东北地区平均、最高、最低气温时空变化特征及对比分析

东北地区是我国受全球气候变暖影响增温最显著的地区之一,有其独特的气候变化特点。利用东北地区建国以来较密集的气象观测资料,运用Yamamoto检测、趋势系数、气候倾向率等方法分析了该区域近44 a来平均、最高、最低气温的时空变化特征和规律,并初步探讨了这些变化的差异和可能影响因素。结果表明:近44 a来,东北地区平均气温存在明显的变暖倾向,气候变暖趋势存在着季节性和地域性差异。冬季增温最强,秋季增温最弱;区域变化表现为在区域中心区域,即吉林、黑龙江、内蒙古三省交界区增温趋势最明显,辽宁中部和内蒙古东部的中心靠近边境区域为增温较弱的地区;最低气温的增温率是最高气温的2倍左右。     

基于GIS的秦岭山地气温空间分布

提出一种以气象站点观测资料为基础,用G IS技术建立山地平均气温分布模型的方法。通过数字高程模型(DEM),获取地形数据,建立山地天文辐射模型。考虑海拔高度、地形等影响气温空间分布因子,建立山地气温分布模型。     

一次孟加拉湾风暴和冷空气影响下滇西大暴雨中尺度分析

应用MICAPS资料, 通过天气诊断分析, 结合FY-2卫星云图及德宏CINRAD-CC雷达体扫资料, 分析了发生在2004年5月18日滇西地区的大暴雨过程。发现本次大暴雨过程天气尺度影响系统为初夏孟加拉湾风暴及南下冷锋切变; 大暴雨发生在高能高湿的水汽辐合中心、700 hPa螺旋度正值区及湿 Q 矢量散度大值辐合区内; 卫星云图上, 多个β-中尺度对流系统在大暴雨区发展; 多普勒雷达回波为絮状混合型降水回波, 强度在30~44 dBz之间, 频繁出现的逆风区、低空急流、中尺度辐合线等中小尺度系统是造成本次大暴雨的直接影响系统。     

晴空与有云大气辐射分布的数值模拟及其对全天空图像云识别的应用

全天空图像自动云识别的研究相对来说是一项较新的研究领域。当前国际上较为通用的全天空图像云识别方法主要依靠图像蓝红灰度值对比的阈值方法进行判断。然而非洁净大气中气溶胶的增多给云识别增加了难度,同时太阳高度角不同天空色度分布情况也不同。文中利用Libradtran辐射传输模式,计算了不同能见度不同太阳高度角情况下3个典型波长(450,550,650nm;蓝/绿/红)无云及有云大气的天空辐亮度分布情况,并进行了比较分析。结果表明,相同太阳高度角情况下,无云及有云大气中蓝红比值随能见度的下降呈单调下降趋势。在特定的云光学厚度和能见度情况下,天空色度彼此呈现出类似的分布状况。全天空图像阈值判断云识别自适应算法的建立需要与太阳高度角、地面能见度联系起来。当前尚无法建立一个判断阈值随太阳高度角以及能见度变化的函数关系式。较为可行的办法是建立典型能见度、典型太阳高度角情况下的辐射信息库,在具体云识别时,首先确定太阳高度角,而后根据天空辐射比情况确定天空能见度,并利用辐射信息标准库做云或非云判别。该工作为全天空云识别算法提供判别依据,同时建立云识别随能见度和太阳高度角变化的判别信息库。     

电视气象节目的市场化运营

在当今以受众者为核心的传播时代,电视气象节目的发展应与电视传媒的整体变革同步进行;逐步完善节目的内容和形式,逐步达到受众的欣赏要求,逐步实现节目的市场化运营.     

Evaluating Local Non-Stationarity when Considering the Spatial Variation of Large-scale Autocorrelation

Multi‐scale effects of spatial autocorrelation may be present in datasets. Given the importance of detecting local non‐stationarity in many theoretical as well as applied studies, it is necessary to “remove” the impact of large‐scale autocorrelation before common techniques for local pattern analysis are applied. It is proposed in this paper to employ the regionalized range to define spatially varying sub‐regions within which the impact of large‐scale autocorrelation is minimized and the local patterns can be investigated. A case study is conducted on crime data to detect crime hot spots and cold spots in San Antonio, Texas. The results confirm the necessity of treating the non‐stationarity of large‐scale spatial autocorrelation prior to any action aiming at detecting local autocorrelation.     

土-结构动力相互作用研究综述

土与结构动力相互作用是当代力学领域的前沿性研究课题,具有很强的实践性。对土与结构动力相互作用的研究历史与现状进行了介绍,简要综述了当前土与结构动力相互作用的研究方法,重点介绍了目前关于土与结构动力相互作用问题中从无限域转化成有限域的人工边界研究进展问题,并对该领域今后的研究工作提出了建议。     

"地震数值模拟的数据库应用平台"项目成果介绍

利用计算机模拟复杂的系统和过程,是当今世界科技发展的新潮流,在地学领域,数值模拟已经渗透到地学研究的各个重大领域。本项目提出建立一个用于地震模拟和预报的数据库应用平台,以地壳动力学研究和强震机理研究为应用核心,将地震地质研究、地形变研究、地应力研究、地球内部结构研究等多种相关的学科手段的观测资料、实验结果和理论分析有机地结合起来,实现技术和数据资源的共享。利用这些信息构建比较合理的地球模型和尽可能多的约束条件,并在有限元分析系统上进行地壳形变和地震过程的数值模拟。     

Integration of transfer function model and back propagation neural network for forecasting storm sewer flow in Taipei metropolis

Typhoons and storms have often brought heavy rainfalls and induced floods that have frequently caused severe damage and loss of life in Taiwan. Our ability to predict sewer discharge and forecast floods in advance during storm seasons plays an important role in flood warning and flood hazard mitigation. In this paper, we develop an integrated model (TFMBPN) for forecasting sewer discharge that combines two traditional models: a transfer function model and a back propagation neural network. We evaluated the integrated model and the two traditional models by applying them to a sewer system of Taipei metropolis during three past typhoon events (NARI, SINLAKU, and NAKR). The performances of the models were evaluated by using predictions of a total of 6 h of sewer flow stages, and six different evaluation indices of the predictions. Finally, an overall performance index was determined to assess the overall performance of each model. Based on these evaluation indices, our analysis shows that TFMBNP yields accurate results that surpass the two traditional models. Thus, TFMBNP appears to be a promising tool for flood forecasting for the Taipei metropolis sewer system. For publication in Stochastic Environmental Research and Risk Analysis.     

Variations of near-surface atmospheric CO2 and H2O concentrations during summer on Muztagata

Expeditions during the summers of 2002 and 2003 implemented continuous monitoring of near-surface (2 m height) atmospheric CO₂ and H₂O concentrations at the 4500 m elevation on Muztagata. The resultant data sets reveal a slight decrease of CO₂ concentrations (of about 5 μmol·mol^-1) and changes in the diurnal variations from the end of June to the middle August. The daily maximum CO₂ concentrations occur between 02:30-05:30 AM (local time) and the minimum levels occur between 12:00-15:30 PM. The atmospheric CO₂ concentrations in the summer of 2002 were around 5 μmol·mol^-1 lower than those during the same period of 2003, whereas the diurnal amplitude was higher. In contrast, we found that the daily mean atmospheric H₂O content in 2003 was much lower than that in 2002 and there exists a striking negative correlation between CO₂ and H₂O concentrations. We therefore suggest that the near-surface atmospheric CO₂ concentration is affected not only by photosynthesis and respiration, but also by the air H₂O content in the glaciated region around Muztagata.