Abstract
Abstract. Geographical Information Systems (GIS) can be used to integrate data from different sources and in different formats to perform innovative spatial and temporal analysis. GIS can be also applied for climatic research to manage, investigate and display all kinds of weather data. The main objective of this study is to demonstrate that GIS is a useful tool to examine and visualise precipitation distribution obtained from different data sources: ground measurements, satellite and radar data. Three selected days (30 cases) with convective rainfall situations were analysed. Firstly, scalable GRID-based approach was applied to store data from three different sources in comparable layout. Then, geoprocessing algorithm was created within ArcGIS 9.2 environment. The algorithm included: GRID definition, reclassification and raster algebra. All of the calculations and procedures were performed automatically. Finally, contingency tables and pie charts were created to show relationship between ground measurements and both satellite and radar derived data. The results were visualised on maps.
Highlights
Radar and satellite remote sensing provide almost continuous spatial information on precipitation as opposed to in situ ground measurements and are very valuable source of data for different hydrological and meteorological applications
Practical use of precipitation data obtained from satellite and weather radar imagery requires validation with use of classic rainfall measurements, which are the only criterion for quality assessment of the remotely sensed data
The summa0ry of the co8n7ti%ngency analysis is 8st2or%ed in the table 1 a7n9d%example visualisation of one case study relationship analisys between Automatic Telemetric Ground Measurement Stations (ATS) and RD precipitation patterns is presented in figure 4
Summary
Radar and satellite remote sensing provide almost continuous spatial information on precipitation as opposed to in situ ground measurements (rain gauges network) and are very valuable source of data for different hydrological and meteorological applications. Practical use of precipitation data obtained from satellite and weather radar imagery requires validation with use of classic rainfall measurements, which are the only criterion for quality assessment of the remotely sensed data. Combining these data within one environment to perform comparative analysis is often a problem due to a different data structures and formats as well as temporal and spatial resolution variety. This study employs GIS techniques as a solution for multiple source precipitation data integration and analysis This is the first attempt to perform comparative analysis of rainfall distribution in Poland within GIS environment.
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