Mobile Weather Forecasts – Ignitia AB

Obstacle Extreme weather variability due to climate change hinders farmers from capitalizing on rainfall for crop production

Innovation Weather Model

Organization Type For-Profit

Country(ies) Côte d'Ivoire, Ghana, Mali, Niger, Nigeria, Senegal

Contact Ruth Brännvall Email Ignitia Website

Challenge

Extreme weather variability due to climate change hinders farmers from capitalizing on rainfall for crop production, especially in regions near the equator. Predicting the weather based on traditional forecasts is often insufficient for small-scale farmers living in these weather volatile regions. Of the estimated 1.4 billion hectares of cropland worldwide, around 80% is rainfed and accounts for about 60% of the global agricultural output. Reliable and accurate weather forecasts help farmers sow, fertilize and harvest at the ideal time to realize greater yields.

Solution

Ignitia AB has developed a highly accurate weather model to help small- scale farmers in West Africa manage their daily activities to predict water availability and improve their yields to optimize food production. Working in partnership with major telecommunications firms, Ignitia sends daily, customized weather forecasts to farmer’s phones.

Weather forecasts are delivered daily via text message to mobile phones and depict the predicted weather for the next 48 hours specific to the subscriber’s location. Farmers receive updates on the likelihood of rain, timing of rainfall, and intensity of precipitation. Messages are low-cost at $0.03/day and constructed to be user-friendly so that even low-literacy subscribers are able to extract useful information after very little training.

Current global weather forecast models all fail to provide accurate forecasts in the tropics. Ignitia’s forecasts are accurate 84% of the time compared to its competitors, which are accurate only 39% of the time. Designed with end-users in mind, Ignitia delivers highly localized, accurate forecasts and a lightening-fast warning system to alert farmers in case of sudden storms.

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