Indigenous knowledge for seasonal weather and climate forecasting across East Africa

Abstract

Climate information and agro-advisory services are crucial in helping smallholder farmers and pastoralists in East Africa manage climate-related risks and adapt to climate change. However, significant gaps exist in provision of climate information that effectively addresses the needs of farmers and pastoralists. Most farmers and pastoralists, therefore, rely on indigenous knowledge (IK), where local indicators and experiences are used to observe and forecast weather conditions. While IK-based forecasting is inbuilt and established in many communities in East Africa, coordinated research and systematic documentation of IK for weather forecasting, including accuracy and reliability of IK is largely lacking. This paper documents and synthesizes existing IK for weather forecasting in East Africa using case studies from Ethiopia, Tanzania, and Uganda. The results show that farmers and pastoralists use a combination of meteorological, biological, and astrological indicators to forecast local weather conditions. IK weather forecasting is, therefore, crucial in supporting efforts to improve access to climate information in East Africa, especially in resource-poor and vulnerable communities. The paper draws valuable lessons on how farmers and pastoralists in East Africa use IK weather forecasts for making crop and livestock production decisions and demonstrates that the trust and willingness to apply scientific forecasts by farmers and pastoralists is likely to increase when integrated with IK. Therefore, a systematic documentation of IK, and a framework for integrating IK and scientific weather forecasting from national meteorological agencies can improve accuracy, uptake, and use of weather forecasts.

Techniques and skills of indigenous weather and seasonal climate forecast in Northern Ghana

“…The methodology for collecting and analysing IK has always been qualitative and descriptive even for those that are explored for weather and seasonal climate forecast. Most of these studies only make an inventory of the IEIs using surveys and focus group discussions (Ebhuoma & Simatele, 2019;Nkuba et al, 2020;Radeny et al, 2019). Therefore a critical knowledge gap in the literature is whether it is possible to collect indigenous forecasts and quantitatively analyse them.…”

“…Scientific advancements now make it possible to provide short and long-term climate information services to support farmers' decision-making (Gubler et al, 2020;Johnson et al, 2019;Mullen, 2007;Nyadzi et al, 2019;Scaife et al, 2019). Yet many farmers still use indigenous knowledge (IK) to adjust their farm practices or diversify their production to respond to local climate variability (Ebhuoma & Simatele, 2019;Eriksen et al, 2005;Radeny et al, 2019;Shoko & Shoko, 2012). Other farmers use a combination of meteorological information and IK for their weather and seasonal climate forecasting decisions (Nyadzi et al, 2018;Orlove et al, 2010;Roudier et al, 2014).…”

The Need of Incorporating Indigenous Knowledge Systems into Modern Weather Forecasting Methods

“…This method is an institutionalized knowledge focused on local locations and is rooted in local traditions, built up and passed on over centuries through oral history (Osunade, 1994;Orlove et al, 2010). Despite the IK weather forecasting interest and significance, the absence of systematic documentation and often passed from one generation to the next through oral history, creating a wide inter-generational divide between IK custodians and the young generation (Radeny et al, 2019). Such prediction accuracy is still penurious (Lutgens & Tarbuck, 2010).…”

Designing agrometeorological information services in Ghana by combining local and scientific forecasting knowledge

“…Scholars increasingly recognize that integrating local and scientific forecasting knowledge can strengthen both knowledge systems, leading to better responses to climate variability (Kalanda-Joshua et al, 2011, Lebel, 2013, Kniveton et al, 2015. This thesis defines local forecasting knowledge (LFK) as indigenous or traditional forecasts by smallholder farmers or pastoralists (non-scientists) based on experience in observing biophysical indicators (Radeny et al, 2019, Balehegn et al, 2019. Scientific forecasting knowledge (SFK) refers to forecasts derived from scientific weather and or climate models.…”

“…It is thus more likely to be accepted and influential in decision-making within local communities, compared to SFK (Kniveton et al, 2015). Some have suggested that combining SFK and LFK could increase not only local adoption of SFK, but also the quality of weather and climate information (Crane et al, 2010, Kniveton et al, 2015, Radeny et al, 2019. While LFK is built-in and established in many African communities, including in Ghana, there is a general lack of coordinated research on LFK, including its formal documentation, verification of its quality (e.g., its accuracy and reliability) and methods of integration with modern forecasting knowledge.…”