Pathways to identify and reduce uncertainties in agricultural climate impact assessments.
Journal
Nature food
ISSN: 2662-1355
Titre abrégé: Nat Food
Pays: England
ID NLM: 101761102
Informations de publication
Date de publication:
15 Jul 2024
15 Jul 2024
Historique:
received:
15
03
2023
accepted:
14
06
2024
medline:
16
7
2024
pubmed:
16
7
2024
entrez:
15
7
2024
Statut:
aheadofprint
Résumé
Both climate and impact models are essential for understanding and quantifying the impact of climate change on agricultural productivity. Multi-model ensembles have highlighted considerable uncertainties in these assessments, yet a systematic approach to quantify these uncertainties is lacking. We propose a standardized approach to attribute uncertainties in multi-model ensemble studies, based on insights from the Agricultural Model Intercomparison and Improvement Project. We find that crop model processes are the primary source of uncertainty in agricultural projections (over 50%), excluding unquantified hidden uncertainty that is not explicitly measured within the analyses. We propose multidimensional pathways to reduce uncertainty in climate change impact assessments.
Identifiants
pubmed: 39009735
doi: 10.1038/s43016-024-01014-w
pii: 10.1038/s43016-024-01014-w
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. Springer Nature Limited.
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