EGU2020-3533
https://doi.org/10.5194/egusphere-egu2020-3533
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Subseasonal forecasts for humanitarian decision-making in Kenya: understanding forecast skill and the latest results from the S2S ForPAc real-time pilot study.

Dave MacLeod1, Mary Kilavi2, Emmah Mwangi3, George Otieno4, Richard Graham5, and Martin Todd6
Dave MacLeod et al.
  • 1Department of Physics, University of Oxford, UK
  • 2Kenya Meteorological Department, Nairobi, Kenya
  • 3International Center for Humanitarian Affairs, Nairobi, Kenya
  • 4IGAD Climate Prediction and Applications Center, Ngong, Kenya
  • 5UK Meteorological Office, Exeter, UK
  • 6Department of Geography, University of Sussex, UK

In 2018 the long rains season in Kenya (March-May) was the wettest ever recorded. The country experienced several multi-day heavy rainfall episodes, leading to dam collapse, land and mudslides. 186 people died due to flooding and 300,000 were left displaced. 

The Kenya Meteorological Department issued several advisories during the season that warned of heavy rainfall events a few days before their occurrence. Ahead of this no warnings were given.

However subseasonal forecasts gave strong indications of the heaviest rainfall episodes, several weeks in advance. With this extra lead time, preparedness actions may have been taken in order to reduce flood risk and save lives. 

To this end, the ForPAc project (Toward Forecast-Based Preparedness Action) has been working in partnerships across Kenya and the UK to evaluate and build trust in subseasonal forecasts, and explore preparedness actions which could be taken in response. Most recently ForPAc has been granted access to real-time subseasonal data as part of phase two of the S2S pilot.

In this presentation we will first show analysis of the S2S hindcasts over East Africa, demonstrating the relatively high levels of subseasonal forecast skill and linking this to a strong MJO teleconnection that models capture relatively well.

In the second part we will describe work with stakeholders to co-design forecast products derived from the S2S data, concluding with a report on the forecasts for the ongoing 2020 long rains season and an evaluation of the way in which these have influenced disaster preparedness.

How to cite: MacLeod, D., Kilavi, M., Mwangi, E., Otieno, G., Graham, R., and Todd, M.: Subseasonal forecasts for humanitarian decision-making in Kenya: understanding forecast skill and the latest results from the S2S ForPAc real-time pilot study., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3533, https://doi.org/10.5194/egusphere-egu2020-3533, 2020

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