2022
DOI: 10.5194/gc-5-151-2022
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Development of forecast information for institutional decision-makers: landslides in India and cyclones in Mozambique

Abstract: Abstract. There remains a gap between the production of scientifically robust forecasts and the translation of these forecasts into useful information such as daily “bulletins” for decision-makers in early warning systems. There is significant published literature on best practice in communicating risk information but very little to guide and provide advice on the process of how these bulletins have been, or should be, developed. This paper reviews two case studies where bulletins were developed for national a… Show more

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Cited by 3 publications
(1 citation statement)
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References 26 publications
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“…The interdisciplinary nature of forecasts, EWS, CBEWS and MHEWS is plural: work is needed to understand the nature and limitations of the scientific and technological process itself, including the use of models, the framing of messaging and the social context of institutions in which science is done (Budimir et al 2022(Budimir et al , 2020Demeritt et al 2013;Morss et al 2016Morss et al , 2005Neußner 2021;Potter et al 2014). It is also needed to understand the communities where the warnings are to be usedrecognising that such communities are themselves often hybrid, consisting of diverse groups with different needs.…”
Section: Models Mapping and Early Warning Systemsmentioning
confidence: 99%
“…The interdisciplinary nature of forecasts, EWS, CBEWS and MHEWS is plural: work is needed to understand the nature and limitations of the scientific and technological process itself, including the use of models, the framing of messaging and the social context of institutions in which science is done (Budimir et al 2022(Budimir et al , 2020Demeritt et al 2013;Morss et al 2016Morss et al , 2005Neußner 2021;Potter et al 2014). It is also needed to understand the communities where the warnings are to be usedrecognising that such communities are themselves often hybrid, consisting of diverse groups with different needs.…”
Section: Models Mapping and Early Warning Systemsmentioning
confidence: 99%