Streefkerk, IN, van den Homberg, MJC, Whitfield, S orcid.org/0000-0002-3040-778X et al. (6 more authors) (2022) Contextualising seasonal climate forecasts by integrating local knowledge on drought in Malawi. Climate Services, 25. 100268. ISSN 2405-8807
Abstract
Droughts and changing rainfall patterns due to natural climate variability and climate change, threaten the livelihoods of Malawi’s smallholder farmers, who constitute 80% of the population. Provision of seasonal climate forecasts (SCFs) is one means to potentially increase the resilience of rainfed farming to drought by informing farmers in their agricultural decisions. Local knowledge can play an important role in improving the value of SCFs, by making the forecast better-suited to the local environment and decision-making. This study explores whether the contextual relevance of the information provided in SCFs can be improved through the integration of farmers’ local knowledge in three districts in central and southern Malawi. A forecast threshold model is established that uses meteorological indicators before the rainy season as predictors of dry conditions during that season. Local knowledge informs our selection of the meteorological indicators as potential predictors. Verification of forecasts made with this model shows that meteorological indicators based on local knowledge have a predictive value for forecasting dry conditions in the rainy season. The forecast skill differs per location, with increased skill in the Southern Highlands climate zone. In addition, the local knowledge indicators show increased predictive value in forecasting locally relevant dry conditions, in comparison to the currently-used El Niño-Southern Oscillation (ENSO) indicators. We argue that the inclusion of local knowledge in the current drought information system of Malawi may improve the SCFs for farmers. We show that it is possible to capture local knowledge using observed station and climate reanalysis data. Our approach could benefit National Meteorological and Hydrological Services in the development of relevant climate services and support drought-risk reduction by humanitarian actors.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | Local knowledge; Drought forecasting; Climate services; Rainfed agriculture; Co-production |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Funding Information: | Funder Grant number NERC (Natural Environment Research Council) NE/S005900/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Nov 2021 13:32 |
Last Modified: | 28 Jan 2022 16:20 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.cliser.2021.100268 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:180779 |