基于GIS的数值预报降水产品精细化方法研究  被引量:9

Research on Fineness Method of Numerical Forecast Precipitation Products Based on GIS

在线阅读下载全文

作  者:王锡稳[1] 刘治国[1] 秘晓东[2] 张旭东[1] 张铁军[1] 

机构地区:[1]兰州中心气象台甘肃省干旱气候变化与减灾重点实验室,甘肃兰州730020 [2]甘肃省气象局,甘肃兰州730020

出  处:《高原气象》2006年第6期1190-1195,共6页Plateau Meteorology

基  金:甘肃省自然科学基金暨中青年科技基金项目"甘肃省山洪地质灾害气象预报预警系统研究"(3ZSO41-A25-012)资助

摘  要:以中尺度数值预报模式MM5为基础,将其降水预报结果提供给地理信息系统ArcInfo平台,各气象站点降水预报结果被转换成数据点图层,然后通过样条插值法生成网格图层,再与具有甘肃省、市、县级边界以及各县乡镇点位置的基础数据图层叠加,用不同颜色表示预报降水量级的大小,最后分区、县及落点三级标准分别生成甘肃降水预报精细化产品。通过实例检验,表明该产品无论在降水分布、量级,还是降水趋势的预报上均与实况基本吻合,对过程降水、局地强对流天气及定点、定量、定时降水预报均有一定的参考价值。这样,将降水预报产品与地理信息系统GIS相结合,不但实现了甘肃降水预报产品的数字化和可视化,而且精度高、效果好。Based on the mesoscale numerical model (MM5), the precipitation forecast products were imported to ArcInfo's flat-top of geographic information system (G/S) on which precipitation forecast of meteorological station exported by MM5 modle was transformed to layers of data-point. Then grid layers produced by spline interpolation overlapped the basis-data layer with the boundaries of the province, city and county levels in Gansu, and with the different colors show different rainfall. As a result, precipitation forecast's precise products of Gansu was exported respectively according to region, county and falling area. It is proved that these fineness products are not only close to facts on spatial distribution, precipitation, and tendency of precipitation, but also useful for forecast of storm precipitation, local severe convective weather and precipitation at stations. It makes numerical, material and video precipitation products of Gansu true through binding forecast production in GIS. The method is of high resolution and great effects, makes precipitation forecast of Gansu accurate to town-level. So it is valuable and credible to plough into daily operation.

关 键 词:地理信息系统 中尺度数值模式MM5 降水预报产品精细化 

分 类 号:P456[天文地球—大气科学及气象学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象