Visualization Of Design And Implementation About Meteorological Forecast Grid-Point Data On Webgis

Visualization research of weather forecast grid information for China’s meteorological has had some results, but the results of these limited visual characteristics of meteorological elements to show specific geographical information and could not be combined with geographic information on the weather forecasts. In order to improve the efficiency of the weather forecast and apply the rich geographic data to weather forecasting, the paper had studied on the visualization of weather forecasting for grid data, and had designed and implemented WebGIS which can support the visual results of weather forecast, and explored the field of geographic information system applications in meteorology.Using ArcGIS platform, the paper integrated meteorological forecast online inquiry system based on WebGIS, realized visualization of the NetCDF file, as result which WRF output. This paper converted NetCDF data into CDL files using ncdump tool. And it extracted weather forecast element data according to NetCDF data structure. Used python script as the main method, it combined NetCDF data with ArcGIS electronic map and achieved a merger of weather forecasting information and geographic information. It formed display mode and visualization result by reasonably using distance weights reciprocal method to facilitate the weather forecast. Finally, using ArcGIS Server9.2as map engine server, it designed the weather forecasting online query system by WebGIS, which supported point-query functions with comprehensive information and highlight optimization, accurately combined the meteorological forecast information and geographic information.Research results provided for forecasters a suitable visualization information platform, and acquired accurate meteorological data message containing important information.It promoted meteorological information quick analysis and mixed query, helped analysis and prediction of meteorology on geographical factors. It converted scientific computing data and results into graphics, and abstract data into visualized information (color, shape, texture. etc.). It was conducive to using huge and numerical weather prediction data results, and played an important role on the accuracy, sharing, vividness, richness of meteorological forecast.