POLICY IMPLICATIONS OF PRICE DYNAMICS AND THE WAY FORWARD - Food Security, Food Prices and Climate Variability - page 183

food price information should provide insight into overall stability in the 19 fragile states in
the region. As a pilot exercise, this data collection approach should be launched in a few stable
and a few fragile states in Africa.
Drought monitoring systems to anticipate the impacts of climate
variability
Information about the weather in the upcoming growing season is a critical and little exploited
way to reduce the impact of climate variability on agriculture. As described in Chapter 3 ,
climate variability refers to short-term (daily, seasonal, annual, interannual, several years) vari-
ations in climate. As food production is increasingly affected by weather shocks, monitoring
and mounting an effective response to extreme events will become more important to ensure
a reliable and consistent food supply. Food access will become increasingly affected by climate
variability in remote areas that have limited access to other markets.
Iizumi et al . (2013) presents a global assessment of the reliability of crop failure retro-
spective analysis for major crops at two lead times derived by linking ensemble seasonal cli-
matic forecasts with statistical crop models. Pre-season yield predictions employ climatic
forecasts and have lead times of approximately three to five months for providing information
regarding variations in yields for the coming cropping season. Within-season yield predictions
use climatic forecasts with lead times of one to three months. Pre-season predictions can be
of value to national governments and commercial concerns, complemented by subsequent
updates from within-season predictions. The latter incorporate information from meteoro-
logical networks and satellite data for the upcoming period of reproductive growth (Iizumi
et al ., 2013).
Moderate-to-marked yield loss over a substantial percentage (26-33 percent) of the harvested
area of these crops could reliably be predictable if climatic forecasts are near perfect. However,
only rice and wheat production are reliably predictable at three months before the harvest using
within-season forecasts. The reliabilities of estimates varied substantially by crop: rice and wheat
yields were the most predictable, followed by soybean and maize. The reasons for variation in the
reliability of the estimates are the differences in crop sensitivity to the climate and the technology
used by the crop-producing regions (Iizumi et al ., 2013). The findings reveal that the use of sea-
sonal climatic forecasts to predict crop failures will be useful for monitoring global food produc-
tion and will encourage the adaptation of food systems to climatic extremes.
Hansen et al . (2011) argue that in some locations, seasonal forecasts can be demonstrated
to have accuracy in predicting the upcoming season. The effective management of climate
risk requires both information and the ability to respond or mechanisms of response to
extreme events. The ability to anticipate climate fluctuations and their impact on agriculture
months in advance should, in principle, enable several opportunities to manage risk. The
authors point out that these opportunities can be exploited, but only within an enabling envi-
ronment that will provide farmers with the opportunities to adopt improved technology,
intensify production, replenish soil nutrients and invest in more profitable enterprises when
conditions are favorable; and to protect more effectively families and farms against the long-
term consequences of adverse extremes (Hansen et al ., 2011).
Early identification of extreme events such as drought and unusually wet conditions is
important for early detection of widespread food production deficits. Poor rainfall accumula-
tions can be identified early in the season and can be a critical mid-season indicator of likely