The application of climate forecasts and agrometeorological information for agriculture, food securi

1
The 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

2
Information needs ofFOOD SECURITY

• Availability of input data
• Appropriate location
• Appropriate spatial resolution
• Timely information

3
Existing Food Security Systems
4
Existing 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.

5
Existing Food Security Systems - AGRHYMET SISP
Parameterization of crop phenology
6
Existing Food Security Systems - AGRHYMET SISP
Correlation between the production SISP indexes
and the agricultural statistics
7
(No Transcript)
8
Existing Food Security Systems - USAID FEWS

• The analysis is organised in three sections
• Vulnerability/Baseline Information
• Hazard/Shock Information
• Risk/Outcome Analysis

9
(No Transcript)
10
(No Transcript)
11
Existing 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

12
Existing Food Security Systems - DHC-Champs
pluviaux
13
Existing 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

14
(No Transcript)
15
Existing 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

16
Existing 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

17
Existing Food Security Systems - FAO GIEWS
18
Solving 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
19
The 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

20
Link 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
21
(No Transcript)
22
(No Transcript)
23
Teleconne-ctions in Sahel
24
Simultaneous Correlation of Sahel Rainfall with
SST (June, July)
25
Simultaneous Correlation of Sahel Rainfall with
SST (August, September)
26
Correlation of Sahel Rainfall in June and July
with SST in May
27
INTERTROPICAL 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)
28
INTERTROPICAL CONVERGENCE ZONE - location
Rapidly increasing SST in May over Guinea cause
delayed monsoon in Sahel (June and July)
29
Synthetic 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

30
Existing 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

31
Applications 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

32
Data formats
33
The 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

34
The 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

35
Examples of Net Assessments
36
Omotosho 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

37
Omotosho methodology Onset of the growing season
38
IBIMET 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)

39
Exercise 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
40
Forecasting 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
41
Estimation 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
42
Field Observation Data Section
Field observation areas Data collected by local
institutions
The collected information are related to the
real sowing date
43
The information of the different three sections
has been compared in order to evaluate the process
Results-2001
42A
44
Results-2002
42B
45
Comparison between predictions
46
Examples of comparison2002 wet season
PRESAO FORECAST
CLIMAG WA FORECAST
Zone 3
Zone 2
Zone 1
47
MONITORING 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

48
MONITORING ACTIVITIES - operational tools
Bulletins

• Ex. AGRHYMET Regional Centre

49
MONITORING ACTIVITIES - operational tools
Space-borne information

• Satellite images (METEOSAT, NOAA,...)

50
MONITORING ACTIVITIES - operational tools
INTERNET

• Warnings diffused by Internet

51
CONCLUSIONS

• 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)