A perspective for advancing climate prediction services in Brazil

Coelho, Caio A.S. ORCID: https://orcid.org/0000-0002-9695-5113; Baker, Jessica C.A.; Spracklen, Dominick V.; Kubota, Paulo Y.; de Souza, Dayana C.; Guimarães, Bruno S.; Figueroa, Silvio N.; Bonatti, José P.; Sampaio, Gilvan; Klingaman, Nicholas P.; Chevuturi, Amulya ORCID: https://orcid.org/0000-0003-2815-7221; Woolnough, Steven J.; Hart, Neil; Zilli, Marcia; Jones, Chris D.. 2022 A perspective for advancing climate prediction services in Brazil [in special issue: Climate Science for Service Partnership Brazil: collaborative research towards climate solutions in Brazil] Climate Resilience and Sustainability, 1 (1), e29. 9, pp. https://doi.org/10.1002/cli2.29

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Official URL: https://doi.org/10.1002/cli2.29

Abstract/Summary

The Climate Science for Service Partnership Brazil (CSSP-Brazil) project provides Brazil and UK partners the opportunity to address important challenges faced by the climate modeling community, including the need to develop subseasonal and seasonal prediction and climate projection services. This paper provides an overview of the climate modeling and prediction research conducted through CSSP-Brazil within the context of a framework to advance climate prediction services in Brazil that includes a research-to-services (R2S) and a services-to-research (S2R) feedback pathway. The paper also highlights plans to advance scientific understanding and capability to produce beneficial climate knowledge and new products to improve climate prediction services to support decisions in various industries in Brazil. Policy-relevant outcomes from climate modeling and prediction exercises illustrated in this paper include supporting stakeholders with climate information provided from weeks to months ahead for (a) improving water management strategies for human consumption, navigation, and agricultural and electricity production; (b) defining crop variety and calendars for food production; and (c) diversifying energy production with alternatives to hydropower.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1002/cli2.29
UKCEH and CEH Sections/Science Areas:	Water Resources (Science Area 2017-)
ISSN:	2692-4587
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	climate modeling, climate projections, climate science, climate services, climate simulations, seasonal prediction, subseasonal prediction
NORA Subject Terms:	Meteorology and Climatology
Date made live:	17 Jan 2022 11:17 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531760

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1002/cli2.29

UKCEH and CEH Sections/Science Areas:

Water Resources (Science Area 2017-)

ISSN:

2692-4587

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

climate modeling, climate projections, climate science, climate services, climate simulations, seasonal prediction, subseasonal prediction