MAINSTREAMING CLIMATE CHANGE ADAPTATION IN AGRICULTURAL EXTENSION
Slide 19
PLAN FOR HOW AN EXTENSION WORKER COULD WORK WITH A GROUP OF
FARMERS USING CLIMATE INFORMATION
Well before the season When SCF and El Nino / La Just before
starts eg June
Nina predictions are
season
available eg Sept
starts
Working with groups of farmers Communicate these to farmer
Farmers use
look at whether there are any groups, (including for El Nino and short term 10
climate trends (by looking at
La Nina the ‘strength’)
day forecasts
graphs together with farmers) (In future years it may be sufficient (and refer to
to text this information to a
probabilities
‘contact’ farmer in each group) and forecasts)
Communicate probabilities of Consider implications with farmers
events to farmers in participatory for livelihoods and crops (revisit
way (including discussion on
options you did with farmers in last
implications and management box of previous column).
options)
Include looking at data for El
Support services e.g. extension,
Nino, La Nina years and discuss can now consider any implications
usefulness of this and of SCF
for farmer requirements eg make
Make farmers aware of 10 day available seeds of varieties needed
forecast
Consider livelihood and crop
options for El Nino, La Nina and
‘normal’ years
(It is also possible to revise now the
probabilities of events eg for a
normal year if you want to)
During season
Use 10 day forecasts & refer
to probabilities. Update of
SCF becomes available & by
then is evident whether it is
an El Nino / La Nina year etc
(May be possible for 10 day
forecasts to be sent to contact
farmers and AEWs by sms to
cell phones?)
i) Continue to visit and work
with farmers
ii) Observe and get feedback
on how this process and
support to farmers can be
improved
Visit farmers at end of season
for feedback &see how this
approach can be improved
Slide 22
2012
Mean number of rain days (Makoholi)
Mean number of rain days (rain is defined as a value >0.85mm)
Month
La Nina Ordinary El Nino
November
December
January
February
March
April
8.4 7.9
12.3 12.5
14.3 9.89
9.6 8.2
6.6 7.0
3.4 3.3
5.1
7.1
7.3
6.8
6.3
3.2
Slide 20
Looking at El Nino and La Nina years
• It can be forecasted well before the season whether
it is likely to be an El Nino, La Nina or ‘normal’ season
• This is because sea surface temperatures in the
oceans before the season will affect whether the
season is going to be El Nino, La Nina or ‘normal’.
These temperatures can be measured before the
season
• In some parts of the country El Nino seasons are
often drier than normal seasons
• Also in some parts of the country La Nina seasons are
often wetter than in normal seasons
• So, first we need to know whether the location in the
country is one where El Nino /La Nina has an effect
on rainfall
Slide 23
El Nino vs other years Makoholi
Nov to Jan Total number of rain days
Total number of rain days from November to January
50
Other
ElNino
40
30
20
10
0
1970
1980
1990
Season
2000
2010
A rain day is defined as one with more than 0.85mm
Slide 21
El Nino, Ordinary and La Nina years at
Makoholi (from IRI)
La Nina
1970
1973
1975
1984
1988
1998-1999
2007
2010
Ordinary
1964
1966-1969
1971
1974
1976-1981
1983
1985
1989-1990
1992-1993
1995-1996
2000-2001
2003-2005
2008
El Nino
1965
1972
1982
1986-1987
1991
1994
1997
2002
2006
2009
Slide 24
El Nino vs other years Makoholi
Feb to April Total number of rain days
Total number of rain days from February to April
50
Other
40 ElNino
30
20
10
0
1970
1980
1990
Season
2000
2010
A Training Manual on Use of Climate Information and Vulnerability and Capacity Assessment for
Agricultural Extension Staff in Zimbabwe
Page 129