Exploring the landscape of seasonal forecast provision by Global Producing Centres
Dragana Bojovic,
Andria Nicodemou,
Asun Lera St.Clair (),
Isadora Christel and
Francisco J. Doblas-Reyes
Additional contact information
Dragana Bojovic: Barcelona Supercomputing Center
Andria Nicodemou: Barcelona Supercomputing Center
Asun Lera St.Clair: Barcelona Supercomputing Center
Isadora Christel: Barcelona Supercomputing Center
Francisco J. Doblas-Reyes: Barcelona Supercomputing Center
Climatic Change, 2022, vol. 172, issue 1, No 8, 23 pages
Abstract:
Abstract Despite the growing demand for seasonal climate forecasts, there is limited understanding of the landscape of organisations providing this critically important climate information. This study attempts to fill this gap by presenting results from an in-depth dialogue with the organisations entrusted with the provision of seasonal forecasts by the World Meteorological Organisation, known as the Global Producing Centres for Long-Range Forecasts (GPCs-LRF). The results provide an overview and detailed description of the organisational setup, mandate, target audience of GPCs-LRF and their interactions with other centres. Looking beyond the GPCs-LRF to other centres providing seasonal forecasts, some of which have been rapidly taking prominent places in this landscape, revealed a heterogeneous and still maturing community of practice, with an increasing number of players and emerging efforts to produce multi-model ensemble forecasts. The dialogues pointed at the need to not only improve climate models and produce more skilful climate forecasts, but also to improve the transformation of the forecasts into useful and usable products. Finally, using the lenses of credibility, salience and legitimacy, we explore ways to bridge the fragmentation of the information offered across the organisations considered and the people involved in the delivery and use of seasonal forecasts. The paper concludes by suggesting ways to address the boundary crossing between science, policy and society in the context of seasonal climate prediction.
Keywords: GPC; Long-range forecast; Best practices; Science-policy-society (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10584-022-03350-x
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