Mainstreaming forecast based action into national disaster risk management systems: experience from drought risk management in Kenya

Mwangi, Emmah; Taylor, Olivia; Todd, Martin C.; Visman, Emma; Kniveton, D.; Kilavi, Mary; Ndegwa, William; Otieno, George; Waruru, Shamton; Mwangi, Joseph; Ambani, Maurine; Abdillahi, Halima Saado; MacLeod, David; Rowhani, Pedram; Graham, Richard; Colman, Andrew

doi:10.1080/17565529.2021.1984194

Cited by 9 publications

(5 citation statements)

References 26 publications

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“…Further, recent experience in the provision of subseasonal rainfall forecasts through the “Forecasts for Preparedness Action” (ForPAc, http://www.forpac.org) project suggests that a narrative explanation of the underlying drivers, for example, the state of the MJO and associated teleconnections, can usefully augment subseasonal forecasts and add confidence in stakeholder interpretation (White et al, 2022). Our results here reinforce the call for enhanced forecasting capability in EA Meteorological services, continued access to subseasonal forecasting information from global modelling centres, and for enhanced and continued co‐production between meteorological services and stakeholders to make most effective use of forecast skill in EA, in line with the growing body of evidence in the region (Gudoshava et al, 2022b; Hirons et al, 2021; Muita et al, 2021; Mwangi et al, 2022). Such activities can ensure advantage is taken from the opportunity afforded by relatively high climate predictability in EA across subseasonal to seasonal timescales.…”

Section: Conclusion and Recommendationssupporting

confidence: 85%

Variability of rainy season onsets over East Africa

Mwangi,

MacLeod,

Kniveton

et al. 2024

Intl Journal of Climatology

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Over the East Africa region forecasts of the onset of the rainy seasons have the potential to support decision‐making, especially in the largely rain‐fed agricultural sector. However, the understanding of key features of onset remains limited. Here, we analyse the variability of onset and associated drivers at interannual and subseasonal timescales, using several onset definitions. Results show that the onset date is especially variable from year to year in some of the high‐potential agricultural areas (standard deviation >20 days), which has implications for agricultural risk management. The choice of onset definition metric matters; agronomic definitions have limited applicability at the regional scale and are also highly sensitive to the spatial scale of analysis and to the choice of rainfall data. Onset information provided at coarse scales should be used with caution for decision‐making at the local scale; the “hit rate” of coarse‐scale tercile onset information at the local scale is less than 40% on average. To varying degrees, onset is related to total seasonal rainfall and thus to dominant interannual drivers of rainfall, including the Indian Ocean Dipole and ENSO modes in October–December and the western Pacific “V‐gradient” pattern in March–May. However, by analysing the dominant proportion of onset variance unrelated to total rainfall during the climatological season we show a substantial influence of subseasonal drivers, notably the Madden–Julian Oscillation. As such, there is an opportunity for rainfall onset information to be provided across seasonal and subseasonal timescales. Our work reinforces the need for enhanced co‐production of such onset information with stakeholders, especially regarding the choice of metric, alignment of forecasts with livelihood calendars, interpretation of the credibility of information content for local‐level decision‐making, as well as appropriate strategies for staggered risk management interventions informed by forecasts over “seamless” lead times.

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Section: Conclusion and Recommendationssupporting

confidence: 85%

Variability of rainy season onsets over East Africa

Mwangi,

MacLeod,

Kniveton

et al. 2024

Intl Journal of Climatology

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“…The need for longer‐lead seasonal forecasts has been noted as advantageous for user applications where forecast input is necessary at fixed points in the decision chain of user applications (Mwangi et al ., 2021). Results presented here suggest levels of long‐lead skill for the GHA ON season, using the hybrid approach discussed, may be sufficiently high to accommodate earlier issue of seasonal rainfall predictions.…”

Section: Discussionmentioning

confidence: 99%

Skilful long‐lead hybrid predictions of the East African short‐rains season

Colman

2021

Intl Journal of Climatology

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We evaluate the skill of predictions of the East African short-rains (October-December) season, of up to 5 months lead, based on a two-stage dynamical/statistical hybrid approach. The statistical component is a wellestablished, zero-month lead, method based on observed ocean-scale patterns of July-September sea surface temperature. A strong advantage of using this method is that its skill is high and also very robustly measureda correlation of 0.77 between forecast and observed area-mean rainfall is achieved over the 26 years of real-time forecasts. Here, we extend the lead time by driving the statistical component with predicted July-September sea surface temperatures available from a number of dynamical model seasonal prediction systems. There is correlation skill near 0.5 for models initialized in May and positive skill from forecasts initialized as early as the previous October.

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“…Despite the potential value of seasonal forecasts for anticipatory action (for example Mwangi et al, 2022), their use in drought DRFs has historically been limited. The statistical observational/forecasting approach utilised in the Pakistan DRF enables quantitative assessment of the probability of drought in advance of the season end.…”

Section: Reflections and Conclusionmentioning

confidence: 99%

A new drought model for disaster risk management in the Punjab, Sindh and Baluchistan provinces of Pakistan

Black,

Maidment,

Rees

et al. 2024

Front. Clim.

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Drought poses a continual threat to both lives and livelihoods in the Global South. Although the impact on food security from drought could be reduced through early release of funds, the humanitarian sector typically reacts to crises rather than anticipates them. A significant challenge lies in devising a drought monitoring and forecasting system that can function across environmentally and economically diverse regions. This is particularly evident in Pakistan, which encompasses environments ranging from fertile riverbeds to arid deserts. This paper details the development, implementation, and operation of an anticipatory drought Disaster Risk Financing (DRF) programme for the provinces of Punjab, Sindh, and Baluchistan in Pakistan. Key to the DRF development are a new yield model for the primary crop in the target season (winter wheat), and a novel forecasting system for four seasonal drought indicators - namely winter wheat yield, precipitation, normalised difference vegetation index (NDVI) and vegetation health index (VHI). Formal evaluations demonstrate that the forecasts are skillful up to 2 months in advance of the end of the season – enabling anticipatory release of funds. The work presented here is applicable beyond Pakistan. Indeed, the model and the methodologies are sufficiently broad and adaptable to be utilised in arid and semi-arid regions across the Global South.

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Mainstreaming forecast based action into national disaster risk management systems: experience from drought risk management in Kenya

Cited by 9 publications

References 26 publications

Variability of rainy season onsets over East Africa

Variability of rainy season onsets over East Africa

Skilful long‐lead hybrid predictions of the East African short‐rains season

A new drought model for disaster risk management in the Punjab, Sindh and Baluchistan provinces of Pakistan

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