in CCM1. A simple averaging procedure that infers a mean January rainfall climatology calculated from the 20 days of MM4 simulation is much closer to the observed than is the CCM1 climatology. The soil moisture and subsurface drainage simulated over 3–5 day integration periods of MM4, however, remain strongly dependent on the initial CCM1 soil moisture and thus are less realistic than the rainfall. Adequate simulation of surface soil water may require integrations of the mesoscale model over time periods.The National Center for Atmospheric Research is sponsored by the National Science Foundation. of up to several months or longer.     

温室效应引起的中国区域气候变化的数值模拟Ⅱ:中国区域气候的可能变化

使用RegCM2区域气候模式单向嵌套澳大利亚CSIRO R21L9全球海-气耦合模式,进行了温室气体CO2加倍对中国气候变化影响的数值试验研究。该文为第2部分,对敏感性试验结果进行的分析。分析表明:由于温室效应,中国区域的地面气温特别是在冬季和北方将有明显升高,区域年平均的升高值为2.5℃;同时区域内日最高和最低气温将明显上升,日较差将减小。结果还表明,在CO2倍增条件下,中国区域降水将呈增加趋势,区域年平均的增加值为12％;以夏季的增加率最大,其次为冬季。中国汛期降水将呈现出“三类雨型”出现频率增多的趋势。南方的大雨日数将有所增加。此外,生成和影响中国的台风数目也将有所增加。温室气体的增加同时对环流场产生影响,如导致500 hPa高度场的升高。