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Weather and climate monitoring for food risk management. Consiglio Nazionale delle Ricerche. WMO, Geneva, November 2004. G. Maracchi IBIMET-CNR. Critical tools for food risk management in West Africa:. The activities of Ibimet are: Monitoring (rainfall, vegetation)

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weather and climate monitoring for food risk management
Weather and climate monitoring for food risk management

Consiglio Nazionale delle Ricerche

WMO, Geneva, November 2004

G. Maracchi

IBIMET-CNR

slide2

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)
slide3

Monitoring rainfall

Calibration of IR Meteosat channel using SSM/I

+

SSM/I: 7 passages /day

Meteosat IR channel

slide4

Monitoring rainfall

Meteosat & SSM/I output

Temporal res: every six hours – Spatial res ~ 5 km

slide5

Monitoring rainfall

Meteorological Information Service for the area touched by the Darfur crisis

slide6

Monitoring rainfall

Integration of a Local Area Model in satellite rainfall estimate

Model: RAMS 4.3.0.0

Simulations Domain:

1 Grid

Delta_x = Delta_y = 60km

NX = NY = 120

Top = 17 km, 36 levels

slide7

Monitoring rainfall

Integration of a Local Area Model in satellite rainfall estimate

Satellite Estimate

RAMS Simulation

Regional Reanalysis with RAMS

-use of satellite estimation to locate rainfall events

-use of RAMS simulation to extrapolate rainfall amount

slide8

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
slide9

Monitoring NDVI

Derived product: vegetation development

Seasonal vegetation development in Burkina-Faso – AP3A Project

slide10

Short term forecast

Statistical Downscaling of Global Forecast System

GFS 00 UTC run

Variables: total precipitation, wind, pressure, relative humidity, temperature

Levels: surface, 1000mb, 925mb, 850 mb

Spatial coverage: global – Resolution 1°

Input

Statistical Model

Kriging method

Output

  • Daily and comprehensive (180hrs) output of the choosen variables at 0.1° resolution distributed through Internet facilities – Spatial coverage: West and East Africa
slide11

Short term forecast

Statistical Downscaling of Global Forecast System

Kriging

Forecast period:00 - 180Hrs

Resolution:0.1°

Spatial coverage:18W 49E – 3N 28N

Forecast period:00 - 180Hrs

Resolution:1°

Spatial coverage:Global

slide12

Short term forecast

Statistical Downscaling of Global Forecast System

Other parameters downscaled:Relative Humidity 1000mb + Temperature 1000mb + Zonal and Meridional wind + Pressure

Forecast period:00 - 180Hrs

Resolution:0.1°

Spatial coverage:18W 49E – 3N 28N

slide13

Medium term forecast

Vertical Integrated Moisture Transport – VIMT

The moisture advection is mainly meridional

slide14

Medium term forecast

Operative use of VIMT through

HOWI (Hidrological Onset and Withdrawal Index)

slide15

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

slide16

Medium term forecast

Current monsoon season

HOWI dynamics computed for each area of interest

Comparison with

climatological profile

slide17

Medium term forecast

SISP/ ZAR (Zones à Risque) Models

Input

Methodology

Output

  • 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
  • Rainfall estimates derived from METEOSAT images
  • Agroclimatic characterisation of the territory based on rainfall time series analysis and relevant cropping systems (millet, sorghum)

ZAR Model

SISP Model

slide18

Medium term forecast

ZAR (Zones à Risque) Output

Comparison between the beginning of season respect to climatology

Estimation of the length of season

slide20

Long term forecast – State of art

IRI

African Desk (NOAA/NCEP)

Presao ACMAD

slide21

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

slide22

Long term forecast

State of the art at IBIMET -

Each year in [1979-2003] is defined by the esa vector = (SSTs1,…,GrowthRate1,…)

Forecast criterion: Proximity technique with euclidean distance for comparison with similar years

slide23

Long term forecast

State of the art at IBIMET – 2004 Result

OUTPUT: Percentage anomaly respect to climatology

ISSUED: every month since April

VALIDITY: 3 months

slide24

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
slide25

Long term forecast

Statistical Model IBIMET - Predictors

Computation of Atlantic and Guinean SST anomalies thanks to MSG

slide26

Long term forecast

Statistical Model IBIMET - Predictors

Geopotential Height Anomalies

slide27

Long term forecast

Statistical Model IBIMET - Predictors

Sahel spring soil humidity anomalies

slide28

Long term forecast

Statistical Model IBIMET - Predictors

Previous SepOctNov Guinean Precipitation

slide29

Long term forecast

Statistical Model IBIMET

Predictors

-SSTs Anomalies -Geopotential Heigth 500 mb -Soil Humidity -Previous SON Guinean preciptation

Statistical Model

MultiLinear Regression MLR with Stepwise

Output

  • Percentage Anomalies respect to climatology
  • Forecast validity 3 months
  • Issued every month since April
slide30

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