本溪市区雷暴天气气候特征及其对农业的影响

根据本溪市区46年气象资料的统计分析,总结出了该地区雷暴天气气候规律和特征,并分析了该地区因雷暴天气灾害频发,造成农业诸多方面灾情,影响和破坏了粮食产量质量及农业基础设施;同时,提出利用雷暴天气规律和特征,指导农业生产活动,并提出防御对策。     

丹东春季回流天气最高气温预报方法研究

分析了丹东地区近50年春季(3~6月)最高气温南北偏差5℃以上的回流天气的气候特征,重点分析了2014年春季丹东地区回流天气的特征,根据地面形势将回流天气分成了2种典型类型。中央指导预报产品对丹东地区回流天气预报误差比较大,运用T639数值预报产品对中央指导报进行订正,可以极大地提高预报准确率。     

基于支持向量机的湖北省洪涝农业损失预测模型

洪涝农业灾情预测在灾害管理和应急救灾等领域都具有非常重要的研究价值,以支持向量机(SVM)模型为基础,以1998～2006年湖北省洪涝灾情数据为样本,构建了基于SVM的洪涝农作物损失预测模型.结果表明,基于径向核函数的SVM模型适合湖北地区洪涝农业损失的预测.     

2014年石嘴山市一次久旱转雪天气过程的数值预报产品能力检验

利用欧洲中期天气预报中心（ECMWF）数值预报产品和德国数值预报产品,对宁夏石嘴山市2014年2月4—6日一次久旱转连阴雪天气过程的预报能力进行了对比分析检验。结果表明,此次过程中ECMWF数值预报模式较德国模式的形势场预报准确,随着预报时效的延长,两种模式的预报准确率也均随之降低;从要素预报来看,24、48、72h 700hPa湿度场及850hPa温度场两种模式预报结果均较实况偏差较大,但72h比24、48h预报更接近实况。     

喀斯特石漠化地区耕地压力 动态变化分析与预测

运用MATLAB 软件在计算贵州省2000要2011 年耕地、人口粮食产量动态变化的基础上,分析耕地面 积、人口数量与耕地压力指数的变化特点;并采用DGM（1,1）离散预测模型对贵州省2015要2030 年的耕地压力指数 状况进行预测。结果表明,2000要2011 年间,贵州省耕地总量及人均耕地面积持续减少;人均粮食产量持续增加,人 口净流出加快,使得耕地压力指数波动减少,但耕地压力指数始终保持在1.0 以上粮食供给处于不安全状态 2015要2030 年,耕地压力指数将持续减少,粮食安全形势缓和。增加农业科技投入、农田基本建设和土地整治工作与 加快净流出人口数量,是减轻耕地压力保证粮食安全的根本途径。     

基于小波变换和神经网络的短期风电功率预测方法

随着并网风电场规模的不断增大,为保证电力系统运行的稳定性、合理制定调度计划、提高风电场在发电市场的竞争力,需要对短期风电功率进行准确地预测。该文提出一种小波变换和神经网络理论相结合的综合预测方法,将历史风电功率序列和历史风速序列分别进行小波单尺度分解,得到对应的概貌功率、细节功率和概貌风速、细节风速;然后用概貌功率和概貌风速序列训练BP神经网络,预测未来的概貌功率;用细节功率和细节风速序列训练BP神经网络,预测未来的细节功率。在此基础上,将概貌功率和细节功率叠加,得到最终预测结果。对我国某风电场的实际数据     

许昌小麦吸浆虫发生趋势气象模型与预警

以许昌1999—2008年10年的气象资料和吸浆虫资料为研究基础,通过分析许昌地区10年内吸浆虫的各个生育期:化蛹开始期、化蛹盛期、成虫开始期与气象因子的关系,运用SPSS统计分析软件建立了吸浆虫气象预测预警模型。结果表明:影响许昌小麦吸浆虫关键发育期发生发展的主要因子是温度和水分;吸浆虫越冬基数的大小,与上年冬(12月至次年1月)热量条件、9月平均最低气温和5月上旬降水量有关,低温限制吸浆虫越冬数量,降水多增加越冬基数,9月平均最低气温是预警越冬基数的首选因子;1月极端最低地温和6月中旬至7月上旬平均气温是发生面积前期和后期主要影响因子。     

使用JDBC实现自动气象站要素信息检索

介绍了使用JDBC实现自动气象站分中心站的气象要素信息检索，程序运用B／S体系结构，遵循MVC设计思想，采用Model2模式进行开发，为了提高程序的运行速度，在数据库中创建了存储过程。     

泉州平原作物生长季和夏旱期降水量叠加预测模式及其应用

采用时间序列分析方法，对最能代表整个泉州平原降水情况的晋江气象站１９６０～１９９６ 年共３７ ａ 中３～１１ 月（作物生长季）和７～９ 月（夏旱期）２ 段时间的降水量资料进行统计，同时分析了该地区的降水量变化规律，获得了该地区上述２ 段时间的降水量模式，进而提出了防御干旱的措施，     

Application of the Cropping System Model (CSM)‐CROPGRO‐Soybean for Determining Optimum Management Strategies for Soybean in Tropical Environments

The determination of optimum crop management practices for increasing soybean production can provide valuable information for strategic planning in the tropics. However, this process is time consuming and expensive. The use of a dynamic crop simulation model can be an alternative option to help estimate yield levels under various growing conditions. The objectives of this study were to evaluate the performance of the Cropping System Model (CSM)‐CROPGRO‐Soybean and to determine optimum management practices for soybean for growing conditions in the Phu Pha Man district, Thailand. Data from two soybean experiments that were conducted in 1991 at Chiang Mai University and in 2003 at Khon Kaen University were used to determine the cultivar coefficients for the cultivars CM 60 and SJ 5. The CSM‐CROPGRO‐Soybean model was evaluated with data from two experiments that were conducted at Chiang Mai University. The observed data sets from farmers’ fields located in the Phu Pha Man district were also used for model evaluation. Simulations for different management scenarios were conducted with soil property information for seven different soil series and historical weather data for the period 1972–2003 to predict the optimum crop management practices for soybean production in the Phu Pha Man district. The results of this study indicated that the cultivar coefficients of the two soybean cultivars resulted in simulated growth and development parameters that were in good agreement with almost all observed parameters. Model evaluation showed a good agreement between simulated and observed data for phenology and growth of soybean, and demonstrated the potential of the CSM‐CROPGRO‐Soybean model to simulate growth and yield for local environments, including farmers’ fields, in Thailand. The CSM‐CROPGRO‐Soybean simulations indicated that the optimum planting dates from June 15 to July 15 produced maximum soybean yield in a rainfed environment. However, the planting date December 15 produced the highest yield under quality irrigation. Soybean yield was slightly improved by applying nitrogen at a rate of 30 kg N ha^?1 at planting. Soybean yield also improved when the plant density was increased from 20 to 40 plants m^?2. The results from this study suggest that the CSM‐CROPGRO‐Soybean model can be a valuable tool in assisting with determining optimum management practices for soybean cropping systems in the Phu Pha Man district and might be applicable to other agricultural production areas in Thailand and southeast Asia.