Abstract
AbstractThe 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.
Highlights
Wileyonlinelibrary.com/journal/climateresilience 1 dent Research Fellowship, Grant/Award Number: NE/L010976/1; European Research Council (ERC), Grant/Award Numbers: DECAF project, Grant agreement 77149
CSSP-Brazil is providing Institute for Space Research (INPE) 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, which are relevant to various industries in Brazil
The fourth pillar consists of identifying model virtues and deficiencies, including geographical regions where prediction performance can guide advanced planning in application sectors, model aspects in need of improvements, and the generation of prediction information to support climate services based on users’ requirements
Summary
Wileyonlinelibrary.com/journal/climateresilience 1 dent Research Fellowship, Grant/Award Number: NE/L010976/1; European Research Council (ERC), Grant/Award Numbers: DECAF project, Grant agreement 77149. INPE collaborates with Brazilian and UK partners in this project on various climate modeling scientific aspects, to configure and evaluate the performance of global models in representing relevant physical processes to produce climate simulations and predictions for Brazil, including assessing these predictions against observational datasets.
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