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The flash flood event of June 2000 in Catalonia: monitoring and nowcasting using the meteorological radar and an automatic raingauge network MARÍA DEL.

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Presentation on theme: "The flash flood event of June 2000 in Catalonia: monitoring and nowcasting using the meteorological radar and an automatic raingauge network MARÍA DEL."— Presentation transcript:

1 The flash flood event of June 2000 in Catalonia: monitoring and nowcasting using the meteorological radar and an automatic raingauge network MARÍA DEL CARMEN LLASAT TOMEU RIGO Meteorological Hazards Analysis Team Department of Astronomy & Meteorology University of Barcelona, Spain INTERREG IIIC: HYDROPTIMET MEETING. GRENOBLE 2-3 FEBRUARY 2004

2 During the early morning of 10 June 2000 there occurred a heavy rainfall event over Catalonia (NE of Spain) that caused material damages estimated at over 65,000,000 euros and there were 5 fatalities. A short diagnosis of the event

3 Location of the event The affected region is placed at NE of the Spain. It is named Internal Basins of Catalonia and it consists of 4 larger basins (Ter, Besos, Llobregat and Francoli) and other smaller ones.

4 Data Raingauge data in surface Radar imagery Radiosoundings of Barcelona and Palma Mallorca Synoptic analysis Mesoscale analysis Acknowledgements for the data: Agencia Catalana de lAigua, Instituto Nacional de Meteorología, Servei de Meteorologia de Catalunya Our special acknowledgement to E. Velasco (ACA) and P. Martín (INM) for their collaboration

5 The raingauge network * Rain gauge White area: IBC The SAIH system of the IBC covers an area of km 2. The rainfall network is composed by 126 tipping-bucket automatic rain gauges. The precipitation is cumulated and recorded every 5 minutes. Rainfall overturning of 0.1 mm.

6 The meteorological radar Placed over the Puig de les Agulles (20 km at SW of Barcelona) at 612 m asl. It belongs to the INM radar network and operates in the C-band.

































39 Total Cumulated Rainfall The 94% of the rainfall gauges of the IBC registered a cumulated rainfall above 15 mm in 24 hours. A lot of 24 hours maximum rainfall values exceeding the 100 mm were recorded in many gauges of the Llobregat Basin and other minor basins. Some examples of maximum values registered are: 223 mm in 24 hours 158 mm in 3 hours 13.2 mm in 5 minutes 21:00 UTC 9 June- 21:00 UTC 10 June

40 The maximum 5-minutal rainfall value (13.2 mm) is equivalent to mm in only one hour. Rainfall Rate and Time Evolution The rainfall event started at the Southern Basins at 21:30 UTC as a consequence of the pass of a quasi- stationary rainfall band, that remained over the same place for about 2 hours.

41 Flow evolution

42 Synoptic Evolution On 10 June at 0000 UTC: Previously: anticyclonic situation, warm and very wet advection in low levels, great potential instability the cold front was situated around the west of Catalonia. in the previous few hours to the event, a surface depression (1008 hPa) had been forming, centred on the Balearic Islands. the flow from the west that dominated most of the Peninsula at 850 hPa had been veering, so that by that time it was coming mainly from the north and had advected very cold air that extended right to the upper troposphere

43 Barcelona Palma MadridMurcia The day of the floods: 10 June (00 UTC)


45 Mesoscale analysis L It showed a conjunction of the following factors: Mesoscalar depression at surface. It led to the convergence of water vapour at low levels and played a direct role in triggering the potential instability cumulated previously 2. the existence of a line of convergence, which advance over Catalonia along a SW-NE axis, with the slow movement of the depression. The squall lines were formed near of it.







52 The radar tool Interaction between the 2 procedures (2D&3D), adapting, improving and combining different algorithms 2D: rainfall structures (separating convective & stratiform precipitation) 3D: convective cells Use of the wind profile over the meteorological radar for tracking and nowcasting 2D&3D structures Warnings production

53 To classify convective structures in 2D


55 To identify convective structures in 3D

56 2D 3D Mesoscale Convective System Multi-Cell Storm To integrate cells and convective structures

57 The method (Johnson et al., 1998) uses the centroid position and other features (size, shape and intensity) of 3D cells of the 6 previous images. For each actual cell identifiyed, the algorithm has tried to detect past cells which distance was less than 10 km. The other features help to describe the state and the life-cycle of the cell. However, for cases where two cells could be associated to the same previous 3D structure, those features, combined with distance, can help to determine which is the selected. Tracking and nowcasting of cells now past future Forecasted position Real position Application to rainfall nowcasting

58 Tracking and nowcasting of cells Cells can move throughout the convective system or in the same direction that the 2D structure. First case is the most dangerous: slow or null cells movement can gives strong rainfall values over the same zone

59 Previous positions have not been used. Reason: in general, positions of 2D structures changes extraordinarily in 10 minutes. The displacement vector has been obtained by combining two different vectors: mean wind vector at mid-levels (HIRLAM data) mean movement vector of convective cells associated to that structure Tracking and nowcasting of convective structures 2D+3D Application to rainfall nowcasting

60 Example of tracking and nowcasting 2D3D

61 Example of tracking and nowcasting Now Tracking Nowcasting Now Application to rainfall nowcasting

62 Past: t -60 -t 0 Future: t 0 -t +60 Tracking & Warning Application to rainfall nowcasting

63 Radar image at 22:40 UTC Z = 800 R 1.6

64 The next steps To apply this methodology to other events To improve the analysis using lightning data To apply objective mesoscale models (see contribution UIB) To obtain the nowcasted rainfall chart by applying the suitable algorithms (convective and stratiform relationships) in order to improve the flood warning system To integrate with hydrological models

65 Thanks for your attention

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