EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Combining Indigenous and Scientific Forecast for Improved Climate Services in Ghana

Emmanuel Nyadzi, Saskia Werners1, Robbert Biesbroek2, and Fulco Ludwig1
Emmanuel Nyadzi et al.
  • 1Water Systems and Global Change Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
  • 2Public Administration and Policy Group, Wageningen University, Hollandseweg 1, 6706 KN, Wageningen, the Netherlands

Extreme weather events and climate change are affecting the livelihoods of farmers across the globe. Accessible and actionable weather and seasonal climate information can be used as an adaptation tool to support farmers to take adaptive farming decisions. There are increasing calls to integrate scientific forecast with indigenous forecast to improve weather and seasonal climate information at local scale. In Northern Ghana, farmers lament about the quality of scientific forecast information thereby depending on their own indigenous forecast for taking adaptive decisions. To improve this, we developed an integrated probability forecast (IPF) method to combine scientific and indigenous forecast into a single forecast and tested its reliability using binary forecast verification method as a proof of concept. We also evaluated the acceptability of IPF among farmers by computing an index from multiple-response questions with good internal consistency check. Results show that, for reliability, IPF on average performed better than indigenous and scientific forecast at a daily timescale. At seasonal timescale, indigenous forecast overall performed better followed by IPF and then scientific forecast. However, IPF has far greater acceptability potential.  About 93% of farmers prefer IPF method as this provides a reliable forecast, requires less time and at the same time helps deal with contradicting forecast information. Results also show that farmers already use insights from both forecasts (complementary) to inform their farm decisions. However, their complementary method does not resolve the issues of contradicting forecast information. We conclude that, as a proof of concept, integrating indigenous and scientific forecast has high acceptability and can potentially increase forecast reliability and uptake.




How to cite: Nyadzi, E., Werners, S., Biesbroek, R., and Ludwig, F.: Combining Indigenous and Scientific Forecast for Improved Climate Services in Ghana, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22322,, 2020

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  • CC1: Comment on EGU2020-22322, Hervé Kerdiles, 05 May 2020

    Interesting and original presentation, thank you.

    I suppose the scientific forecast is GMet (I am not a meteorologist, so some info on this model would help). I would also like to better understand the time scale of the forecast: are we talking of the next 5 days, 2 weeks, month, 2-3 months, 6 months with both the butterflies, ants, earthworms and GMet? 

    I understood farmers made their forecast and with the rain gauges and Sapelli app compared the forecast with observations, so I suppose we are talking of short term forecast...

  • AC1: Comment on EGU2020-22322, Emmanuel Nyadzi, 05 May 2020

    Thanks for your comments. The weather forecast from both Gmet and Farmers were at daily timescale (24hrs). 

    • AC2: Reply to AC1, Emmanuel Nyadzi, 05 May 2020

      Also, the seasonal forecast was for the entire rainy season(i.e 6 months)

      • CC3: Reply to AC2, Hervé Kerdiles, 06 May 2020

        I understand this seasonal forecast is made with the GMet (like Ghana Met?) model and it consists in predicting above average, normal or below average rainfall. Correct?

        Can farmers do the same with ecological observations?

        • AC3: Reply to CC3, Emmanuel Nyadzi, 06 May 2020

          Yes please, the farmers are also able to predict the seasonal tercile rainfall( above,below normal rainfall) with the indigenous ecological indicators. They, however, indicated that the seasonal time scale is more difficult compared to daily timescale.

    • CC2: Reply to AC1, Hervé Kerdiles, 06 May 2020

      Thank you for the reply. Do you mean that the experiment consisted in forecasting the rainfall of only the next day using ecological indicators or meteo forecast?

      I mean, by observing the behaviour of insects or worms, what is the actual forecast by farmers? Do farmers say "it is going to rain tommorow" or "it is going to rain every day in the next 5 days"  or "it is going to rain 22 mm in the next 3 days"?  is it a qualitative or also quantitative forecast? what period can be covered by this forecast? 

  • AC5: Comment on EGU2020-22322, Emmanuel Nyadzi, 06 May 2020

    We did not collect seasonal climate forecast with the mobile app. we collected the data at a workshop right before the beginning of the rainy season. Following similar procedure just as the  weather forecast.