1. Towards improved QPE with a local area X-band radar in the framework of COPS F. Tridon, J. Van Baelen and Y. Pointin Laboratoire de Météorologie Physique, UMR CNRS/UBP 6016 24, avenue des Landais, 63177 Aubière Cedex, France (F.Tridon@opgc.univ-bpclermont.fr)

2. Introduction (1) Radar technology: tool for quantitative rainfall measurements Main parameters:  Reflectivity factor : Z (mm 6.m -3 )  Rainrate: R (mm.h -1 )  Drop Size Distribution: DSD (l -1.mm -1 ) Power law relationship: Z = aR b Variability of DSD Use of unique Z-R relationship for one precipitating event

3. Introduction (2) Objective: Quantitative precipitation estimation on a small catchment basin with a simple scanning X-band radar Use of a nearby vertically looking MicroRain Radar to:  study the properties of precipitation (DSD) with a high resolution  do a classification of different rain regimes within the same precipitating event  derive specific Z-R relationships for these regimes Check the efficiency of these specific Z-R relationships against a single one

4. X-band radar (9.41GHz) Elevation: 5° High resolution:  Time: 30 s  Azimuth: 2°  Range: 60 m Max range: 20 km

5. Micro Rain Radar (K-band, 24.1GHz) Doppler spectra of 63 bins (0 to 12 m.s -1 ) over 32 range gates every 10 s Relation between drop diameter and terminal fall velocity (Atlas et al. 1973): Profile of DSD

6.  Derivation of rain parameters:  Attenuation coefficient  Iterative attenuation correction  Reflectivity factor  Rain rate

7. June 15, 07 (IOP 3b) Synoptic-scale through moving northeastwardly giving stratiform precipitation with weak showers over the COPS area

8. DSD temporal evolution Grayscale: Number of raindrops in size interval Bold solid line: Median-volume diameter Thin solid lines: 10th and 90th percentiles of distribution of liquid rain water content over raindrop diameters   measure of the width of the raindrop size distribution

9. DSD temporal evolution 1 st period: small drops, narrow spectra, high variability 2 nd period: large drops, wide spectra, medium variability 3 rd period: low variability anomaly 1 2 3

10. Anomaly less visible near the ground MRR measurement issue due to:  strong updraft  heavy attenuation  bad noise level estimation

11. Z-R relationships GlobalSpecific 1 2 3

12. Corresponding rainfall RainrateCumulative rainfall MRR estimationGlobal Z-RSpecific Z-R Total rainfall (mm)2.812.532.50

13. August 8-9, 07 (IOP 14b) An intense large-scale precipitating system spread over the COPS area during all the night

14. DSD temporal evolution 1 st period: medium drops, medium variability 2 nd period: small drops, narrow spectra, low variability 3 rd period: small drops, narrow spectra, medium variability 4 th period: high variability 1 23 4

15. Z-R relationships GlobalSpecific 1 23 4

16. Corresponding rainfall RainrateCumulative rainfall MRR estimationGlobal Z-RSpecific Z-R Total rainfall (mm)10.8710.7410.80

17. Conclusions and perspectives High variability of rain even within a stratiform precipitation system Detection of temporally stable regimes of precipitation with significantly different Z-R relationships Derivation of the equivalent exponential or gamma distribution to explain the difference between the Z-R relationships Next step: apply these specific Z-R relationships on the X-band reflectivity

18.  Problem: How to detect these regimes with a single parameter X-band radar ? Periods of increasing, stagnating and decreasing intensity can be part of the same temporally stable regime of precipitation Conclusions and perspectives 1 2 34 2 3 1

19. Thanks for your attention Questions ?