与时俱进 成就斐然——丁裕国教授     

《沙漠与绿洲气象(新疆气象)》2009,3(2):62-62

丁裕国教授,江办人,1941年出生于江苏省镇江市。1964年南京大学毕业后分配到南京气象学院（后更名为南京信息工程大学）任教,长期从事气候学研究与教学。曾任气象系气候教研室主任多年;先后讲授《气候统计学》、《气候变化》、《气象时间序列谱分析》、《气候诊断与预测》等课程,指导和培养硕士生30多人。曾任中国气象学会统计气象专业委员会暨江苏省气象学会统计气象专业委员会及出版委员会委员等职。  相似文献   

“新疆棉田干旱监测预警及优化配水服务系统”项目通过验收     

桑长青  傅玮东 《沙漠与绿洲气象(新疆气象)》2009,3(6):60-60

2009年12月19日,由新疆气象局副局长魏文寿任组长的专家组对新疆气候中心承担的中国气象局业务新技术推广项目“新疆棉田干旱监测预警及优化配水服务系统”进行了验收。  相似文献   

浅析毕节地区“暴雨预警信号”发布策略与技巧     

胡永松  李德章  张寿荣  陈焰犊  李应桃  刘丽萍 《贵州气象》2009,33(6):44-46

从防灾减灾、服务社会的基本思路着手,就毕节地区暴雨预警信号发布过程中的一些问题作了初步的分析,并提出自己的发布策略与技巧,希望对今后暴雨预警信号发布工作有一定的参考作用。  相似文献   

充满活力的邹城市气象局     

本刊编辑部 《山东气象》2009,29(2):F0003-F0003

近年来,在济宁市气象局和市委、市政府的正确领导下,邹城市气象局不断提升天气预警预报和短期气候预测预估水平,不断加强气象现代化基础设施建设,大力提高公共气象服务质量,为建设“经济强市、文化名市、生态靓市、和谐新市”作出了巨大贡献。  相似文献   

陕西气象科技服务在公共气象服务中科学发展的战略思考          下载免费PDF全文

米天明 《陕西气象》2009,(2):1-4

对流有效位能（CAPE）是强对流天气分析预报的重要参数。通过理论推导,提出了载水气块和非载水气块两种情况下对流有效位能的两个新的计算公式,便于业务应用;并讨论了对流有效位能的局地变化因子和预报思路。  相似文献   

汉江流域气象预警中心网站设计与实现          下载免费PDF全文

周义兵  田光普  宁志谦  郭江峰  王大君 《陕西气象》2009,(5):32-34

随着信息和互联网技术的发展普及,依托该技术的WEB应用飞速发展,WEB服务成为新时期最主要的信息发布媒体。为进一步提高汉江流域气象预警中心服务能力,改进服务方式,提高服务效率,中心网站建设十分必要和重要。紧紧围绕中心业务实际和流域广大业务人员需要,设计开发了“汉江流域气象预警中心网站”。  相似文献   

地面报表预审中值得注意的几个问题     

雷春丽 《陕西气象》2009,(6):18-18

在地面报表预审时,A、J文件中的台站参数、质量控制、降水终止时间的一致性、下月1日20—08时降水量、跨月连续（无）降水开始日期和上跨连续降水量等项目值得注意。  相似文献   

影响卢氏县的气象灾害防御措施   总被引：2，自引：1，他引：1  

莫爱勰  马丽征  蔡涛  胡韶华  吕国华  王梅娟 《气象与环境科学》2009,32(Z1)

影响卢氏山区的气象灾害有暴雨、暴雪、寒潮、大风、高温、干旱、雷电、冰雹、大雾、道路积冰等.其中暴雨、冰雹出现频率较高,且危害最大.为防御气象灾害,气象部门应提高灾害性天气预报准确率;政府及有关单位要及时把灾害性天气预报信息通过各种渠道,及时传播至千家万户;加强防灾减灾宣传,提高民众自救能力;建立和完善灾害性天气预警应急预案.  相似文献   

Mesoscale Analysis of a Heavy Rainfall Event Along the Huaihe River Valley During 8-9 July 2007          下载免费PDF全文

ZHANG Xiaoling  JIAO Meiyan  CHEN Tao 《Acta Meteorologica Sinica》2010,24(3):365-379

During 8-9 July 2007,several successively developed rainstorms along the Meiyu front produced heavy rainfall in the Huaihe River Valley,which led to the most catastrophic flooding in this region since 1954.Through mesoscale analysis of both conventional and intensive observations from upper air and surface stations,automatic weather stations,Doppler radars,and the FY-2C satellite,the current study examines the developing style and environmental conditions of the mesoscale convective systems(MCSs)that led to the development of the rainstorms.Our analysis showed that this event went through three phases.The first phase of the heavy rainfall(Phase Ⅰ)was caused by a meso-α-scale wind shear in the lower troposphere during 0200-1700 BT(Beijing Time)8 July.Phase Ⅱ was characterized by a reduction in rain rate and the formation of a low-level vortex between 1700 BT 8 and 0200 BT 9 July.In Phase Ⅲ,the well-organized mature meso-α-scale low-level vortex brought about intensified rains during 0200-0800 BT 9 July.Satellite and raclar observations showed a backward development of MCSs(new convective cells were generated at the back of the system)in PhaseⅡ,a forward development in Phase Ⅲ,and a spiral organization of the convective lines in Phase Ⅱ.The heavy rainstorm systems were initiated continuously along a surface mesoscale dew-point front with a horizontal scale of～300 km(as part of the Meiyu front)in the upper reaches of the Huaihe River Valley near Fuyang City,Anhui Province and then gradually decayed in the middle and lower reaches.It is hypothesized that lifting by strong low-level convergence is sufficient to trigger convection in the high CAPE(convective available potential energy)environment.  相似文献   

The Prediction of Non-stationary Climate Series Based on Empirical Mode Decomposition   总被引：1，自引：0，他引：1  

YANG Peicai  WANG Geli  BIAN Jianchun  ZHOU Xiuji 《大气科学进展》2010,27(4):845-854

This paper proposes a new approach which we refer to as ``segregated prediction" to predict climate time series which are nonstationary. This approach is based on the empirical mode decomposition method (EMD), which can decompose a time signal into a finite and usually small number of basic oscillatory components. To test the capabilities of this approach, some prediction experiments are carried out for several climate time series. The experimental results show that this approach can decompose the nonstationarity of the climate time series and segregate nonlinear interactions between the different mode components, which thereby is able to improve prediction accuracy of these original climate time series.  相似文献