Title: The application of climate forecasts and agrometeorological information for agriculture, food securi
1The application of climate forecasts and
agrometeorological information for agriculture,
food security, forestry, livestock and fisheries
- G. Maracchi, F. Meneguzzo, M. Paganini
- Banjul, Gambia, 9-13 December, 2002
2Information needs ofFOOD SECURITY
- Availability of input data
- Appropriate location
- Appropriate spatial resolution
- Timely information
3Existing Food Security Systems
4Existing Food Security Systems - AGRHYMET SISP
- Base parameters
- statistical analysis procedures on rainfall for
ecological zoning - a millet simulation model to estimate millet crop
conditions and the effect of rainfall
distribution - statistical analysis of the yields.
5Existing Food Security Systems - AGRHYMET SISP
Parameterization of crop phenology
6Existing Food Security Systems - AGRHYMET SISP
Correlation between the production SISP indexes
and the agricultural statistics
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8Existing Food Security Systems - USAID FEWS
- The analysis is organised in three sections
- Vulnerability/Baseline Information
- Hazard/Shock Information
- Risk/Outcome Analysis
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11Existing Food Security Systems - DHC-Champs
pluviaux
- The CCD are used in the crop water diagnostic
(DHC) in order to produce - maps of the crop water satisfaction
- maps of the crop water needs
- maps of crop yields
12Existing Food Security Systems - DHC-Champs
pluviaux
13Existing Food Security Systems - World Food
Programme -Vulnerability Analysis Mapping
- WFP has produced vulnerability assessment maps in
3 stages - identifying the income sources for each relevant
group - analysing the causal structure of vulnerability
- reconciling the analysis of risk and coping
capacity
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15Existing Food Security Systems - FAO GIEWS
- monitors food supply and demand
- analyses information on production stocks, trade
and food aid - monitors export prices
- reacts to natural disasters
- issues Special Alerts and up-to-date reports
16Existing Food Security Systems - FAO GIEWS
- web pages on the Internet
- develops new approaches for early warning
- cultivates and maintains information-sharing
between governmental and private actors - depends on the free exchange of information
17Existing Food Security Systems - FAO GIEWS
18Solving the problem
FOOD SECURITY INFORMATION
- Information available on Internet
- More appropriate to the decision makers
information needs - Improved survey methods and operations for
monitoring actual and potential outbreak areas - Create interaction between producers of
information
CLIMATE PREDICTION INFORMATION
19The local CLIMATE
- Decreasing annual pluviometry S-N
- Alternation of dry season (9-5 months) and rainy
season - The monsoon is the main defining factor
- Unimodal distribution of the rain
20Link between climate and teleconnections
CLIMATE DEFINITION
- The average of the weather over periods
- The effects of changes in sea surface
temperatures in the Pacific Ocean on temperature
and rainfall patterns in regions that are far
away from the Pacific
TELECONNECTIONS DEFINITION
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23Teleconne-ctions in Sahel
24Simultaneous Correlation of Sahel Rainfall with
SST (June, July)
25Simultaneous Correlation of Sahel Rainfall with
SST (August, September)
26Correlation of Sahel Rainfall in June and July
with SST in May
27INTERTROPICAL CONVERGENCE ZONE - location
- Drought years are associated with the ITCZ being
south of its normal position, while wet years are
associated with the ITCZ north of normal
Warmer SST in Guinea Gulf lead to higher
precipitation over Guinea coast (increased
moisture) and lesser over Sahel (northerly flow,
sinking at low levels)
28INTERTROPICAL CONVERGENCE ZONE - location
Rapidly increasing SST in May over Guinea cause
delayed monsoon in Sahel (June and July)
29Synthetic descriptions of atmospheric
teleconnection patterns
- Can be found at following addresses
- The Climate Diagnostics Center
(NOAA)http//www.cdc.noaa.gov/Teleconnections - Climate Precition Center (NOAA)
http//www.cpc.noaa.gov/data/teledoc/telecontents.
html
30Existing climate predictions
- Amount of rainfall
- IRI Net assessments
- PRESAO outlook
- CLIMAG WA enhanced methodology
- Onset of the growing season
- IBIMET methodology (Maracchi/Pini)
- Omotosho method
- CLIMAG WA enhanced methodology
31Applications for 2001 2002
- Comparison of results per single zone for each
year - BUT
- Each methodology has its own spatial resolution
- Each methodology has its own temporal resolution
32Data formats
33The IRI Forecast Process (1)
- Forecasting the tropical SST anomalies using
dynamical and statistical models - Using the predicted SST for atmospheric general
circulation models (GCMs) - Estimating the expected skill
34The IRI Forecast Process (2)
- Statistical postprocessing of model output
- Putting all the indications together a final IRI
forecast called net assessment - issued in the form of maps that show regions
having homogeneous forecast probabilities for the
below, near and above normal terciles
35Examples of Net Assessments
36Omotosho methodology Onset of the growing season
- The method is empirical/dynamical and uses the
following requirements - Difference between the U-component of the wind at
3000 m and at the surface must be between 20 m/s
and 5 m/s - Difference between the U-component of the wind at
7500 m and at 3000 m must be between 0 and 10 m/s
37Omotosho methodology Onset of the growing season
38IBIMET method
Onset of the growing season
- Predict the seeding decades for the different
zones in order to produce advises to peasants - The philosophy is to utilise the information
already available on INTERNET (NOAA, IGES COLA,
ADDS)
39Exercise for the agricultural season 2001
1 Rainfall Forecasting section NOAA - Climate
Prediction Center, Prediction of the rainfall
quantity at 24-96 hours 2 Rainfall Estimation
section ADDS - Africa Data Dissemination Service,
Decadal rainfall estimation images 3 Field data
section Real sowing dates in different areas in
Mali collected by local institutions
40Forecasting Section
Daily forecast images
Total rainfall of the decade
Through the daily images it is possible to
forecast the amount of rainfall expected in the
decade and give the advise of the sowing date to
farmers
41Estimation Section
Precipitation Estimate based on GPI, SSM/I, AMSU
and GTS
The image has been utilised to validate the
information prepared by the forecasting
information
42Field Observation Data Section
Field observation areas Data collected by local
institutions
The collected information are related to the
real sowing date
43The information of the different three sections
has been compared in order to evaluate the process
Results-2001
42A
44Results-2002
42B
45Comparison between predictions
46Examples of comparison2002 wet season
PRESAO FORECAST
CLIMAG WA FORECAST
Zone 3
Zone 2
Zone 1
47MONITORING ACTIVITIES - an added value
- Allows to evaluate the conditions of the wet
season on the agricultural and food situation - Allows to evaluate the conditions and the
effectiveness of the Early Warning Systems and of
the mechanisms of crisis management
48MONITORING ACTIVITIES - operational tools
Bulletins
- Ex. AGRHYMET Regional Centre
49MONITORING ACTIVITIES - operational tools
Space-borne information
- Satellite images (METEOSAT, NOAA,...)
50MONITORING ACTIVITIES - operational tools
INTERNET
- Warnings diffused by Internet
51CONCLUSIONS
- Improving and merging food security systems
- Improve interactions and combinations between
food security and seasonal prediction systems - Using seasonal prediction to define specific
inputs (e.g. onset of the growing season)