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

Abstract

There are strong calls to integrate scientific and indigenous forecasts to help farmers adapt to climate variability and change. Some studies used qualitative approaches to investigate indigenous people's techniques for forecasting weather and seasonal climate. In this study, we demonstrate how to quantitatively collect indigenous forecast and connect this to scientific forecasts. We identified and characterized the main indigenous ecological indicators (IEIs) local farmers in Northern Ghana use for forecasting. Mental model was constructed to establish the relationship between IEIs and their forecasts. Local farmers were trained to send their rainfall forecast with mobile apps and record observed rainfall with rain gauges. Results show that farmers forecast techniques are based on established cognitive relationship between IEIs and forecast events. Skill assessment shows that on the average both farmers and Ghana Meteorological Agency (GMet) were able to accurately forecast one out of every three daily rainfall events. Performance at the seasonal scale showed that unlike farmers, GMet was unable to predict rainfall cessation in all communities. We conclude that it is possible to determine the techniques and skills of indigenous forecasts in quantitative terms and that indigenous forecasts are not just intuitive but a skill developed over time and with practice.