Rainfall data for validating satellite rainfall estimates - Precipitation network set up in Africa for AMMA Henri Laurent Marielle Gosset (Benin) Christian Depraetere Thierry Lebel (Niger) IRD/LTHE, Grenoble, France Abou Amani Abdou Ali Agrhymet, Niger

Ground validation issues - time sampling effect “ground truth”: estimation of areal rainfall and accuracy Need for a good knowledge of rain fields  raingauge networks  radar Observations and studies in the AMMA framework (African Monsoon Multidisciplinary Analyses) regional scale – daily rainfall observations meso scale – high resolution observations

Convective cloud cover – 1 month Reference: all Meteosat images Time sampling problem     Rainfall estimate error (%)   1°x1° 5°x5° annual Jul/Aug Jun/Sep SSM/I 40 73 101 29 TRMM 36 76 92 23 MT 25 65 18 Sampling: SSM/I Sampling: TRMM Using the dense raingauge network in Niamey (1°x1°), it has been shown that the time sampling error is reduced by 15-25 % for MT compared to TRMM Sampling: MT  

Rainfall estimation at regional scale (from daily rainfall) Raingauge network - Sahel • CILSS : 600-650 + CRA : 280 O Synop : 85

Raingauge network - Sahel Summary on the kriging method used to create the areal rainfall for validation of satellite rainfall estimates  Regression Kriging method used to estimate the mean areal rainfall (grid: 0.5°x0.5°, 1°x1° or 2.5°x2.5°) cumulated oved 10-day, monthly or annual periods   Anisotropy of rainfall fields: the drift has to be taken into account  For details on the kriging method, see: Ali et al., J. Appl. Meteo, 2005 (in press)

Comparison of different methods for areal rainfall estimate 3 krigging methods taking the drift into account Theor. error Observed error Interpolated values are close, but very different estimations of theoretical error

Intercomparison of different satellite products Monthly rainfall, 2.5°x2.5° Sahel - 1990-1999 CMAP (Sat+gauges) GPCP (Sat+gauges) GPCC  (gauges) GPI (Sat) SYN (gauges from synoptic network) RMSE (%)

Rainfall at regional scale: daily estimation? Tracking from METEOSAT infrared channel 19 July 1994 Kriging from CILSS daily rain gauges

African Monsoon Multidisciplinary Analysis AMMA Long term experimental set up 3 meso-scale sites – 2 of which are already well equiped for precipitation measurements. Upper OUEME valley 15 000 km2 Soudanian rain : 1200-1300 mm/year specialized in water budget / hydrological processes. data since 1997 Gourma 30 000 km2 Sahelian to Saharian Rain : 200 - 400 mm/year site specialized in vegetation + satellite validation. Few rain gages / Possibility to densify. Niamey square degree 10 000 km2 Sahelian rain : 450-600 mm/year Specialized in hydrology and the study of land / rain intreactions. Data since 1990 (Hapex –Sahel, Epsat-Niger)

Niamey square degree Since 1989: between 30 and 109 raingauges Many works, e.g.: Lebel et al., Water Res. Res., 1992 – Amani et al., Water Res. Res., 1996 – Lebel et al., J. Hydro, 1997 – LeBarbé and Lebel, J. Hydro, 1997 – Amani and Lebel, J. Hydro, 1997 – Amani and Lebel, Sto. Hydro., 1998 – Lebel and Amani, J. Appl. Meteo, 1999 – Mathon et al., J. Appl. Meteo, 2002 – Ali et al., J. Hydromet., 2003 See www.lthe.hmg.inpg.fr/catch/ Very good knowledge of Sahelian rain fields modelisation, downscaling issues interpolation and estimation (kriging) estimation error Not simply transposable in another region  First it is needed to study precipitation fields

Raingauge network – Mesoscale sites Available data sets for 2004 Niamey square degree (Niger) 33 recording rain gauges Raw data 5 min, ~ from May to September (depends on the station) Validated data: 10-day periods - station and grid (kriging 5 km x5 km) rainfall events (i.e. >30% rainy stations) - station and grid (kriging 5 km x5 km) Oueme (North Benin) 35 recording rain gauges Raw data 5 min, all over the year (with some missing data) Validated data: daily rainfall (stations) Gridded estimates are not available (yet) by lack of climatological knowledge

Upper OUEME valley Mesoscale Site: Raingage network, river flow, ground water. Surface, monitoring of vegetation dynamics. Meteo/climate stations “Super Site”: Donga watershed Denser network (20 gages / 600 km2) Meteorological radar Xport + optical disdrometer

Details: www.lthe.hmg.inpg.fr/catch/xport/ X port Radar developed at LTHE X band – 9.4 GHz diameter 1.8 m – 100 kW polarisation H and V doppler Details: www.lthe.hmg.inpg.fr/catch/xport/ Optical Spectrogranulometer, recording data every 1 min on the rain drop size distributions observed at ground level.

X-port : Data and objectives Donga / Bénin, 2004-2007 - EOP AMMA Which measurement ? -Reflectivity (power returned to the radar by the precipitation)  Amount of precipitation -Polarimetric variables (difference between Horizontal and Vertical signal)  median diameter of the drop size distribution  attenuation correction -Doppler  velocities of hydrometeors. 2D - Structure 3 D structure multiparameters

Radar - vertical profiles analysis Vertically pointing mode: vertical structure of precipitation (images VPR McGill) Derive statistics of vertical structure in a given climatic region observe amount of convective vs stratiform rain quantify occurrence of evaporation  improve parameterization  feed data base for satellite remote sensing algo. (+ FFT analysis of Doppler spectrum -> evolution of DSD with height)

Radar + disdrometer data - Application - High resolution 2D fields of precipitation – Homogeneity ? Propagation at ground ? - Down scaling issues - Observation of vertical profile of reflectivity within rain storm – gather profil types and assess variability, useful for inversion of satellite data - DSD analysis + radar polarimetric product : Analyze the time/space variability of Drop size distributions at the ground level.

Rainfall types during the rainy season (1999-2003) Ongoing studies on the characterisation of the rainfall events in North Benin using rain gauge data Development of a rainfall model valid for Sahel and sub-Sahel rain fields. Based on a modelisation of convective cells Rainfall types during the rainy season (1999-2003) Identification of Mesocale Convective Systems (rainfall) and determination of their propagation (speed and direction) Depraetere et al., EGU Conference, 24-29 April 2005, Vienna, Austria

Directional chronogram of the rainfall event Computation of optimal direction and speed of the rainfall event Directional chronogram of the rainfall event Meso scale hyetogram derived from the pseudo-chronogram Directional pseudo-chronogram of the rainfall event

Possible collaborations on ground validation issues Summary Possible collaborations on ground validation issues rainfall ground truth – estimation and estimation error - regional scale - meso scale possibilities in the West African, sub-Sahelian zone : - Data from the Upper Ouémé meso-scale site - Rainfield modelling /Down scaling issues. - Use of a light X-Band, polarimetric radar for field observation of the precipitating systems