Examination of model predictions at different horizontal grid resolutions

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs and data requirements increase significantly with increasing grid resolution. Therefore, it is important to examine, for any given application, whether the expected benefit of increased grid resolution justifies the extra costs. In this study, we examine temperature and ozone observations and model predictions for three high ozone episodes that occurred over the northeastern United States during the summer of 1995. In the first set of simulations, the meteorological model RAMS4a was run with three two-way nested grids of 108/36/12 km grid spacing covering the United States and the photochemical model UAM-V was run with two grids of 36/12 km grid spacing covering the eastern United States. In the second set of simulations, RAMS4a was run with four two-way nested grids of 108/36/12/4 km grid spacing and UAM-V was run with three grids of 36/12/4 km grid spacing with the finest resolution covering the northeastern United States. Our analysis focuses on the comparison of model predictions for the finest grid domain of the simulations, namely, the region overlapping the 12 km and 4 km domains. A comparison of 12 km versus 4 km fields shows that the increased grid resolution leads to finer texture in the model predictions; however, comparisons of model predictions with observations do not reveal the expected improvement in the predictions. While high-resolution modeling has scientific merit and potential uses, the currently available monitoring networks, in conjunction with the scarceness of highly resolved spatial input data and the limitations of model formulation, do not allow confirmation of the expected superiority of the high-resolution model predictions.The U.S. Governments right to retain a non-exclusive royalty-free licence in and to any copyright is acknowledged.     

Soft intervention technology as a tool for integrated coastal zone management

After introducing soft defence techniques as an alternative to hard defence techniques, the need is emphasized to consider the coastal area as an integral system. By recalling the main driving factors for coastal management: conflict resolution, resilience and sustainability, we logically arrive at the concepts of ecological engineering and ecotechnology, which are increasingly acknowledged as possible solutions to achieve sustainable use of coastal space as a resource. In this context, we refer to the principles of self design and of ecosystem conservation. In order to deal with real situations we are in need of fundamental ‘tools’ for the application of the soft intervention technology approach. We therefore introduce the concept of physiographic units and develop an initial elaboration for a coastal stretch and for coastal wetlands. The latter deserve more attention because of the already established practices of ecotechnology, at least as far as water and soil quality are concerned, but certainly also concerning morphology, especially in the future. We conclude by briefly discussing how activities undertaken in two research projects currently being conducted under the framework of the Marine Science and Technology Program of the Commission of the European Communities are expected to contribute to the concepts introduced here.     

浅谈校园网ARP欺骗攻击与防御

ARP欺骗木马病毒是校园网络中经常出现的病毒攻击形式．基于ARP协议的概念和工作原理,并通过分析ARP欺骗的工作原理,提出了几种可行的解决ARP欺骗攻击的实用方法,以达到防范并解决ARP欺骗的目的．参5．     

Conservation Threats Due to Human-Caused Increases in Fire Frequency in Mediterranean-Climate Ecosystems

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas.     

东北区域空气质量时空分布特征及重度污染成因分析

东北已成为我国又一个霾污染多发和重发区域.采用2013～2017年东北区域大气污染物地面监测数据、卫星数据和气象数据等信息,探讨了中国东北地区空气质量时空分布特征与重度污染成因.结果表明,"沈阳-长春-哈尔滨"带状城市群是全年污染最严重的区域,空气质量指数(AQI)的空间分布具有明显的季节性,冬季污染最严重,春季吉林省西部周围为椭圆形污染区,夏季和秋季大部分时间空气质量最佳.3个典型的霾污染时期是10月下旬和11月上旬(即秋末和初冬,时期一),12月下旬和1月(即冬季最冷的时候,时期二),及4月到5月中旬(即春季沙尘和农业耕作期).时期一,季节性作物残茬焚烧和冬季采暖用煤燃烧产生的PM_(2.5)强排放是极端霾事件发生的主要原因(AQI 300);时期二,在最严寒月份里,重度霾污染事件(200 AQI 300),主要由燃煤和汽车燃料消耗的PM_(2.5)排放量高,大气边界层较低,以及大气扩散性差等共同引起;时期三,春季PM_(10)浓度较高,主要是由内蒙古中部退化草原的风沙和吉林省西部裸地的区域性扬尘传输造成的.同时,当地农业耕作本身也释放PM_(10),并提升了裸土的人为源矿物尘的排放强度.     

Assumptions beyond the science: encouraging cautious conclusions about functional magnetic resonance imaging research on organizational behavior

Functional magnetic resonance imaging (fMRI) is likely to become the major tool for studying the neural underpinnings of organizational behavior. It is a technique for brain imaging that, according to advocates, provides information about which areas of the brain are activated during organizational processes (e.g., leadership and decision‐making). In this article, we take a critical look at this tool from a technical perspective. In particular, we take the reader through the assumptions that must be made at the three main steps of the research process (study design, data capture, and interpretation of results) in order to draw conclusions about organizational phenomena from fMRI research. Applying this analysis to three case studies demonstrates the gap between what fMRI can actually tell us and the claims often made about the contribution of fMRI to understanding and improving organizational behavior. Our discussion provides researchers with a series of recommendations oriented toward optimizing the use of fMRI to help it live up to its potential in the field of organizational behavior and consumers with a means of evaluating fMRI research in order to draw appropriate and warranted conclusions. Copyright © 2016 John Wiley & Sons, Ltd.     

MODIS林火识别算法的验证分析

利用中国境内9起森林火灾事件对MODIS火点识别的理论算法进行验证分析．结果表明：MODIS火点识别的理论算法在中国境内是基本通用的．但受地域和季节变化的影响．应用时可能会遗漏个别低温闷烧的热点;利用火点亮温偏离统计均值标准差的关系来确定阁值．可以避免火点的遗漏;林火点在CH21和CH22上的值比较接近。一般有CH21-CH22〈20K。而噪声点在两个波段上的亮温差异比较大。根据以上知识．提出了改进MODIS林火热点识别算法的建议。     

水库中长期径流预报系统的开发研究

水库中长期径流预报系统采用PowerBuilder作为系统主要开发工具，集水情信息查询、检索、监视、预报与管理等功能于一体，实现了中长期水文预报和信息管理的各种功能要求。该系统具有功能全面，技术基础坚实，通用性和开放性强，自动化程度高，界面友好，全菜单操作等特点。     

Spatial distribution of aerosol pollution based on MODIS data over Beijing, China

With the help of regression analysis,the relationships were detected between aerosol's contribution to apparent reflectance(ACR) derived from Moderate Resolution Imaging Spectroradiometer(MODIS)on board Terra and hourly PM_(10)mass concentration measured at 30 ground-based locations in Beijing for the August of 2003 and 2004.It was shown that there was a good correlation between the ACR and PM_(10)(linear correlation coefficient,R=0.56).On the basis of this relationship,spatial distribution and possible sources of PM_(10)derived from MODIS were analyzed and two frequently heavily-polluted regions were found,namely downtown of the city and the district near Xishan Mountain.These two regions coincidently are also urban heat island centers.The foundings of this paper will be greatly useful for environmental monitoring and urban planning for Beijing,especially for the 2008 Olympic game to be held in Beijing.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.