To address the gap between climate information generation and its potential societal appropriation, the scientific community has started to apply innovative methodologies based on interdisciplinary and intersectoral interactions, such as the coproduction of climate services. Here we present the development of a novel subseasonal prediction product for the cumulative precipitation of week-2 (days 8 to 14 since the initial forecast date) to be used by local actors from family farming and related local institutions for the Bermejo Department of the Chaco Province in Argentina. This innovative work is based on an interdisciplinary and intersectorial experience that includes ethnographic fieldwork, a series of coproduction cycles implemented in the territory, based on an implicated science approach, and a robust climate prediction tool development. The prediction product is based on the 16 operational members of the CFSv2 model. It includes the probabilities for week-2 accumulated precipitation exceeding 1mm, 20mm, 50mm and 100mm thresholds. It is currently available online and has been widely used by the local actors since 2022. It performs well in terms of discrimination and outperforms climatology for the 20 mm threshold, although it is closer to climatology for the other thresholds. The coproduction process has ensured the usability of the prediction product by the local community for pursuing their daily activities, especially those related to agriculture production. Some of the benefits of this product include the delivery of probabilistic information that enhances understanding of prediction uncertainty and the use of situated thresholds that are directly relevant to the production of family farms. It also provides localised information, improving the relevance and applicability of the forecasts for users in the territory. The successful experience of this development highlights the importance of involving local communities in the development of climate information products from the outset so that they are socially appropriated.
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Díaz et al. (2026) studied this question.
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