Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Weather and climate monitoring for food risk management.

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Presentation transcript:

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Weather and climate monitoring for food risk management G. Maracchi IBIMET-CNR Consiglio Nazionale delle Ricerche WMO, Geneva, November 2004

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Critical tools for food risk management in West Africa: The activities of Ibimet are: Monitoring (rainfall, vegetation) Short term forecast (rainfall, temperature, humidity) Medium term prediction (advection of humidity, beginning and length of the cropping season in the Sahel) Long term prediction (2-3 months rainfall prediction)

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring rainfall Calibration of IR Meteosat channel using SSM/I SSM/I: 7 passages / day + Meteosat IR channel

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring rainfall Meteosat & SSM/I output Temporal res: every six hours – Spatial res ~ 5 km

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring rainfall Meteorological Information Service for the area touched by the Darfur crisis

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring rainfall Integration of a Local Area Model in satellite rainfall estimate Simulations Domain: 1 Grid Delta_x = Delta_y = 60km NX = NY = 120 Top = 17 km, 36 levels Model: RAMS

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring rainfall Integration of a Local Area Model in satellite rainfall estimate RAMS Simulation Satellite Estimate Regional Reanalysis with RAMS -use of satellite estimation to locate rainfall events -use of RAMS simulation to extrapolate rainfall amount

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring NDVI MSG product Advantage: 15 minutes outputs used to compute daily and decadal images with Maximum Value Composite (MVC) technique in order to remove clouds effect

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Monitoring NDVI Derived product: vegetation development Seasonal vegetation development in Burkina-Faso – AP3A Project

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Short term forecast Statistical Downscaling of Global Forecast System Input Output Statistical Model GFS 00 UTC run Variables: total precipitation, wind, pressure, relative humidity, temperature Levels: surface, 1000mb, 925mb, 850 mb Spatial coverage: global – Resolution 1° Kriging method Daily and comprehensive (180hrs) output of the choosen variables at 0.1° resolution distributed through Internet facilities – Spatial coverage: West and East Africa

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Forecast period: Hrs Resolution: 0.1° Spatial coverage: 18W 49E – 3N 28N Forecast period: Hrs Resolution: 1° Spatial coverage: Global Kriging Short term forecast Statistical Downscaling of Global Forecast System

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Other parameters downscaled: Relative Humidity 1000mb + Temperature 1000mb + Zonal and Meridional wind + Pressure Forecast period: Hrs Resolution: 0.1° Spatial coverage: 18W 49E – 3N 28N Short term forecast Statistical Downscaling of Global Forecast System

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Medium term forecast Vertical Integrated Moisture Transport – VIMT The moisture advection is mainly meridional

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Medium term forecast Operative use of VIMT through HOWI (Hidrological Onset and Withdrawal Index)

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Medium term forecast Predictive meaning of HOWI When HOWI>0 we can predict that monsoon onset will take place from 6 weeks (WAM) up to 2 weeks after (North Sahel) WAM = 10W 10E – 5N 20N Sahel = 10W 10E – 10N 20N N Sahel = 10W 10E – 15N 20N

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Medium term forecast Current monsoon season HOWI dynamics computed for each area of interest Comparison with climatological profile

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Medium term forecast SISP/ ZAR (Zones à Risque) Models Input ZAR Model SISP Model OutputMethodology Rainfall estimates derived from METEOSAT images Agroclimatic characterisation of the territory based on rainfall time series analysis and relevant cropping systems (millet, sorghum) forecast of the length of the current season evaluation of the possibility to sow in zones that are not yet sown comparison between the actual onset with the average onset of the agricultural season the average growing season onset, length, end …

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Estimation of the length of season Comparison between the beginning of season respect to climatology Medium term forecast ZAR (Zones à Risque) Output

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Long term forecast – State of art ECMWFMet Office

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 IRI Long term forecast – State of art African Desk (NOAA/NCEP) Presao ACMAD

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Long term forecast State of the art at IBIMET Multidimensional space: SST Nino-3 std anomalies SST Guinea std anomalies SST Indian std anomalies SST Nino-3 Growth rate SST Guinea Growth rate SST Indian Growth rate

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Forecast criterion: Proximity technique with euclidean distance for comparison with similar years Each year in [ ] is defined by the esa vector = (SSTs1,…,GrowthRate1,…) Long term forecast State of the art at IBIMET -

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 OUTPUT : Percentage anomaly respect to climatology ISSUED : every month since April VALIDITY : 3 months Long term forecast State of the art at IBIMET – 2004 Result

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Long term forecast Development of a new statistical model at IBIMET New predictors: Atlantic and Guinean SST Anomalies Geopotential heigth 500 mb Soil moisture Previous (SepOctNov) Guinean 2° rainfall season

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Long term forecast Statistical Model IBIMET - Predictors Computation of Atlantic and Guinean SST anomalies thanks to MSG

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Geopotential Height Anomalies Long term forecast Statistical Model IBIMET - Predictors

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Sahel spring soil humidity anomalies Long term forecast Statistical Model IBIMET - Predictors

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Previous SepOctNov Guinean Precipitation Long term forecast Statistical Model IBIMET - Predictors

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 Predictors Long term forecast Statistical Model IBIMET Output Statistical Model -SSTs Anomalies-Geopotential Heigth 500 mb -Soil Humidity-Previous SON Guinean preciptation MultiLinear Regression MLR with Stepwise Percentage Anomalies respect to climatology Forecast validity 3 months Issued every month since April

Weather and climate monitoring for food risk management G. Maracchi WMO, Geneva, November 2004 CONCLUSION IBIMET activities cover all steps of meteo and climate informations for feeding food crises prevention process Innovative tools have been developed to improve monitoring and forecasting techniques Operational products are available and quasi real time diffusion of informations Effort in the next future will be focused on operational production of long term predictions