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  The optimization of model ensemble composition and size can enhance the robustness of crop yield projections

Li, L., Wang, B., Feng, P., Jägermeyr, J., Asseng, S., Müller, C., Macadam, I., Liu, D. L., Waters, C., Zhang, Y., He, Q., Shi, Y., Chen, S., Guo, X., Li, Y., He, J., Feng, H., Yang, G., Tian, H., & Yu, Q. (2023). The optimization of model ensemble composition and size can enhance the robustness of crop yield projections. Communications Earth and Environment, 4:. doi:10.1038/s43247-023-01016-9.

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資料種別: 学術論文

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s43247-023-01016-9.pdf (出版社版), 4MB
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s43247-023-01016-9.pdf
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-
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公開
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application/pdf / [MD5]
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 作成者:
Li, Linchao1, 著者
Wang, Bin1, 著者
Feng, Puyu1, 著者
Jägermeyr, Jonas2, 著者              
Asseng, Senthold1, 著者
Müller, Christoph2, 著者              
Macadam, Ian1, 著者
Liu, De Li1, 著者
Waters, Cathy1, 著者
Zhang, Yajie1, 著者
He, Qinsi1, 著者
Shi, Yu1, 著者
Chen, Shang1, 著者
Guo, Xiaowei1, 著者
Li, Yi1, 著者
He, Jianqiang1, 著者
Feng, Hao1, 著者
Yang, Guijun1, 著者
Tian, Hanqin1, 著者
Yu, Qiang1, 著者
所属:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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キーワード: Agriculture, Climate-change impacts, Environmental impact
 要旨: Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncertainty from Global Gridded Crop Models and Global Climate Models under future climate change. We performed a cluster analysis to identify distinct groups of ensemble members based on their projected outcomes, revealing unique patterns in crop yield projections and corresponding uncertainty levels, particularly for wheat and soybean. Furthermore, our findings suggest that approximately six Global Gridded Crop Models and 10 Global Climate Models are sufficient to capture modeling uncertainty, while a cluster-based selection of 3-4 Global Gridded Crop Models effectively represents the full ensemble. The contribution of individual Global Gridded Crop Models to overall uncertainty varies depending on region and crop type, emphasizing the importance of considering the impact of specific models when selecting models for local-scale applications. Our results emphasize the importance of model composition and ensemble size in identifying the primary sources of uncertainty in crop yield projections, offering valuable guidance for optimizing ensemble configurations in climate-crop modeling studies tailored to specific applications.

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言語: eng - 英語
 日付: 2023-05-032023-09-152023-10-092023-10-09
 出版の状態: Finally published
 ページ: 11
 出版情報: -
 目次: -
 査読: 査読あり
 識別子(DOI, ISBNなど): DOI: 10.1038/s43247-023-01016-9
Organisational keyword: RD2 - Climate Resilience
PIKDOMAIN: RD2 - Climate Resilience
Working Group: Land Use and Resilience
MDB-ID: No data to archive
Research topic keyword: Food & Agriculture
Research topic keyword: Land use
Regional keyword: Global
Model / method: LPJmL
OATYPE: Gold Open Access
 学位: -

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出版物 1

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出版物名: Communications Earth and Environment
種別: 学術雑誌, SCI, Scopus, oa
 著者・編者:
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出版社, 出版地: -
ページ: - 巻号: 4 通巻号: 362 開始・終了ページ: - 識別子(ISBN, ISSN, DOIなど): CoNE: https://publications.pik-potsdam.de/cone/journals/resource/communications-earth-environment
Publisher: Nature