4.5 Article

Drivers and Subseasonal Predictability of Heavy Rainfall in Equatorial East Africa and Relationship with Flood Risk

Journal

JOURNAL OF HYDROMETEOROLOGY
Volume 22, Issue 4, Pages 887-903

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-20-0211.1

Keywords

Africa; Madden-Julian oscillation; Forecast verification; skill; Flood events

Funding

  1. Science for Humanitarian Emergencies and Resilience (SHEAR) consortium project Towards Forecast-based Preparedness Action'' (ForPAc) [NE/P000673/1, NE/P000568/1, NE/P000428/1]
  2. U.K. Natural Environment Research Council
  3. Economic and Social Research Council
  4. U.K. Department for International Development
  5. Peter Carpenter African Climate Scholarship programme
  6. U.K. International Development Challenges Fund
  7. SHEAR Doctoral Training Cohort
  8. NERC [NE/P000428/1] Funding Source: UKRI

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Equatorial East Africa faces significant flood risks, which can be mitigated with preemptive action. Subseasonal climate forecasts show skill in predicting extreme rainfall events in the region at lead times of 2 weeks and beyond. Weekly rainfall totals are found to be relevant for fluvial flood risk, with heavy rainfall and high antecedent rainfall conditions identified as key drivers. Promising skill in subseasonal forecasts suggests their potential use in enhancing preparedness activities in the region.
Equatorial East Africa (EEA) suffers from significant flood risks. These can be mitigated with preemptive action; however, currently available early warnings are limited to a few days' lead time. Extending warnings using subseasonal climate forecasts could open a window for more extensive preparedness activity. However, before these forecasts can be used, the basis of their skill and relevance for flood risk must be established. Here we demonstrate that subseasonal forecasts are particularly skillful over EEA. Forecasts can skillfully anticipate weekly upper-quintile rainfall within a season, at lead times of 2 weeks and beyond. We demonstrate the link between the Madden-Julian oscillation (MJO) and extreme rainfall events in the region, and confirm that leading forecast models accurately represent the EEA teleconnection to the MJO. The relevance of weekly rainfall totals for fluvial flood risk in the region is investigated using a long record of streamflow from the Nzoia River in western Kenya. Both heavy rainfall and high antecedent rainfall conditions are identified as key drivers of flood risk, with upper-quintile weekly rainfall shown to skillfully discriminate flood events. We additionally evaluate GloFAS global flood forecasts for the Nzoia basin. Though these are able to anticipate some flooding events with several weeks lead time, analysis suggests action based on these would result in a false alarm more than 50% of the time. Overall, these results build on the scientific evidence base that supports the use of subseasonal forecasts in EEA, and activities to advance their use are discussed.

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