Seasonal weather forecasting: Integration of indigenous and scientific knowledge
Henry Mahoo1, Winfred Mbungu1, Filbert Rwehumbiza1, Emmanuel Mpeta2, Isack
Yonah2, James Kinyangi3, Maren Radeny3, John Recha3, 4
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2
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Sokoine University of Agriculture (SUA), Tanzania
Tanzania Meteorological Agency (TMA)
CGIAR Research Program on Climate Change, Agriculture & Food Security (CCAFS), E. Africa
Presenting Author, j.recha @cgiar.org
Smallholder farmers in East Africa are highly vulnerable to climate change and variability. Other
environmental stresses and low adaptive capacity lead to food insecurity. Due to increased
exposure to climate risks, smallholder farmers who mainly depend on rain-fed agriculture for
their livelihood have developed various risk coping strategies. However, the increasing climate
variability, frequency and severity of climate risks highlights the need for downscaled, reliable
and timely climate information to inform farm-level decision making processes. Despite
progress in provision of climate services by the Meteorological Departments in East Africa,
significant gaps still exist. These gaps include the type of climate information useful to farmers,
and location specific forecasts that can assist farmers to make decisions on when and what to
plant, for example. Consequently, farming communities have been relying on forecasting using
indigenous knowledge (IK). This study identifies and documents existing IK in weather
forecasting withgin the agroecologicall diverse Lushoto district, Northern TanzaniaThe aim is to
promote the integration and utilization of IK and scientific weather forecasting for risk
management and improved food security.
The IK indicators identified included changes in behaviour of domestic and wild animals, plant
phenology, wind movement, appearance of the moon, cloud formation, and air temperature.
Nearly all the respondents were aware of the change in climate, and identified the agricultural
sector as the most affected by climate variability. Majority of the farmers (56%) indicated that
weather forecasts using IK were more reliable and specific to their location compared to
scientific forecast from the meteorological agency which tends to be more general. Three local
IK forecasting teams have been constituted across seven villages. For the 2012 long rainy season
(March-May), the IK teams forecasted a normal rainfall season with 90% accuracy and were in
agreement with the scientific forecast from Tanzania Meteorological Agency (TMA). However,
the farmers observed that IK forecasts were more reliable for the long rainy season (March-May)
compared to the short rainy season (October-December) unlike the scientific weather forecast
from TMA.
There is a need to establish a framework for integrating seasonal weather forecast information
from IK and TMA, establish an information dissemination network and to integrate weather
forecasting in the District Development Programmes. Only 61% of the farmers access TMA
weather forecasts through the media.
Key words: Indigenous knowledge, weather forecasts, rainy season