Oceanic exchange variability across the continental slope west coast,South Island,New Zealand

Current observations taken at depths between 630 and 830 m from the west coast South Island continental slope exhibit one‐ to four‐weekly periodicities superimposed on the semi‐diurnal tide. These variable flows at 630 m and otter large, longer‐timescale events have a significart onshore/offshore component of flow which leads to a similar transport of alongshore momentum and heat.     

A procedure on ground motion selection and scaling for nonlinear response of simple structural systems

This study presents a ground-motion selection and scaling methodology that preserves the basic seismological features of the scaled records with reduced scatter in the nonlinear structural response. The methodology modifies each strong-motion recording with known fundamental seismological parameters using the estimations of ground-motion prediction equations for a given target hazard level. It provides robust estimations on target building response through scaled ground motions and calculates the dispersion about this target. This alternative procedure is not only useful for record scaling and selection but, upon its further refinement, can also be advantageous for the probabilistic methods that assess the engineering demand parameters for a given target hazard level. Case studies that compare the performance of the proposed procedure with some other record selection and scaling methods suggest its usefulness for building performance assessment and loss models. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment on variability of extreme climate events for the Upper Thames River basin in Canada

Climate change may affect magnitude and frequency of regional extreme events with possibility of serious impacts on the existing infrastructure systems. This study investigates how the current spatial and temporal variations of extreme events are affected by climate change in the Upper Thames River basin, Ontario, Canada. A weather generator model is implemented to obtain daily time series of three climate variables for two future climate scenarios. The daily time series are disaggregated into hourly to capture characteristics of intense and rapidly changing storms. The maximum annual precipitation events for five short durations, 6‐, 12‐, 24‐, 48‐, and 72‐h durations, at each station are extracted from the generated hourly data. The frequency and seasonality analyses are conducted to investigate the temporal and spatial variability of extreme precipitation events corresponding to each duration. In addition, this study investigates the impacts of increase in temperature using reliability, resilience, and vulnerability. The results indicate that the extreme precipitation events under climate change will occur earlier than in the past. In addition, episodes of extremely high temperature may last longer up to 19·7% than under the no‐change climate scenario. This study points out that the revision of the design storms (e.g. 100‐ or 250‐year return period) is warranted for the west and the south east region of the basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Spatial scale effect on the upper soil effective parameters of a distributed hydrological model

Nonlinear dynamics and spatial variability in hydrological systems make the formulation of scaling theories difficult. Therefore, the development of knowledge related to scale effects, scaling techniques, parameterization and linkages of parameters across scales is highly relevant. The main purpose of this work is to analyse the spatial effect of the static storage capacity parameter H_u and the saturated hydraulic conductivity parameter k_s from microscale (sub‐grid level) to mesoscale (grid level) and its implication to the definition of an optimum cell size. These two parameters describe the upper soil water characteristics in the infiltration process conceptualization of the TETIS hydrological model. At microscale, the spatial heterogeneity of H_u and k_s was obtained generating random parameter fields through probability distribution functions and a spatial dependence model with pre‐established correlation lengths. The effective parameters at mesoscale were calculated by solving the inverse problem for each parameter field. Results indicate that the adopted inverse formulation allows transferring the nonlinearity of the system from microscale to the mesoscale via non‐stationary effective parameters. Their values at each cell and time step are in the range of zero to the mean value of the parameter at microscale. The stochastic simulations showed that the variance of the estimated effective parameters decreases when the ratio between mesoscale cell size and correlation length at microscale increases. For a ratio greater than 1, we found cell sizes having the characteristics of a representative elementary area (REA); in such case, the microscale variability pattern did not affect the system response at mesoscale. Copyright © 2011 John Wiley & Sons, Ltd.     

东北季风期台湾海峡的逆温现象

利用2006-2008年3个航次水文资料,结合日本海洋数据中心(JODC)的历史温度数据分析了东北季风期台湾海峡的逆温现象。结果显示,除台湾浅滩及海峡西岸浅水区外,几乎整个台湾海峡皆有逆温现象。逆温幅度和发生频率在海峡西部较高,海峡东部及粤东近海较低。逆温层上界深度春季较秋、冬季深,逆温频发区(发生频率大于60%)随着季节南北向移动,秋季频发区的最南端位于厦门近海,冬季扩展至台湾浅滩北部,春季回退至平潭近海。分析表明,浙闽沿岸水随季节南北向伸缩导致了逆温频发区的同步移动。除了季节变化外,逆温现象在2006年和2007年冬季有显著差异,2006年逆温仅出现在海峡西部近岸海域,2007年扩展至海峡东部且向南伸至粤东近岸,浙闽沿岸水的横向伸缩是造成此差异的主因。     

Interdecadal variations of surface winds over China marginal seas

Long term variability in the surface winds over the marginal seas of China is examined with a dominant-mode singular value decomposition method. Both interannual and interdecadal patterns are found to be seasonally and spatially dependent, with reanalyses and satellite remote sensing data yielding highly consistent results. The study reveals that summer monsoon winds over the East China Sea experienced an interdecadal weakening in the late 1960s and began a persistent recovery in 2005. The study also shows gradual weakening of the winter monsoon in the southern South China Sea by more than 2m/s since the 1960s, with corroboration from coastal climate stations in Borneo. This phenomenon has not been reported in previous monsoon studies.     

Interdecadal variability of the South China Sea monsoon and its relationship with latent heat flux in the Pacific Ocean

We analyzed interdecadal variability of the South China Sea monsoon and its relationship with latent heat flux in the Pacific Ocean, using NCEP wind field and OAFlux heat flux datasets. Results indicate that South China Sea monsoon intensity had an obvious interdecadal variation with a decreasing trend. Variability of the monsoon was significantly correlated with latent heat flux in the Kuroshio area and tropical Pacific Ocean. Variability of latent heat flux in the Kuroshio area had an interdecadal increasing trend, while that in the tropical Pacific Ocean had an interdecadal decreasing trend. Latent heat flux variability in these two sea areas was used to establish a latent heat flux index, which had positive correlation with variability of the South China Sea monsoon. When the latent heat flux was 18 months ahead of the South China Sea monsoon, the correlation coefficient maximized at 0.58 (N=612), with a 99.9% significance level of 0.15. Thus, it is suggested that latent heat flux variability in the two areas contributes greatly to interdecadal variability of the South China Sea monsoon.     

基于分形理论的灌溉水有效利用系数空间尺度变异

基于2010 年度广东省75 处样点灌区的实测资料和遥感图像, 应用分形理论, 采用网格盒维数法计算了各样点灌区盒维数, 结果表明:广东省灌区具有明显的分形特征, 盒维数介于1.0004~1.675 之间, 分维数均值为1.308, 形状指数均值为0.335, 都随灌区规模呈同步减小趋势。不同规模灌区盒维数大型灌区(1.442) > 中型灌区(1.287) > 小型灌区(1.195)。灌溉水有效利用系数与空间分形特征诸因子中以非空网格对数值最高, 相关性达到0.941。基于此, 建立了不同网格尺度下的灌区面积与灌溉水有效利用系数和盒维数空间尺度变异函数。同时, 从影响灌溉水有效利用系数的众多因素中, 选取了工程评价值、盒子维数、灌区形状指数、参考作物蒸发蒸腾量ET0 和当年降水量5 项指标进行了空间格局影响因素分析, 结合灰关联计算结果表明:空间各影响因素中以工程评价因子的关联度最高, 达到0.8478, 其次为形态特征因子, 自然气象因子影响最小。尝试利用分形理论为不同面积尺度灌区灌溉水有效利用系数的空间变异规律分析和尺度转换提供一种新的思路, 该结果对于指导灌区投资改造和规划建设, 具有较强的理论和应用价值。     

新疆奇台绿洲农田灌溉前后土壤水盐时空变异性研究

对比研究了新疆奇台县绿洲农田灌溉前后土壤水盐的时空变异特征。结果表明,灌溉前,剖面各层土壤含水量较低（18.43%～20.30%之间）,且呈中等（偏弱）变异性。大水漫灌后1周,除40～60 cm和100～120 cm土层外,其他层土壤含水量均变为弱变异性;剖面平均土壤含水量升高6.90%,脱盐率达11.37%,其中,表层（0～20 cm）土壤水分增加率（50.93%）及脱盐率（27.14%）最大,底层（100～120 cm）土壤水分增加率（26.59%）及脱盐率（-4.76%）最小。灌后3周,剖面平均含水量减少3.64%,其中,表层（0～20 cm）失水率（28.84%）最大;剖面平均脱盐率降为9.63%,0～60 cm土层平均脱盐率（7.58%）减小,而60～120 cm土层脱盐率（11.01%）增大。除20～40 cm土层外,其他层含水量变异性均与灌前一致,说明含水量已接近灌前水平。至灌后第3周,各层含盐量、剖面平均盐分（中等变异性）及平均水分（弱变异性）含量的变异性未变,但其变异系数均在减小;剖面平均含水量的空间自相关性由中等转为强烈,变程一直增大,而平均含盐量均具有强烈的空间自相关性,变程先增大后减小。     

Vegetation greenness modeling in response to climate change for Northeast Thailand

In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.