Crop Insurance as a Risk Management Strategy in Bangladesh

Historical
monthly values
Mean Standard deviation
Coefficient
of variation
Future Monthly
Climatic attributes
(12 Months)
1 st
set
n th
set
Future Standard
deviation
GCM Monthly
values
Probability distribution
( Lognormal)
System model for
Flood/Drought/Cyclone
System model for
Flood/Drought/Cyclone
Figure 5.11: A conceptual model for risk analysis by generation of synthetic future climatic
attributes under changing climatic condition
Where, X is a score from the original normal distribution, µ is the mean of the original
normal distribution, and σ is the standard deviation of original normal distribution. The
standard normal distribution is sometimes called the z distribution. If the value of µ and σ is
known, for a set of random number generated the Z values can be estimated for the normal
probability plot. Figures 5.12 (a) and (b) show an example of generating 100 sets of monthly
precipitation values for future scenarios of doubling CO2 level, based on GCM predicted
change in precipitation amount.
ppt./ cm
70
60
50
40
30
20
10
0
0 2 4 6 8 10 12
month
75
total ppt./mm
2500
2000
1500
1000
500
O(1)
O(n)
Risk of
Flood/Drought/
Cyclone
Risk of
Flood/Drought/
Cyclone
yearly total ppt.
0
0 20 40 60 80 100
year/data set
ppt. generated
historical ppt. obsv.
Figure 5.12: (a) Generation of synthetic monthly data set for the Monte Carlo Simulation, and
(b) Yearly total amount of the historical observed and generated synthetic precipitation data