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<br />388 <br /> <br />PJ. BREMAUD AND Y.B. POIr-rrIN <br /> <br />FORECASTING HEAVY RAINFALL FROM RAIN CELL MOTION <br /> <br />389 <br /> <br />Andrieu, H.. Creutin. J.D., Delrieu, G.. leoussof, J. and Pointin, Y. 1989. Radar data <br />processing for hydrology in the Cevennes region. IAHS II1rd Scientific Assembly, 10-19 <br />May 1989, Baltimore, IAHS Publication No. 186, pp. lOS-I 15. <br /> <br />Austin, G.L. and Bellon, A., 1914. The use of digital weather radar records for short.term <br />precipitation forcasting. Q. J. R. Meteorol. Soc., 100: 658-664. <br />Barclay, P.A. and Wilk, K.E. 1970. Severe thunderstorm radar echo motion and related <br />weather events hazardous to aviation operations. ESSA Tech. Memo. 46. National Severe <br />Storms Laboratory, Nonnan, OK., 63 pp. <br />Bellon, A. and Austin. G.L. 1978. The evaluation of two years of rcal-time operation of a <br />short-teon precipitation forecasting procedure (SHARP). J. Appl. 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Computer applications and techniques for storm tracking and warning. <br />17th Conference on Radar Meteorology, 26-29 October 1976, Seattle, American Meteoro- <br />logical Society, Boston, MA, pp. 514-521. <br /> <br />a new forecasling method (Bremaud, 1991) which focuses on heavy rainfall, <br />as it detects and exlrapolales the molion of heavy rainfall cells which are <br />closely associated with conveclive cells, Indeed, both the precipitation fore- <br />casting method and the radar data must be adapled 10 their use, parlicularly <br />in terms of the desired forecast period, because the meteorological structures <br />associated with rain can have very different spatial and temporal characteris- <br />tic scales: from I km and 30min for the convective cells to 1000 km and 48h <br />for the extratropical cyclones, each of these different scale structures having <br />their OWn motion, Therefore, to oblain the best rainfall forecast, Ihe method <br />must detect and extrapolate the motion of the precipitating meteorological <br />structure whose duration is about the forecasting time interval and whose <br />motion can be detected on the successive radar pictures. In the case of a I h <br />forecasting time interval, the most suitable melhod is that which uses small <br />spatial scale radar data and extrapolates the molion of rain cells associated <br />with convective cells. <br />We have compared our method (named 'P ARAPLUIE') with three other <br />methods, one of which (SCOUT 11.0) is at present used for sewer <br />management. The results according to the 'concordance' or hydrological <br />criteria show that our method is reliable and performs well whatever the <br />studied event or the forecasting time interval used, up to 15 min. Thus, the <br />PARAPLUIE method appears to be well suited for forecasling time intervals <br />of aboul15 min to I h, whereas the cross-correlation methods perform belter <br />in the case of forecasting time intervals of 2 h or more by using composite <br />radar data, For 1-2 hours lead time, the most suited method may be that <br />which tracks the slructures enclosing the convective cells, i,e, the method <br />extrapolating T echoes defined at a low reflectivity threshold (aboul 20 dB), <br /> <br />ACKNOWLEDGEMENTS <br /> <br />The authors are indebted to Dr. T, Einfalt for discussions and for making <br />the radar data of the Paris 1989 event available, The Cevennes 1988 and the <br />other radar data have been obtained by the members of the radar group of the <br />LaMP/OPGC and by all campaign participants, The mathematical tools, <br />such as the pattern recognition techniques which are used in the <br />PARAPLUIE method, have been described to us by R, Pejoux and 0, <br />Chambreuil. The edition of this manuscript owes much to Dr, H, Lassen and <br />0, Guillot and 1. Squarise, We express our thanks to all these persons, <br /> <br />REFERENCES <br /> <br />