台风灾害风险区划中社会经济易损性因子的计算

通过对台风灾害风险区划中承灾体的分析,选取人口密度、非农业经济产值、耕地果园面积和固定资产投资额四个因子作为易损性评价因子,探讨了对各因子在1km×1km单元格内进行精细化计算的方法,得到各因子在社会经济易损性指数中的权重,依据社会经济易损性指数绘制了海南省社会经济易损性分布图。     

基于GIS的海南台风灾害评估业务系统研发与应用

针对传统方法在灾害评估中的不足,基于GIS平台建立实时的灾害评估系统。本文详细介绍系统的结构、功能、业务工作流程,并采用完全集成的方法将评估模型在ARCGIS平台上实现集成。选取了2009年热带风暴"天鹅"进行实例分析,结果表明系统具有很好的实用性。     

国外发达国家气象灾害防御机制现状

联合国的有关报告指出,过去10年全球发生的气象灾害,导致30多万人丧生,造成经济损失超过8000亿美元。20世纪的观测事实表明,全世界70％的自然灾害和气象相关。专家研究发现：欠发达地区比发达地区更容易产生自然灾害。同等级的自然灾害,     

海南儋州雷暴天气气候特征分析

利用1971-2000年儋州30年逐日雷暴观测资料,对海南儋州地区雷暴时间分布特点和变化规律进行分析研究,总结了儋州雷电活动的气候特征.结果表明:儋州年平均雷暴日数达111天,高发季节为每年5-8月,高发时段为午后13-17时,年雷暴日数年代际线性变化呈下降趋势,但二阶滑动平均变化趋势为先减后增.对1991-2000年雷暴产生的天气影响系统统计表明:儋州雷暴主要产生于冷空气、变暖的高压脊、热带气旋、副热带高压、热带低值系统5类天气系统中,有明显的季节特征.     

Variation characteristics of tropical cyclones making landfall in China at different intensities

According to the national standard(2006)on tropical cyclone(TC)intensity,TCs are categorized into six intensity types,namely,tropical depression(TD),tropical storm(TS),severe tropical storm(STS), typhoon(TY),severe typhoon(STY),and super severe typhoon(SSTY).Fifty-eight years(1949–2006)of the datasets from the Yearbook of Typhoons and Yearbook of Tropical Cyclones were used to study the variation characteristics of TCs making landfalls in mainland China,Hainan and Taiwan islands.The main results are as foll...     

琼州海峡大风数值模拟及地形敏感性试验

使用WRF3.1模式对2008年12月4日、12月21日、2009年3月13日的三次冷空气造成的琼州海峡大风过程进行数值模拟和地形敏感性试验.模拟结果表明:水平格距4 km的模拟地面风场与实况接近,中尺度模式在大风的起风时间、持续时间、风速大小等方面有较强的预报能力,并能反映冷空气偏东路径与偏西路径过程中琼州海峡大风的...     

“98.7”海南暴雨天气成因初探

分析海南暴雨产生的水汽条件、能量条件、抬升条件、环流形势的演变及主要影响系统,发现副高西南缘的东南气流和西南季风带来的西南气流的双辐合是暴雨产生的有利机制,由于迎风坡效应,海南岛在西南季风期间的降水,南部明显大于北部,低空急流是暴雨形成的有利条件。     

OBSERVATION AND ANALYSIS OF SEA SURFACE WIND OVER THE QIONGZHOU STRAIT

The spatial variation and diurnal fluctuation of sea surface wind over the Qiongzhou Strait were described using verified datasets from automatic weather stations on board a ferry, buoys, and on the coast. Results are as follows: (1) On average, sea surface wind speed is 3–4 m/s larger over the Qiongzhou Strait than in the coastal area. Sea surface wind speeds of 8.0 m/s or above (on Beaufort scale five) in the coastal area are associated with speeds 5–6 m/s greater over the surface of the Qiongzhou Strait. (2) Gust coefficients for the Qiongzhou Strait decrease along with increasing wind speeds. When coastal wind speed is less than scale five, the average gust coefficient over the sea surface is between 1.4 and 1.5; when wind speed is equal to scale five or above, the average gust coefficient is about 1.35. (3) In autumn and winter, the diurnal differences of average wind speed and wind consistency over the strait are less than those in the coastal area; when wind speed is 10.8 m/s (scale six) or above, the diurnal difference of average wind speed decreases while wind consistency increases for both the strait and the coast.     

琼州海峡沿岸雾统计特征及天气学预报指标

利用海口站1961～2006年高空地面观测资料,分析了琼州海峡沿岸雾的气候统计特征。结果表明：琼州海峡沿岸雾目的年际变化呈现了显著的减少趋势。20世纪70年代初期和90年代初期为雾日减少的两个气候突变期。雾日减少与气候变暖密切相关,夜间最低温度升高是引起海峡雾日减少的主要原因。琼州海峡沿岸雾多出现在冬春季节,一天中出现雾的峰值时间为06：00～07：00,消散峰值时间为08：OO～09：00。利用1987～2006年NCEP再分析资料,总结了产生琼州海峡沿岸雾的3种天气形势,根据雾的类型提出了相应的预报指标。     

EVALUATION OF TEMPERATURE RECORDS OBTAINED BY AWS IN HAINAN PROVINCE AND ADJUSTMENT OF CLIMATOLOGICAL TIME SERIES

Based on the parallel air temperature data of automatic sounding and manual observations at 16 weather stations in Hainan province from 2004 to 2005, a comparative analysis and evaluation is made for validity according to relevant standards. The results indicate that there are daily and seasonal differences between temperature observations recorded by automatic weather stations (AWSs) and with conventional methods. The reasons for the differences are the systematic error, the sensitivity of the two types of instruments to the environmental temperature change, the difference of the observation time and the effect of solar radiation. Because the long-range data were obtained from manual observation, an empirical conversion formula between the temperature records obtained by the instruments is provided for continuous use of the climate data after the changes in instruments.