GIS Ostrava 2011 23. – 26. 1. 2011, Ostrava ANALYZING RADAR-MEASURED RAINFALL VS. RAIN GAUGES IN GIS Arnošt, MÜLLER Department of Mapping and Cartography, Faculty of Civil Engineering, Czech Technical University, Thákurova 7, 166 29 Praha 6 – Dejvice, [email protected]ABSTRACT Rainfall data are traditionally collected at discrete point locations in space, at meteorological stations (rain gauges). Values at any other point must be interpolated or can be remotely sensed by ground-based radar, which can detect the areal distribution of precipitation at more detailed spatial scale. Nevertheless, radar measurements are affected by various types of errors and the transformation of measured radar reflectivity into rain rates is far from accurate. This study provides a deeper analysis of the influence of topography on radar measured precipitation. By the means of linear regression analysis residuals between 134 rain gauges and corresponding radar estimated rainfalls were calculated, and then studied using residual regression analysis with the following independent variables: altitude, longitude, latitude, aspect, slope, curvature, distance from the radar antenna, aspect perpendicular to the radar beam referred to as directional difference, mean air temperature, and solar radiation. The independent variables were derived from the 90 m SRTM DEM in ArcGIS. A multivariate second order polynomial regression model was developed with three topographic and locational variables as the best predictors: altitude, distance, and latitude, which can explain up to 74% of variance of the residual errors. This means that radar measurement errors are not only a cause of random variation, but can be partially predicted, which may allow for some type of correction and improvement in radar’s accuracy. Keywords: rainfall, rain gauge, radar, GIS, regression, terrain analysis INTRODUCTION Precipitation, as one of the basic climatological factors, is used as an input in various models in hydrologic modeling, e.g. flood prediction, in agriculture applications for estimating yields, in land management, or in atmospheric simulation models. Rainfall data are traditionally collected at meteorological stations (rain gauges), which are discrete point locations in space. Values at any other point must be derived from neighboring meteorological stations or can be remotely sensed, e.g. by ground-based radar. The main advantage of rain gauges is a fine temporal resolution. In fact, gauges record continuously and are able to detect even short (minute) rainfalls [1]. Rain gauge observations are still considered as close to true rainfall as we can get at present state of art technologies [4]. While rain gauges measure at discrete locations, weather radar samples at discrete time instances (e.g. every 10 minutes). Radar’s main advantage is that it can ‘see’ much larger atmospheric space than rain gauges located on the ground. Radar can detect the areal distribution of precipitation at more detailed spatial scale than rain gauge network and therefore, the final rain field pattern should be determined by radar, as recommended by Krajewski [4]. However, precipitation obtained only from radar data cannot be directly used because radar measurements are affected by various types of errors and the transformation of measured radar reflectivity into rain rates is far from accurate [4, 8]. The objective of this study is to test the influence of following topographic, locational and atmospheric variables on residual errors: altitude, longitude, latitude, aspect, slope, curvature, distance from the radar antenna (DIST), aspect perpendicular to the radar beam referred to as directional difference (DIF), mean air temperature and solar radiation. Residual errors are calculated as the difference between radar-estimated rainfall and rain gauges observations, which are considered as a good approximation of the true ground rainfall. If some factors influencing residual errors are found significant, this would mean radar errors are not random and therefore can be removed by some type of correction.
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GIS Ostrava 2011 23. – 26. 1. 2011, Ostrava
ANALYZING RADAR-MEASURED RAINFALL VS. RAIN GAUGES IN GIS
Arnošt, MÜLLER
Department of Mapping and Cartography, Faculty of Civil Engineering, Czech Technical University,
[3] Gorokhovich, Y., Villarini, G. (2005) Application of GIS for processing and establishing thecorrelation between weather radar reflectivity and precipitation data. Meteorological Applications, 12,1, 91-99.
[4] Krajewski, W.F. (1995) Rainfall Estimation Using Weather Radar and Ground Stations, InternationalSymposium on Weather Radars, São Paulo, Brazil.
[5] Müller, A. (2010) Spatial Modeling of Climate, Faculty of Civil Engineering, Department of Mappingand Cartography, The Czech Technical University in Prague.
[6] Řezáčová, D., Sokol, Z., Kráčmar, J. , Novák, P. (2001) Statistical adjustment of radar-based daily precipitation to ground data from the Czech territory, Proceedings of 30th International Conf. onRadar Meteorology, 19-24 July 2001. Amer. Meteorol. Soc., Munich, 570-572.
[7] Sokol, Z. (2003) The use of radar and gauge measurements to estimate areal precipitation forseveral Czech river basins. Studia Geophysica Et Geodaetica, 47, 3, 587-604.
[8] Sokol, Z., Bližňák, V. (2009) Areal distribution and precipitation-altitude relationship of heavy short-term precipitation in the Czech Republic in the warm part of the year, Atmos. Res., 94, 652-662.