Presentation on theme: "Rainfall estimation for food security in Africa, using the Meteosat Second Generation (MSG) satellite. Robin Chadwick."— Presentation transcript:
1 Rainfall estimation for food security in Africa, using the Meteosat Second Generation (MSG) satellite. Robin Chadwick
2 Contents of presentation Motivation for satellite rainfall estimation in AfricaTAMSAT satellite rainfall estimation methodologyMet office NIMROD nowcasting precipitation estimation product.Extension of Met office rainfall estimates to AfricaAMMA Sahelian rain-gauge datasetComparison of Met office rainfall estimates against TAMSAT estimates and AMMA gauge dataCurrent and future work
3 Motivation for satellite rainfall estimation in Africa Accurate near-real time estimates of rainfall are vital for humanitarian applications such as famine prediction and prevention, and flood prediction.Very few precipitation radar networks. Rain-gauges sparce and badly maintained.Satellite based rainfall estimation algorithms offer one solution to this problem.Several algorithms exist, using IR data (from geostationary satellites) , passive microwave data (from polar orbiting satellites) or a combination.
5 The TAMSAT rainfall estimation method Utilises one infrared channel (10.8 microns) from the MSGSimple method based on the concept of Cold Cloud DurationProduces operational dekadal rainfall estimates for AfricaIntercomparisons of various satellite rainfall products over Africa have found that the TAMSAT method is as accurate as more complex algorithms.Should be possible to improve on this because of the information on rainfall provided by other channels on the MSG.
6 TAMSAT methodologyCCD is the Cold Cloud Duration; the length of time each pixel is below the threshold temperatureRainfall, R = a + b(CCD)Threshold temperature and coefficients a, b calibrated for each region using historical rain-gauge data
7 TAMSAT rainfall estimate for 2007 October 1st dekad
8 Met office NIMROD nowcasting precipitation estimation product Rain-rate estimates over Europe produced operationally every 15 minutesRadar Satellite Analysis+=Francis et al ‘06
9 Calibration of NIMROD using only 2 MSG channels MeteosatIR channelRadar rain-rateBrightDarkColdWarmMeteosatVis channelNimrod satelliterain-rate
10 Extension of NIMROD to multiple channels SZA Primary correlation method0o-75o d (0.8/1.6/3.9 refl/10.8)75o-80o 4-d (0.8/1.6/3.9 refl/10.8) =>3-d (0.8/1.6/10.8)80o-85o 3-d (0.8/1.6/10.8)85o-88o 3-d (0.8/1.6/10.8) =>3-d (3.9BT/10.8/12.0)>88o 3-d (3.9BT/10.8/12.0)
13 Current domain of Met office algorithm extension
14 The AMMA Sahelian rain-gauge dataset O.5 degree resolution gridded rain-gauge dataset for May – September 2004 covering the Sahel.Met office estimates processed for this period & region using historical MSG dataEstimates still use (historical) European radar data for calibrationComparison of Met office estimates against AMMA gauge data, for grid cells containing gauges only.Comparison of TAMSAT estimates against AMMA gauge dataComparison of Met office estimates against TAMSAT estimates
20 Current and Possible Future work Use of historical local radar data (AMMA or TRMM) to calibrate the Met office algorithmUse of historical gauge data to constrain or calibrate an MSG based algorithmNeural network based algorithm