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  Assessing the impact on crop modelling of multi- and uni-variate climate model bias adjustments

Galmarini, S., Solazzo, E., Ferrise, R., Kumar Srivastava, A., Ahmed, M., Asseng, S., Cannon, A. J., Dentener, F., De Sanctis, G., Gaiser, T., Gao, Y., Gayler, S., Gutierrez, J. M., Hoogenboom, G., Iturbide, M., Jury, M., Lange, S., Loukos, H., Maraun, D., Moriondo, M., McGinnis, S., Nendel, C., Padovan, G., Riccio, A., Ripoche, D., Stockle, C. O., Supit, I., Thao, S., Trombi, G., Vrac, M., Weber, T. K. D., Zhao, C. (2024): Assessing the impact on crop modelling of multi- and uni-variate climate model bias adjustments. - Agricultural Systems, 215, 103846.
https://doi.org/10.1016/j.agsy.2023.103846

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Galmarini, S.1, Autor
Solazzo, E.1, Autor
Ferrise, R.1, Autor
Kumar Srivastava, A.1, Autor
Ahmed, M.1, Autor
Asseng, S.1, Autor
Cannon, A. J.1, Autor
Dentener, F.1, Autor
De Sanctis, G.1, Autor
Gaiser, T.1, Autor
Gao, Y.1, Autor
Gayler, S.1, Autor
Gutierrez, J. M.1, Autor
Hoogenboom, G.1, Autor
Iturbide, M.1, Autor
Jury, M.1, Autor
Lange, Stefan2, Autor              
Loukos, H.1, Autor
Maraun, D.1, Autor
Moriondo, M.1, Autor
McGinnis, S.1, AutorNendel, C.1, AutorPadovan, G.1, AutorRiccio, A.1, AutorRipoche, D.1, AutorStockle, C. O.1, AutorSupit, I.1, AutorThao, S.1, AutorTrombi, G.1, AutorVrac, M.1, AutorWeber, T. K. D.1, AutorZhao, C.1, Autor mehr..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Crop models are essential tools for assessing the impact of climate change on national or regional agricultural production. Starting from meteorology, soil and crop management, fertilization and irrigation practices, they predict the yield of specific crop varieties. For long term assessments, climate models are the source of primary information. To make climate model results usable in a specific time frame context, bias adjustment (BA) is required. In fact, climate models tend to deviate from day-to-day values of the physical parameters while conserving the climate variability signal. BA brings the climatic signal to the actual values observed in a specific location and period, and to be representative of a specific period in absolute terms. BA techniques come in different flavours. The broadest categorization is univariate and multivariate methods. Multivariate methods adjust the variables considering possible cross-correlations while univariate methods treat the variables one by one without accounting for possible dependence on one another.

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Sprache(n): eng - Englisch
 Datum: 2023-04-182023-12-182024-01-292024-03-01
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.agsy.2023.103846
Organisational keyword: RD3 - Transformation Pathways
PIKDOMAIN: RD3 - Transformation Pathways
Working Group: Data-Centric Modeling of Cross-Sectoral Impacts
Regional keyword: Europe
Regional keyword: Africa
Model / method: Model Intercomparison
Research topic keyword: Food & Agriculture
Research topic keyword: Land use
MDB-ID: No data to archive
 Art des Abschluß: -

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Titel: Agricultural Systems
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 215 Artikelnummer: 103846 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/agricultural-systems
Publisher: Elsevier